diff --git a/html/SimSolve_logistic.html b/html/SimSolve_logistic.html index 248fc1b..f12ae2f 100644 --- a/html/SimSolve_logistic.html +++ b/html/SimSolve_logistic.html @@ -11,7 +11,7 @@ - + Logistic Regression Power Analysis @@ -475,7 +475,7 @@

Logistic Regression Power Analysis

Phil Chalmers (source adopted from Greg Snow)

-

2024-12-12

+

2024-12-13

diff --git a/html/SimSolve_mediation.html b/html/SimSolve_mediation.html index 6ecf9a1..67ef499 100644 --- a/html/SimSolve_mediation.html +++ b/html/SimSolve_mediation.html @@ -11,7 +11,7 @@ - + Mediation power analysis @@ -475,7 +475,7 @@

Mediation power analysis

Phil Chalmers

-

2024-12-12

+

2024-12-13

@@ -556,190 +556,192 @@

SimSolve code

## # A tibble: 4 × 4
 ##         N       a       b cprime
 ##     <dbl>   <dbl>   <dbl>  <dbl>
-## 1 264.81  0.59161 0.14142   0.39
-## 2  85.519 0.59161 0.26458   0.39
-## 3  49.076 0.59161 0.38730   0.39
-## 4  33.752 0.59161 0.59161   0.39
+## 1 264.62 0.59161 0.14142 0.39 +## 2 85.866 0.59161 0.26458 0.39 +## 3 49.776 0.59161 0.38730 0.39 +## 4 33.608 0.59161 0.59161 0.39

Additional information about the solutions

summary(solved)
## $condition_1
 ## $root
-## [1] 264.8052
+## [1] 264.6209
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 261.7220 267.8394 
+## 261.0348 268.3031 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7951283 0.8047843
+## [1] 0.7951044 0.8048074
 ## 
 ## $terminated_early
 ## [1] TRUE
 ## 
 ## $time
-## [1] 01m 49.54s
+## [1] 01m 44.62s
 ## 
 ## $iterations
-## [1] 94
+## [1] 91
 ## 
 ## $total.replications
-## [1] 32800
+## [1] 31300
 ## 
 ## $tab
 ##            y   x reps
-## 5  0.7718750 240  640
-## 6  0.7775000 243  400
-## 8  0.7775000 247  800
-## 9  0.7945946 248  370
-## 10 0.8085714 249  350
-## 12 0.7812500 252  320
-## 14 0.7357143 254  420
-## 15 0.7830508 256  590
-## 16 0.7747573 257 1030
-## 17 0.8029412 258  340
-## 18 0.7901639 259  610
-## 19 0.7957447 260  470
-## 20 0.8006667 261 1500
-## 21 0.7808081 262  990
-## 22 0.7968000 263 2500
-## 23 0.7980000 264 1500
-## 24 0.8075000 265 2000
-## 25 0.7940000 266 3500
-## 26 0.7964158 267 2790
-## 27 0.8111675 268 3940
-## 28 0.8132530 269 2490
-## 30 0.8200000 273  650
-## 32 0.8366667 276  600
-## 34 0.8109375 280  640
-## 35 0.8028571 281  350
-## 36 0.8162162 283  370
+## 2  0.7193548 220  310
+## 3  0.7562500 242  320
+## 4  0.7439024 243  410
+## 5  0.7323529 245  340
+## 6  0.7782609 246  460
+## 7  0.7975000 248  400
+## 8  0.7738095 249  420
+## 9  0.8075000 250  400
+## 10 0.7883721 251  430
+## 11 0.7881579 252  760
+## 13 0.7945652 254  920
+## 14 0.8114286 255  350
+## 15 0.8121212 256  330
+## 16 0.8166667 257  480
+## 17 0.7666667 258  600
+## 18 0.7874372 259 1990
+## 19 0.7927419 260 1240
+## 20 0.7974619 261 1970
+## 21 0.8083333 262  600
+## 22 0.8140000 263 1000
+## 23 0.7893443 264 1220
+## 24 0.7932584 265  890
+## 25 0.7913333 266 1500
+## 26 0.8096525 267 2590
+## 27 0.7984615 268 3250
+## 28 0.8030000 269 1000
+## 29 0.8104693 270 2770
+## 31 0.8014085 272  710
+## 32 0.8400000 273  500
+## 34 0.8040000 276  500
+## 35 0.8176471 277  340
 ## 
 ## 
 ## $condition_2
 ## $root
-## [1] 85.5189
+## [1] 85.86562
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 84.69951 86.41016 
+## 84.96882 86.82550 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7950228 0.8048860
+## [1] 0.7951230 0.8047894
 ## 
 ## $terminated_early
 ## [1] TRUE
 ## 
 ## $time
-## [1] 02m 1.85s
+## [1] 01m 36.25s
 ## 
 ## $iterations
-## [1] 104
+## [1] 88
 ## 
 ## $total.replications
-## [1] 37800
+## [1] 29800
 ## 
 ## $tab
-##            y  x  reps
-## 5  0.7487805 80   410
-## 7  0.7753086 82  1620
-## 8  0.7867308 83 10400
-## 9  0.7865359 84  7650
-## 10 0.7953012 85  8300
-## 11 0.8033841 86  5910
-## 12 0.8200000 87   550
-## 13 0.8129032 88   310
+##            y  x reps
+## 6  0.7840000 82  500
+## 9  0.7891693 85 9510
+## 10 0.8043876 86 5470
+## 11 0.8082974 87 9280
+## 12 0.8193878 88  980
+## 15 0.8225000 91  800
 ## 
 ## 
 ## $condition_3
 ## $root
-## [1] 49.0756
+## [1] 49.77646
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 48.72800 49.44029 
+## 49.38997 50.16569 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7951202 0.8047925
+## [1] 0.7950696 0.8048406
 ## 
 ## $terminated_early
 ## [1] TRUE
 ## 
 ## $time
-## [1] 01m 44.64s
+## [1] 01m 37.87s
 ## 
 ## $iterations
-## [1] 94
+## [1] 89
 ## 
 ## $total.replications
-## [1] 32800
+## [1] 30300
 ## 
 ## $tab
 ##           y  x  reps
-## 3 0.7664879 47  3730
-## 4 0.7785619 48  7510
-## 5 0.8006916 49  7230
-## 6 0.8141838 50 11210
-## 7 0.8204082 51   490
-## 8 0.8128205 52   390
-## 9 0.8324324 54   370
+## 4 0.7726563 47  1280
+## 5 0.7605263 48  2660
+## 6 0.7939976 49  8330
+## 7 0.7991285 50  4590
+## 8 0.8170611 51 10140
+## 9 0.8116667 52   600
 ## 
 ## 
 ## $condition_4
 ## $root
-## [1] 33.7523
+## [1] 33.60792
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 33.62241 33.88328 
+## 33.47795 33.73867 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7951522 0.8047611
+## [1] 0.7950492 0.8048606
 ## 
 ## $terminated_early
 ## [1] TRUE
 ## 
 ## $time
-## [1] 02m 3.78s
+## [1] 01m 47.95s
 ## 
 ## $iterations
-## [1] 106
+## [1] 94
 ## 
 ## $total.replications
-## [1] 38800
+## [1] 32800
 ## 
 ## $tab
 ##           y  x  reps
-## 2 0.7227116 32 11580
-## 3 0.7727392 33  7630
-## 4 0.8074984 34 15470
-## 5 0.8403846 35  1560
-## 6 0.8666667 36   450
+## 1 0.7284371 32 8510 +## 2 0.7798780 33 8200 +## 3 0.8120623 34 10280 +## 4 0.8482428 35 3130 +## 5 0.8621622 36 370 
plot(solved, 1)
-

+

plot(solved, 2)
-

+

plot(solved, 3)
-

+

# also can plot median history and estimate precision
 plot(solved, 1, type = 'history')
-

+

plot(solved, 1, type = 'density')
## Warning in density.default(x, weights = reps/sum(reps)): Selecting bandwidth
 ## *not* using 'weights'
-

+

diff --git a/html/SimSolve_muthenmuthen2002.html b/html/SimSolve_muthenmuthen2002.html index 60cd29b..143982f 100644 --- a/html/SimSolve_muthenmuthen2002.html +++ b/html/SimSolve_muthenmuthen2002.html @@ -11,7 +11,7 @@ - + Muthen and Muthen (2002) CFA example @@ -475,7 +475,7 @@

Muthen and Muthen (2002) CFA example

Phil Chalmers

-

2024-12-12

+

2024-12-13

@@ -537,64 +537,56 @@

2024-12-12

solved <- SimSolve(design=Design, b=.8, interval=c(100,300), generate=Generate, analyse=Analyse, summarise=Summarise, packages='lavaan', - parallel=TRUE, predCI.tol=.01) -
## 
-## Number of parallel clusters in use: 47
-
## 
-## Iter: 1; Median = 199; E(f(x)) = 0.12; Total.reps = 100Iter: 2; Median = 184; E(f(x)) = 0.09; Total.reps = 200Iter: 3; Median = 170; E(f(x)) = 0.07; Total.reps = 300Iter: 4; Median = 157; E(f(x)) = 0.06; Total.reps = 400Iter: 5; Median = 149; E(f(x)) = 0.05; Total.reps = 500Iter: 6; Median = 139; E(f(x)) = 0.04; Total.reps = 600Iter: 7; Median = 132; E(f(x)) = 0.02; Total.reps = 700Iter: 8; Median = 137; E(f(x)) = 0.02; Total.reps = 800Iter: 9; Median = 134; E(f(x)) = 0.02; Total.reps = 900Iter: 10; Median = 136; E(f(x)) = 0.01; Total.reps = 1000Iter: 11; Median = 145; E(f(x)) = 0.01; Total.reps = 1100Iter: 12; Median = 151; E(f(x)) = 0.01; Total.reps = 1200Iter: 13; Median = 144; E(f(x)) = 0.01; Total.reps = 1300Iter: 14; Median = 150; E(f(x)) = 0.01; Total.reps = 1400Iter: 15; Median = 144; E(f(x)) = 0.01; Total.reps = 1500Iter: 16; Median = 141; E(f(x)) = 0.01; Total.reps = 1600Iter: 17; Median = 146; E(f(x)) = 0.01; Total.reps = 1710Iter: 18; Median = 140; E(f(x)) = 0.01; Total.reps = 1830Iter: 19; Median = 137; E(f(x)) = 0.00; Total.reps = 1960Iter: 20; Median = 141; E(f(x)) = 0.01; Total.reps = 2100Iter: 21; Median = 136; E(f(x)) = 0.00; Total.reps = 2250Iter: 22; Median = 135; E(f(x)) = 0.00; Total.reps = 2410Iter: 23; Median = 138; E(f(x)) = 0.00; Total.reps = 2580Iter: 24; Median = 138; E(f(x)) = 0.00; Total.reps = 2760Iter: 25; Median = 142; E(f(x)) = 0.00; Total.reps = 2950Iter: 26; Median = 140; E(f(x)) = 0.00; Total.reps = 3150Iter: 27; Median = 141; E(f(x)) = 0.00; Total.reps = 3360; k.tol = 0; Pred = 140.2Iter: 28; Median = 138; E(f(x)) = 0.00; Total.reps = 3580; k.tol = 0; Pred = 140.0Iter: 29; Median = 142; E(f(x)) = 0.00; Total.reps = 3810; k.tol = 0; Pred = 140.2Iter: 30; Median = 140; E(f(x)) = 0.00; Total.reps = 4050; k.tol = 0; Pred = 140.0Iter: 31; Median = 142; E(f(x)) = 0.00; Total.reps = 4300; k.tol = 0; Pred = 139.8Iter: 32; Median = 141; E(f(x)) = 0.00; Total.reps = 4560; k.tol = 0; Pred = 140.3Iter: 33; Median = 139; E(f(x)) = 0.00; Total.reps = 4830; k.tol = 0; Pred = 139.3Iter: 34; Median = 137; E(f(x)) = 0.00; Total.reps = 5110; k.tol = 0; Pred = 138.9Iter: 35; Median = 134; E(f(x)) = 0.00; Total.reps = 5400; k.tol = 0; Pred = 139.0Iter: 36; Median = 136; E(f(x)) = 0.00; Total.reps = 5700; k.tol = 0; Pred = 138.4Iter: 37; Median = 136; E(f(x)) = 0.00; Total.reps = 6010; k.tol = 0; Pred = 138.5Iter: 38; Median = 138; E(f(x)) = 0.00; Total.reps = 6330; k.tol = 0; Pred = 140.0Iter: 39; Median = 137; E(f(x)) = 0.00; Total.reps = 6660; k.tol = 0; Pred = 140.2Iter: 40; Median = 138; E(f(x)) = 0.00; Total.reps = 7000; k.tol = 0; Pred = 139.9Iter: 41; Median = 141; E(f(x)) = 0.00; Total.reps = 7350; k.tol = 0; Pred = 139.5Iter: 42; Median = 140; E(f(x)) = 0.00; Total.reps = 7710; k.tol = 0; Pred = 139.2Iter: 43; Median = 139; E(f(x)) = 0.00; Total.reps = 8080; k.tol = 0; Pred = 138.4Iter: 44; Median = 137; E(f(x)) = 0.00; Total.reps = 8460; k.tol = 0; Pred = 138.9Iter: 45; Median = 139; E(f(x)) = 0.00; Total.reps = 8850; k.tol = 0; Pred = 139.0Iter: 46; Median = 137; E(f(x)) = 0.00; Total.reps = 9250; k.tol = 0; Pred = 139.0Iter: 47; Median = 139; E(f(x)) = 0.00; Total.reps = 9660; k.tol = 0; Pred = 139.6Iter: 48; Median = 139; E(f(x)) = 0.00; Total.reps = 10080; k.tol = 0; Pred = 139.7Iter: 49; Median = 138; E(f(x)) = 0.00; Total.reps = 10510; k.tol = 0; Pred = 139.6Iter: 50; Median = 140; E(f(x)) = 0.00; Total.reps = 10950; k.tol = 0; Pred = 139.9Iter: 51; Median = 141; E(f(x)) = 0.00; Total.reps = 11400; k.tol = 0; Pred = 140.8Iter: 52; Median = 141; E(f(x)) = 0.00; Total.reps = 11860; k.tol = 0; Pred = 140.7Iter: 53; Median = 141; E(f(x)) = 0.00; Total.reps = 12330; k.tol = 0; Pred = 141.3Iter: 54; Median = 139; E(f(x)) = 0.00; Total.reps = 12810; k.tol = 0; Pred = 141.8Iter: 55; Median = 140; E(f(x)) = 0.00; Total.reps = 13300; k.tol = 0; Pred = 141.7Iter: 56; Median = 143; E(f(x)) = 0.00; Total.reps = 13800Iter: 57; Median = 144; E(f(x)) = 0.00; Total.reps = 14300Iter: 58; Median = 143; E(f(x)) = 0.00; Total.reps = 14800; k.tol = 0; Pred = 142.9Iter: 59; Median = 140; E(f(x)) = 0.00; Total.reps = 15300; k.tol = 0; Pred = 142.9Iter: 60; Median = 142; E(f(x)) = 0.00; Total.reps = 15800; k.tol = 0; Pred = 142.6Iter: 61; Median = 141; E(f(x)) = 0.00; Total.reps = 16300; k.tol = 0; Pred = 143.9Iter: 62; Median = 142; E(f(x)) = 0.00; Total.reps = 16800; k.tol = 0; Pred = 147.1Iter: 63; Median = 144; E(f(x)) = 0.00; Total.reps = 17300; k.tol = 0; Pred = 143.3Iter: 64; Median = 140; E(f(x)) = 0.00; Total.reps = 17800; k.tol = 0; Pred = 143.3Iter: 65; Median = 142; E(f(x)) = 0.00; Total.reps = 18300; k.tol = 0; Pred = 143.3Iter: 66; Median = 142; E(f(x)) = 0.00; Total.reps = 18800; k.tol = 0; Pred = 143.2Iter: 67; Median = 146; E(f(x)) = 0.00; Total.reps = 19300; k.tol = 0; Pred = 143.4Iter: 68; Median = 142; E(f(x)) = 0.00; Total.reps = 19800; k.tol = 0; Pred = 143.0Iter: 69; Median = 143; E(f(x)) = 0.00; Total.reps = 20300; k.tol = 0; Pred = 142.7Iter: 70; Median = 142; E(f(x)) = 0.00; Total.reps = 20800; k.tol = 0; Pred = 142.8Iter: 71; Median = 143; E(f(x)) = 0.00; Total.reps = 21300; k.tol = 0; Pred = 142.4Iter: 72; Median = 140; E(f(x)) = 0.00; Total.reps = 21800; k.tol = 0; Pred = 142.4Iter: 73; Median = 140; E(f(x)) = 0.00; Total.reps = 22300; k.tol = 0; Pred = 142.5Iter: 74; Median = 140; E(f(x)) = 0.00; Total.reps = 22800; k.tol = 0; Pred = 142.5Iter: 75; Median = 141; E(f(x)) = 0.00; Total.reps = 23300; k.tol = 0; Pred = 142.5Iter: 76; Median = 141; E(f(x)) = 0.00; Total.reps = 23800; k.tol = 0; Pred = 142.2Iter: 77; Median = 141; E(f(x)) = 0.00; Total.reps = 24300; k.tol = 0; Pred = 142.2Iter: 78; Median = 141; E(f(x)) = 0.00; Total.reps = 24800; k.tol = 0; Pred = 142.2Iter: 79; Median = 144; E(f(x)) = 0.00; Total.reps = 25300; k.tol = 0; Pred = 142.1Iter: 80; Median = 141; E(f(x)) = 0.00; Total.reps = 25800; k.tol = 0; Pred = 142.0Iter: 81; Median = 143; E(f(x)) = 0.00; Total.reps = 26300; k.tol = 0; Pred = 142.4Iter: 82; Median = 144; E(f(x)) = 0.00; Total.reps = 26800; k.tol = 0; Pred = 142.2Iter: 83; Median = 143; E(f(x)) = 0.00; Total.reps = 27300; k.tol = 0; Pred = 142.5Iter: 84; Median = 144; E(f(x)) = 0.00; Total.reps = 27800; k.tol = 0; Pred = 142.6Iter: 85; Median = 144; E(f(x)) = 0.00; Total.reps = 28300; k.tol = 0; Pred = 142.9Iter: 86; Median = 143; E(f(x)) = 0.00; Total.reps = 28800; k.tol = 0; Pred = 142.9Iter: 87; Median = 142; E(f(x)) = 0.00; Total.reps = 29300; k.tol = 0; Pred = 143.3Iter: 88; Median = 144; E(f(x)) = 0.00; Total.reps = 29800; k.tol = 0; Pred = 143.4Iter: 89; Median = 142; E(f(x)) = 0.00; Total.reps = 30300; k.tol = 0; Pred = 143.5Iter: 90; Median = 142; E(f(x)) = 0.00; Total.reps = 30800; k.tol = 0; Pred = 143.4Iter: 91; Median = 143; E(f(x)) = 0.00; Total.reps = 31300; k.tol = 0; Pred = 143.4Iter: 92; Median = 142; E(f(x)) = 0.00; Total.reps = 31800; k.tol = 0; Pred = 143.5Iter: 93; Median = 144; E(f(x)) = 0.00; Total.reps = 32300; k.tol = 0; Pred = 143.9Iter: 94; Median = 144; E(f(x)) = 0.00; Total.reps = 32800; k.tol = 0; Pred = 143.8Iter: 95; Median = 142; E(f(x)) = 0.00; Total.reps = 33300; k.tol = 0; Pred = 143.8Iter: 96; Median = 143; E(f(x)) = 0.00; Total.reps = 33800; k.tol = 0; Pred = 144.0Iter: 97; Median = 142; E(f(x)) = 0.00; Total.reps = 34300; k.tol = 0; Pred = 144.1Iter: 98; Median = 144; E(f(x)) = 0.00; Total.reps = 34800; k.tol = 0; Pred = 144.0Iter: 99; Median = 142; E(f(x)) = 0.00; Total.reps = 35300; k.tol = 0; Pred = 143.9Iter: 100; Median = 144; E(f(x)) = 0.00; Total.reps = 35800; k.tol = 0; Pred = 144.0
-## 
-## Solution for N: 144.0
-## 95% Prediction Interval: [140.7, 147.0]
-
solved
+ parallel=TRUE, predCI.tol=.01, verbose=FALSE) +solved 
## # A tibble: 1 × 4
 ##        N  fcor loadings residuals
 ##    <dbl> <dbl>    <dbl>     <dbl>
-## 1 144.05  0.25      0.8      0.36
+## 1 147.75 0.25 0.8 0.36 
summary(solved)
## $root
-## [1] 144.0456
+## [1] 147.7542
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 140.7380 146.9962 
+## 146.3834 149.2755 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7921155 0.8076580
+## [1] 0.7951620 0.8047518
 ## 
 ## $terminated_early
-## [1] FALSE
+## [1] TRUE
 ## 
 ## $time
-## [1] 03m 5.42s
+## [1] 02m 38.47s
 ## 
 ## $iterations
-## [1] 100
+## [1] 88
 ## 
 ## $total.replications
-## [1] 35800
+## [1] 29800
 ## 
 ## $tab
 ##            y   x reps
-## 2  0.7743590 134  390
-## 4  0.7930233 136  860
-## 5  0.7802469 137 1620
-## 6  0.7825301 138 1660
-## 7  0.7934426 139 2440
-## 8  0.7908046 140 4350
-## 9  0.7959559 141 5440
-## 10 0.7926081 142 7170
-## 11 0.7937778 143 4500
-## 12 0.8021053 144 5700
-## 14 0.8049180 146  610
+## 5 0.7875000 144 1200 +## 6 0.7975155 145 1610 +## 7 0.7796610 146 1180 +## 8 0.8009901 147 6060 +## 9 0.7965909 148 5280 +## 10 0.8040441 149 8160 +## 11 0.8081081 150 2960 +## 12 0.8175926 151 1080 +## 13 0.8275000 152 400 +## 14 0.8111111 153 360 
plot(solved)
-

+

plot(solved, type = 'history')
-

+

-
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+
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diff --git a/html/SimSolve_ordlogistic.html b/html/SimSolve_ordlogistic.html index b90f410..ebddac3 100644 --- a/html/SimSolve_ordlogistic.html +++ b/html/SimSolve_ordlogistic.html @@ -11,7 +11,7 @@ - + Ordinal Logistic Regression Power Analysis @@ -475,7 +475,7 @@

Ordinal Logistic Regression Power Analysis

Phil Chalmers (source adopted from Greg Snow)

-

2024-12-12

+

2024-12-13

@@ -516,61 +516,56 @@

Step 1: Define design and NA condition to solve

# terminate when prediction CI between [.895, .905] solved <- SimSolve(design=Design, b=.9, interval=c(30,300), parallel=TRUE, analyse=Analyse, summarise=Summarise, - predCI.tol=.01, maxiter = 200) -
## 
-## Number of parallel clusters in use: 47
-
## 
-## Iter: 1; Median = 164; E(f(x)) = 0.10; Total.reps = 100Iter: 2; Median = 141; E(f(x)) = 0.09; Total.reps = 200Iter: 3; Median = 122; E(f(x)) = 0.06; Total.reps = 300Iter: 4; Median = 106; E(f(x)) = 0.06; Total.reps = 400Iter: 5; Median = 95; E(f(x)) = 0.05; Total.reps = 500Iter: 6; Median = 84; E(f(x)) = 0.04; Total.reps = 600Iter: 7; Median = 93; E(f(x)) = 0.03; Total.reps = 700Iter: 8; Median = 101; E(f(x)) = 0.03; Total.reps = 800Iter: 9; Median = 92; E(f(x)) = 0.02; Total.reps = 900Iter: 10; Median = 99; E(f(x)) = 0.02; Total.reps = 1000Iter: 11; Median = 93; E(f(x)) = 0.02; Total.reps = 1100Iter: 12; Median = 88; E(f(x)) = 0.02; Total.reps = 1200Iter: 13; Median = 78; E(f(x)) = 0.02; Total.reps = 1300Iter: 14; Median = 85; E(f(x)) = 0.02; Total.reps = 1400Iter: 15; Median = 93; E(f(x)) = 0.01; Total.reps = 1500Iter: 16; Median = 95; E(f(x)) = 0.01; Total.reps = 1600Iter: 17; Median = 91; E(f(x)) = 0.01; Total.reps = 1710Iter: 18; Median = 94; E(f(x)) = 0.01; Total.reps = 1830Iter: 19; Median = 99; E(f(x)) = 0.01; Total.reps = 1960Iter: 20; Median = 111; E(f(x)) = 0.01; Total.reps = 2100Iter: 21; Median = 100; E(f(x)) = 0.01; Total.reps = 2250Iter: 22; Median = 97; E(f(x)) = 0.01; Total.reps = 2410Iter: 23; Median = 101; E(f(x)) = 0.01; Total.reps = 2580Iter: 24; Median = 96; E(f(x)) = 0.01; Total.reps = 2760Iter: 25; Median = 100; E(f(x)) = 0.01; Total.reps = 2950Iter: 26; Median = 96; E(f(x)) = 0.01; Total.reps = 3150Iter: 27; Median = 95; E(f(x)) = 0.01; Total.reps = 3360; k.tol = 0; Pred = 98.9Iter: 28; Median = 96; E(f(x)) = 0.01; Total.reps = 3580; k.tol = 0; Pred = 97.9Iter: 29; Median = 93; E(f(x)) = 0.01; Total.reps = 3810; k.tol = 0; Pred = 97.8Iter: 30; Median = 93; E(f(x)) = 0.01; Total.reps = 4050; k.tol = 0; Pred = 97.8Iter: 31; Median = 93; E(f(x)) = 0.01; Total.reps = 4300; k.tol = 0; Pred = 97.9Iter: 32; Median = 98; E(f(x)) = 0.01; Total.reps = 4560; k.tol = 0; Pred = 98.9Iter: 33; Median = 100; E(f(x)) = 0.01; Total.reps = 4830; k.tol = 0; Pred = 97.6Iter: 34; Median = 98; E(f(x)) = 0.01; Total.reps = 5110; k.tol = 0; Pred = 97.4Iter: 35; Median = 96; E(f(x)) = 0.01; Total.reps = 5400; k.tol = 0; Pred = 96.7Iter: 36; Median = 95; E(f(x)) = 0.01; Total.reps = 5700; k.tol = 0; Pred = 96.2Iter: 37; Median = 91; E(f(x)) = 0.01; Total.reps = 6010; k.tol = 0; Pred = 96.2Iter: 38; Median = 95; E(f(x)) = 0.01; Total.reps = 6330; k.tol = 0; Pred = 96.1Iter: 39; Median = 94; E(f(x)) = 0.01; Total.reps = 6660; k.tol = 0; Pred = 96.5Iter: 40; Median = 95; E(f(x)) = 0.01; Total.reps = 7000; k.tol = 0; Pred = 96.6Iter: 41; Median = 93; E(f(x)) = 0.01; Total.reps = 7350; k.tol = 0; Pred = 96.7Iter: 42; Median = 96; E(f(x)) = 0.00; Total.reps = 7710; k.tol = 0; Pred = 97.0Iter: 43; Median = 93; E(f(x)) = 0.00; Total.reps = 8080; k.tol = 0; Pred = 97.0Iter: 44; Median = 93; E(f(x)) = 0.00; Total.reps = 8460; k.tol = 0; Pred = 97.0Iter: 45; Median = 96; E(f(x)) = 0.00; Total.reps = 8850; k.tol = 0; Pred = 96.5Iter: 46; Median = 93; E(f(x)) = 0.00; Total.reps = 9250; k.tol = 0; Pred = 96.5Iter: 47; Median = 95; E(f(x)) = 0.00; Total.reps = 9660; k.tol = 0; Pred = 96.5Iter: 48; Median = 96; E(f(x)) = 0.00; Total.reps = 10080; k.tol = 0; Pred = 96.6Iter: 49; Median = 94; E(f(x)) = 0.00; Total.reps = 10510; k.tol = 0; Pred = 96.2Iter: 50; Median = 93; E(f(x)) = 0.00; Total.reps = 10950; k.tol = 0; Pred = 96.2Iter: 51; Median = 95; E(f(x)) = 0.00; Total.reps = 11400; k.tol = 0; Pred = 96.0Iter: 52; Median = 95; E(f(x)) = 0.00; Total.reps = 11860; k.tol = 0; Pred = 96.0Iter: 53; Median = 93; E(f(x)) = 0.00; Total.reps = 12330; k.tol = 0; Pred = 96.0Iter: 54; Median = 95; E(f(x)) = 0.00; Total.reps = 12810; k.tol = 0; Pred = 96.3Iter: 55; Median = 94; E(f(x)) = 0.00; Total.reps = 13300; k.tol = 0; Pred = 96.5Iter: 56; Median = 96; E(f(x)) = 0.00; Total.reps = 13800; k.tol = 0; Pred = 96.5Iter: 57; Median = 96; E(f(x)) = 0.00; Total.reps = 14300; k.tol = 0; Pred = 96.7Iter: 58; Median = 96; E(f(x)) = 0.00; Total.reps = 14800; k.tol = 0; Pred = 96.8Iter: 59; Median = 95; E(f(x)) = 0.00; Total.reps = 15300; k.tol = 0; Pred = 96.8Iter: 60; Median = 94; E(f(x)) = 0.00; Total.reps = 15800; k.tol = 0; Pred = 96.5Iter: 61; Median = 94; E(f(x)) = 0.00; Total.reps = 16300; k.tol = 0; Pred = 96.5Iter: 62; Median = 94; E(f(x)) = 0.00; Total.reps = 16800; k.tol = 0; Pred = 96.5Iter: 63; Median = 96; E(f(x)) = 0.00; Total.reps = 17300; k.tol = 0; Pred = 96.6Iter: 64; Median = 95; E(f(x)) = 0.00; Total.reps = 17800; k.tol = 0; Pred = 96.3Iter: 65; Median = 95; E(f(x)) = 0.00; Total.reps = 18300; k.tol = 0; Pred = 96.3Iter: 66; Median = 94; E(f(x)) = 0.00; Total.reps = 18800; k.tol = 0; Pred = 96.2Iter: 67; Median = 94; E(f(x)) = 0.00; Total.reps = 19300; k.tol = 0; Pred = 96.5Iter: 68; Median = 96; E(f(x)) = 0.00; Total.reps = 19800; k.tol = 0; Pred = 96.5Iter: 69; Median = 96; E(f(x)) = 0.00; Total.reps = 20300; k.tol = 0; Pred = 96.5Iter: 70; Median = 95; E(f(x)) = 0.00; Total.reps = 20800; k.tol = 0; Pred = 96.5Iter: 71; Median = 96; E(f(x)) = 0.00; Total.reps = 21300; k.tol = 0; Pred = 96.4Iter: 72; Median = 94; E(f(x)) = 0.00; Total.reps = 21800; k.tol = 0; Pred = 96.5Iter: 73; Median = 94; E(f(x)) = 0.00; Total.reps = 22300; k.tol = 0; Pred = 96.5Iter: 74; Median = 94; E(f(x)) = 0.00; Total.reps = 22800; k.tol = 0; Pred = 96.5Iter: 75; Median = 95; E(f(x)) = 0.00; Total.reps = 23300; k.tol = 0; Pred = 96.3Iter: 76; Median = 96; E(f(x)) = 0.00; Total.reps = 23800; k.tol = 0; Pred = 96.0Iter: 77; Median = 96; E(f(x)) = 0.00; Total.reps = 24300; k.tol = 0; Pred = 96.1Iter: 78; Median = 94; E(f(x)) = 0.00; Total.reps = 24800; k.tol = 0; Pred = 96.0Iter: 79; Median = 96; E(f(x)) = 0.00; Total.reps = 25300; k.tol = 0; Pred = 96.0Iter: 80; Median = 95; E(f(x)) = 0.00; Total.reps = 25800; k.tol = 1; Pred = 96.0Iter: 81; Median = 95; E(f(x)) = 0.00; Total.reps = 26300; k.tol = 0; Pred = 96.1Iter: 82; Median = 94; E(f(x)) = 0.00; Total.reps = 26800; k.tol = 0; Pred = 96.1Iter: 83; Median = 96; E(f(x)) = 0.00; Total.reps = 27300; k.tol = 1; Pred = 96.0Iter: 84; Median = 96; E(f(x)) = 0.00; Total.reps = 27800; k.tol = 2; Pred = 95.8
-## 
-## Solution for n: 95.7
-## 95% Prediction Interval: [94.6, 96.9]
-
solved
+ predCI.tol=.01, maxiter = 200, verbose=FALSE) +solved 
## # A tibble: 1 × 4
 ##        n beta0 beta1 beta2
 ##    <dbl> <dbl> <dbl> <dbl>
-## 1 95.748  -0.5  0.25  0.25
+## 1 96.056 -0.5 0.25 0.25 
summary(solved)  # note that prediction CI is within [.895, .905]
## $root
-## [1] 95.74824
+## [1] 96.05581
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 94.57197 96.87598 
+## 94.92464 97.11774 
 ## 
 ## $b
 ## [1] 0.9
 ## 
 ## $predCI.b
-## [1] 0.8956555 0.9041829
+## [1] 0.8950486 0.9047426
 ## 
 ## $terminated_early
 ## [1] TRUE
 ## 
 ## $time
-## [1] 40.23s
+## [1] 41.07s
 ## 
 ## $iterations
-## [1] 85
+## [1] 87
 ## 
 ## $total.replications
-## [1] 28300
+## [1] 29300
 ## 
 ## $tab
-##            y   x reps
-## 5  0.8857143  91  420
-## 7  0.8874636  93 3430
-## 8  0.8919937  94 6370
-## 9  0.8988006  95 6670
-## 10 0.9043224  96 8560
-## 12 0.8944444  98  540
-## 14 0.9213115 100  610
+## y x reps +## 6 0.8838235 91 680 +## 7 0.8718750 92 640 +## 8 0.8900000 93 700 +## 9 0.8945455 94 12100 +## 10 0.8858770 95 4390 +## 11 0.9000000 96 8320 +## 12 0.9058824 97 340 +## 13 0.9189189 98 370 +## 14 0.9100000 99 500 
plot(solved)
-

+

plot(solved, type = 'history')
-

+

-
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+
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diff --git a/html/SimSolve_simr.html b/html/SimSolve_simr.html index f633d6f..1553aa0 100644 --- a/html/SimSolve_simr.html +++ b/html/SimSolve_simr.html @@ -11,7 +11,7 @@ - + Sample size estimation for multi-level model with simr @@ -475,7 +475,7 @@

Sample size estimation for multi-level model with simr

Phil Chalmers

-

2024-12-12

+

2024-12-13

@@ -514,39 +514,32 @@

2024-12-12

# sample size to 95% power res <- SimSolve(design=Design, b=.95, interval=c(10, 50), - generate=Generate, parallel=TRUE, - analyse=Analyse, summarise=Summarise, packages='simr') -
## 
-## Number of parallel clusters in use: 47
-
## 
-## Iter: 1; Median = 29; E(f(x)) = 0.05; Total.reps = 100Iter: 2; Median = 27; E(f(x)) = 0.05; Total.reps = 200Iter: 3; Median = 25; E(f(x)) = 0.05; Total.reps = 300Iter: 4; Median = 20; E(f(x)) = 0.05; Total.reps = 400Iter: 5; Median = 18; E(f(x)) = 0.04; Total.reps = 500Iter: 6; Median = 18; E(f(x)) = 0.04; Total.reps = 600Iter: 7; Median = 17; E(f(x)) = 0.03; Total.reps = 700Iter: 8; Median = 18; E(f(x)) = 0.03; Total.reps = 800Iter: 9; Median = 15; E(f(x)) = 0.01; Total.reps = 900Iter: 10; Median = 16; E(f(x)) = 0.01; Total.reps = 1000Iter: 11; Median = 18; E(f(x)) = 0.01; Total.reps = 1100Iter: 12; Median = 18; E(f(x)) = 0.01; Total.reps = 1200Iter: 13; Median = 15; E(f(x)) = 0.01; Total.reps = 1300Iter: 14; Median = 18; E(f(x)) = 0.00; Total.reps = 1400Iter: 15; Median = 17; E(f(x)) = 0.01; Total.reps = 1500Iter: 16; Median = 16; E(f(x)) = 0.01; Total.reps = 1600Iter: 17; Median = 16; E(f(x)) = 0.02; Total.reps = 1710Iter: 18; Median = 16; E(f(x)) = 0.02; Total.reps = 1830Iter: 19; Median = 18; E(f(x)) = 0.02; Total.reps = 1960Iter: 20; Median = 18; E(f(x)) = 0.02; Total.reps = 2100Iter: 21; Median = 18; E(f(x)) = 0.02; Total.reps = 2250Iter: 22; Median = 17; E(f(x)) = 0.01; Total.reps = 2410Iter: 23; Median = 16; E(f(x)) = 0.02; Total.reps = 2580Iter: 24; Median = 18; E(f(x)) = 0.02; Total.reps = 2760Iter: 25; Median = 18; E(f(x)) = 0.01; Total.reps = 2950Iter: 26; Median = 16; E(f(x)) = 0.02; Total.reps = 3150Iter: 27; Median = 16; E(f(x)) = 0.02; Total.reps = 3360; k.tol = 0; Pred = 17.0Iter: 28; Median = 16; E(f(x)) = 0.02; Total.reps = 3580; k.tol = 0; Pred = 17.0Iter: 29; Median = 17; E(f(x)) = 0.02; Total.reps = 3810; k.tol = 0; Pred = 17.0Iter: 30; Median = 18; E(f(x)) = 0.02; Total.reps = 4050; k.tol = 0; Pred = 18.8Iter: 31; Median = 18; E(f(x)) = 0.02; Total.reps = 4300; k.tol = 0; Pred = 18.7Iter: 32; Median = 18; E(f(x)) = 0.02; Total.reps = 4560; k.tol = 0; Pred = 18.7Iter: 33; Median = 16; E(f(x)) = 0.02; Total.reps = 4830; k.tol = 0; Pred = 17.0Iter: 34; Median = 18; E(f(x)) = 0.02; Total.reps = 5110; k.tol = 0; Pred = 18.9Iter: 35; Median = 18; E(f(x)) = 0.02; Total.reps = 5400; k.tol = 0; Pred = 18.6Iter: 36; Median = 17; E(f(x)) = 0.02; Total.reps = 5700; k.tol = 0; Pred = 17.1Iter: 37; Median = 18; E(f(x)) = 0.02; Total.reps = 6010; k.tol = 0; Pred = 18.5Iter: 38; Median = 16; E(f(x)) = 0.02; Total.reps = 6330; k.tol = 0; Pred = 17.1Iter: 39; Median = 18; E(f(x)) = 0.02; Total.reps = 6660; k.tol = 0; Pred = 18.5Iter: 40; Median = 16; E(f(x)) = 0.02; Total.reps = 7000; k.tol = 0; Pred = 17.1Iter: 41; Median = 16; E(f(x)) = 0.02; Total.reps = 7350; k.tol = 0; Pred = 17.1Iter: 42; Median = 16; E(f(x)) = 0.02; Total.reps = 7710; k.tol = 0; Pred = 17.1Iter: 43; Median = 17; E(f(x)) = 0.02; Total.reps = 8080; k.tol = 0; Pred = 17.4Iter: 44; Median = 16; E(f(x)) = 0.02; Total.reps = 8460; k.tol = 0; Pred = 17.5Iter: 45; Median = 16; E(f(x)) = 0.02; Total.reps = 8850; k.tol = 0; Pred = 17.4Iter: 46; Median = 18; E(f(x)) = 0.02; Total.reps = 9250; k.tol = 1; Pred = 17.5Iter: 47; Median = 16; E(f(x)) = 0.02; Total.reps = 9660; k.tol = 2; Pred = 17.5
-## 
-## Solution for N: 17.5
-## 95% Prediction Interval: [17.0, 18.0]
-
res
+ generate=Generate, parallel=TRUE, verbose=FALSE, + analyse=Analyse, summarise=Summarise, packages='simr') +res 
## # A tibble: 1 × 1
 ##        N
 ##    <dbl>
-## 1 17.473
+## 1 17.531 
summary(res)
## $root
-## [1] 17.47258
+## [1] 17.53129
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 17.02401 18.04473 
+## 17.34188 17.71937 
 ## 
 ## $b
 ## [1] 0.95
 ## 
 ## $predCI.b
-## [1] 0.9394240 0.9588105
+## [1] 0.9438763 0.9554870
 ## 
 ## $terminated_early
 ## [1] TRUE
 ## 
 ## $time
-## [1] 01m 38.28s
+## [1] 01m 37.29s
 ## 
 ## $iterations
 ## [1] 48
@@ -556,15 +549,15 @@ 
2024-12-12

 ## 
 ## $tab
 ##           y  x reps
-## 2 0.8800000 16 4050
-## 3 0.9357143 17 1260
-## 4 0.9582734 18 4170
+## 2 0.8833333 16 3060 +## 3 0.9227273 17 1320 +## 4 0.9633047 18 4660 
plot(res)
-

+

plot(res, type = 'history')
-

+

-
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+
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diff --git a/html/SimSolve_ttests.html b/html/SimSolve_ttests.html index 49aecd1..85a2a91 100644 --- a/html/SimSolve_ttests.html +++ b/html/SimSolve_ttests.html @@ -11,7 +11,7 @@ - + Independent samples t-tests @@ -475,7 +475,7 @@

Independent samples t-tests

Phil Chalmers

-

2024-12-12

+

2024-12-13

@@ -528,67 +528,34 @@

Step 3 — Optimize N over the rows in design

# Terminate if prediction CI is consistently within [.795, .805] solved <- SimSolve(design=Design, b=.8, interval=c(10, 500), generate=Generate, analyse=Analyse, - summarise=Summarise, predCI.tol = .01) -
## 
-## #############
-## Design row 1:
-## 
-##    N   d sig.level   b
-## 1 NA 0.2      0.05 0.8
-## 
-## Iter: 1; Median = 256; E(f(x)) = 0.13; Total.reps = 100Iter: 2; Median = 295; E(f(x)) = 0.11; Total.reps = 200Iter: 3; Median = 331; E(f(x)) = 0.09; Total.reps = 300Iter: 4; Median = 357; E(f(x)) = 0.07; Total.reps = 400Iter: 5; Median = 335; E(f(x)) = 0.06; Total.reps = 500Iter: 6; Median = 355; E(f(x)) = 0.06; Total.reps = 600Iter: 7; Median = 379; E(f(x)) = 0.05; Total.reps = 700Iter: 8; Median = 397; E(f(x)) = 0.04; Total.reps = 800Iter: 9; Median = 382; E(f(x)) = 0.04; Total.reps = 900Iter: 10; Median = 396; E(f(x)) = 0.03; Total.reps = 1000Iter: 11; Median = 384; E(f(x)) = 0.03; Total.reps = 1100Iter: 12; Median = 394; E(f(x)) = 0.03; Total.reps = 1200Iter: 13; Median = 386; E(f(x)) = 0.03; Total.reps = 1300Iter: 14; Median = 393; E(f(x)) = 0.02; Total.reps = 1400Iter: 15; Median = 385; E(f(x)) = 0.02; Total.reps = 1500Iter: 16; Median = 375; E(f(x)) = 0.01; Total.reps = 1600Iter: 17; Median = 354; E(f(x)) = 0.02; Total.reps = 1710Iter: 18; Median = 369; E(f(x)) = 0.02; Total.reps = 1830Iter: 19; Median = 383; E(f(x)) = 0.02; Total.reps = 1960Iter: 20; Median = 390; E(f(x)) = 0.02; Total.reps = 2100Iter: 21; Median = 393; E(f(x)) = 0.02; Total.reps = 2250Iter: 22; Median = 391; E(f(x)) = 0.02; Total.reps = 2410Iter: 23; Median = 387; E(f(x)) = 0.02; Total.reps = 2580Iter: 24; Median = 388; E(f(x)) = 0.02; Total.reps = 2760Iter: 25; Median = 393; E(f(x)) = 0.02; Total.reps = 2950Iter: 26; Median = 389; E(f(x)) = 0.02; Total.reps = 3150Iter: 27; Median = 392; E(f(x)) = 0.02; Total.reps = 3360; k.tol = 0; Pred = 390.6Iter: 28; Median = 389; E(f(x)) = 0.02; Total.reps = 3580; k.tol = 0; Pred = 391.3Iter: 29; Median = 392; E(f(x)) = 0.01; Total.reps = 3810; k.tol = 0; Pred = 390.2Iter: 30; Median = 391; E(f(x)) = 0.01; Total.reps = 4050; k.tol = 0; Pred = 390.1Iter: 31; Median = 388; E(f(x)) = 0.01; Total.reps = 4300; k.tol = 0; Pred = 390.2Iter: 32; Median = 391; E(f(x)) = 0.01; Total.reps = 4560; k.tol = 0; Pred = 390.0Iter: 33; Median = 390; E(f(x)) = 0.01; Total.reps = 4830; k.tol = 0; Pred = 390.3Iter: 34; Median = 391; E(f(x)) = 0.01; Total.reps = 5110; k.tol = 0; Pred = 390.3Iter: 35; Median = 389; E(f(x)) = 0.01; Total.reps = 5400; k.tol = 0; Pred = 389.9Iter: 36; Median = 390; E(f(x)) = 0.01; Total.reps = 5700; k.tol = 0; Pred = 388.5Iter: 37; Median = 387; E(f(x)) = 0.01; Total.reps = 6010; k.tol = 0; Pred = 388.8Iter: 38; Median = 390; E(f(x)) = 0.01; Total.reps = 6330; k.tol = 0; Pred = 388.0Iter: 39; Median = 387; E(f(x)) = 0.01; Total.reps = 6660; k.tol = 0; Pred = 387.7Iter: 40; Median = 388; E(f(x)) = 0.01; Total.reps = 7000; k.tol = 0; Pred = 387.4Iter: 41; Median = 389; E(f(x)) = 0.01; Total.reps = 7350; k.tol = 0; Pred = 387.6Iter: 42; Median = 390; E(f(x)) = 0.01; Total.reps = 7710; k.tol = 0; Pred = 387.8Iter: 43; Median = 387; E(f(x)) = 0.01; Total.reps = 8080; k.tol = 0; Pred = 387.7Iter: 44; Median = 388; E(f(x)) = 0.01; Total.reps = 8460; k.tol = 0; Pred = 387.6Iter: 45; Median = 389; E(f(x)) = 0.01; Total.reps = 8850; k.tol = 0; Pred = 388.3Iter: 46; Median = 388; E(f(x)) = 0.01; Total.reps = 9250; k.tol = 0; Pred = 388.7Iter: 47; Median = 388; E(f(x)) = 0.01; Total.reps = 9660; k.tol = 0; Pred = 388.5Iter: 48; Median = 388; E(f(x)) = 0.01; Total.reps = 10080; k.tol = 0; Pred = 388.4Iter: 49; Median = 387; E(f(x)) = 0.01; Total.reps = 10510; k.tol = 0; Pred = 388.5Iter: 50; Median = 390; E(f(x)) = 0.01; Total.reps = 10950; k.tol = 0; Pred = 388.5Iter: 51; Median = 389; E(f(x)) = 0.01; Total.reps = 11400; k.tol = 0; Pred = 387.8Iter: 52; Median = 388; E(f(x)) = 0.01; Total.reps = 11860; k.tol = 0; Pred = 387.5Iter: 53; Median = 388; E(f(x)) = 0.01; Total.reps = 12330; k.tol = 0; Pred = 387.7Iter: 54; Median = 388; E(f(x)) = 0.01; Total.reps = 12810; k.tol = 0; Pred = 387.9Iter: 55; Median = 389; E(f(x)) = 0.01; Total.reps = 13300; k.tol = 0; Pred = 388.6Iter: 56; Median = 390; E(f(x)) = 0.01; Total.reps = 13800; k.tol = 0; Pred = 388.5Iter: 57; Median = 388; E(f(x)) = 0.01; Total.reps = 14300; k.tol = 0; Pred = 388.3Iter: 58; Median = 389; E(f(x)) = 0.01; Total.reps = 14800; k.tol = 0; Pred = 388.3Iter: 59; Median = 388; E(f(x)) = 0.01; Total.reps = 15300; k.tol = 0; Pred = 388.4Iter: 60; Median = 388; E(f(x)) = 0.01; Total.reps = 15800; k.tol = 0; Pred = 388.1Iter: 61; Median = 388; E(f(x)) = 0.01; Total.reps = 16300; k.tol = 0; Pred = 388.3Iter: 62; Median = 390; E(f(x)) = 0.01; Total.reps = 16800; k.tol = 0; Pred = 388.6Iter: 63; Median = 389; E(f(x)) = 0.01; Total.reps = 17300; k.tol = 0; Pred = 389.0Iter: 64; Median = 390; E(f(x)) = 0.01; Total.reps = 17800; k.tol = 0; Pred = 389.2Iter: 65; Median = 388; E(f(x)) = 0.01; Total.reps = 18300; k.tol = 0; Pred = 388.9Iter: 66; Median = 388; E(f(x)) = 0.01; Total.reps = 18800; k.tol = 0; Pred = 389.0Iter: 67; Median = 387; E(f(x)) = 0.01; Total.reps = 19300; k.tol = 0; Pred = 388.8Iter: 68; Median = 388; E(f(x)) = 0.01; Total.reps = 19800; k.tol = 0; Pred = 388.8Iter: 69; Median = 384; E(f(x)) = 0.01; Total.reps = 20300; k.tol = 0; Pred = 388.7Iter: 70; Median = 378; E(f(x)) = 0.01; Total.reps = 20800; k.tol = 0; Pred = 388.7Iter: 71; Median = 384; E(f(x)) = 0.01; Total.reps = 21300; k.tol = 0; Pred = 386.7Iter: 72; Median = 378; E(f(x)) = 0.01; Total.reps = 21800; k.tol = 0; Pred = 387.0Iter: 73; Median = 385; E(f(x)) = 0.01; Total.reps = 22300; k.tol = 0; Pred = 388.5Iter: 74; Median = 388; E(f(x)) = 0.01; Total.reps = 22800; k.tol = 0; Pred = 388.9Iter: 75; Median = 389; E(f(x)) = 0.01; Total.reps = 23300; k.tol = 0; Pred = 388.5Iter: 76; Median = 390; E(f(x)) = 0.01; Total.reps = 23800; k.tol = 0; Pred = 389.0Iter: 77; Median = 388; E(f(x)) = 0.01; Total.reps = 24300; k.tol = 0; Pred = 389.8Iter: 78; Median = 388; E(f(x)) = 0.01; Total.reps = 24800; k.tol = 0; Pred = 389.1Iter: 79; Median = 388; E(f(x)) = 0.01; Total.reps = 25300; k.tol = 0; Pred = 389.0Iter: 80; Median = 389; E(f(x)) = 0.01; Total.reps = 25800; k.tol = 0; Pred = 389.7Iter: 81; Median = 390; E(f(x)) = 0.01; Total.reps = 26300; k.tol = 0; Pred = 389.9Iter: 82; Median = 390; E(f(x)) = 0.01; Total.reps = 26800; k.tol = 0; Pred = 389.3Iter: 83; Median = 390; E(f(x)) = 0.01; Total.reps = 27300; k.tol = 0; Pred = 389.0Iter: 84; Median = 388; E(f(x)) = 0.01; Total.reps = 27800; k.tol = 0; Pred = 390.0Iter: 85; Median = 389; E(f(x)) = 0.01; Total.reps = 28300; k.tol = 0; Pred = 390.1Iter: 86; Median = 390; E(f(x)) = 0.01; Total.reps = 28800; k.tol = 0; Pred = 390.2Iter: 87; Median = 390; E(f(x)) = 0.01; Total.reps = 29300; k.tol = 0; Pred = 389.5Iter: 88; Median = 388; E(f(x)) = 0.01; Total.reps = 29800; k.tol = 0; Pred = 389.4Iter: 89; Median = 388; E(f(x)) = 0.01; Total.reps = 30300; k.tol = 0; Pred = 389.4Iter: 90; Median = 389; E(f(x)) = 0.01; Total.reps = 30800; k.tol = 0; Pred = 389.5Iter: 91; Median = 390; E(f(x)) = 0.01; Total.reps = 31300; k.tol = 0; Pred = 390.2Iter: 92; Median = 388; E(f(x)) = 0.01; Total.reps = 31800; k.tol = 0; Pred = 391.0Iter: 93; Median = 390; E(f(x)) = 0.01; Total.reps = 32300; k.tol = 0; Pred = 392.6Iter: 94; Median = 390; E(f(x)) = 0.01; Total.reps = 32800; k.tol = 0; Pred = 395.3Iter: 95; Median = 389; E(f(x)) = 0.01; Total.reps = 33300; k.tol = 0; Pred = 393.2Iter: 96; Median = 390; E(f(x)) = 0.01; Total.reps = 33800; k.tol = 0; Pred = 391.6Iter: 97; Median = 390; E(f(x)) = 0.01; Total.reps = 34300; k.tol = 0; Pred = 390.8Iter: 98; Median = 390; E(f(x)) = 0.01; Total.reps = 34800; k.tol = 0; Pred = 390.8Iter: 99; Median = 388; E(f(x)) = 0.01; Total.reps = 35300; k.tol = 0; Pred = 390.6Iter: 100; Median = 389; E(f(x)) = 0.01; Total.reps = 35800; k.tol = 0; Pred = 390.8
-## 
-## Solution for N: 390.8
-## 95% Prediction Interval: [384.0, 394.4]
-## 
-## #############
-## Design row 2:
-## 
-##    N   d sig.level   b
-## 1 NA 0.5      0.05 0.8
-## 
-## Iter: 1; Median = 254; E(f(x)) = 0.20; Total.reps = 100Iter: 2; Median = 213; E(f(x)) = 0.20; Total.reps = 200Iter: 3; Median = 181; E(f(x)) = 0.20; Total.reps = 300Iter: 4; Median = 152; E(f(x)) = 0.20; Total.reps = 400Iter: 5; Median = 127; E(f(x)) = 0.19; Total.reps = 500Iter: 6; Median = 109; E(f(x)) = 0.19; Total.reps = 600Iter: 7; Median = 93; E(f(x)) = 0.18; Total.reps = 700Iter: 8; Median = 79; E(f(x)) = 0.17; Total.reps = 800Iter: 9; Median = 66; E(f(x)) = 0.16; Total.reps = 900Iter: 10; Median = 56; E(f(x)) = 0.14; Total.reps = 1000Iter: 11; Median = 48; E(f(x)) = 0.12; Total.reps = 1100Iter: 12; Median = 56; E(f(x)) = 0.10; Total.reps = 1200Iter: 13; Median = 64; E(f(x)) = 0.10; Total.reps = 1300Iter: 14; Median = 57; E(f(x)) = 0.09; Total.reps = 1400Iter: 15; Median = 63; E(f(x)) = 0.08; Total.reps = 1500Iter: 16; Median = 56; E(f(x)) = 0.07; Total.reps = 1600Iter: 17; Median = 62; E(f(x)) = 0.07; Total.reps = 1710Iter: 18; Median = 59; E(f(x)) = 0.07; Total.reps = 1830Iter: 19; Median = 62; E(f(x)) = 0.06; Total.reps = 1960Iter: 20; Median = 65; E(f(x)) = 0.06; Total.reps = 2100Iter: 21; Median = 76; E(f(x)) = 0.06; Total.reps = 2250Iter: 22; Median = 66; E(f(x)) = 0.06; Total.reps = 2410Iter: 23; Median = 63; E(f(x)) = 0.05; Total.reps = 2580Iter: 24; Median = 67; E(f(x)) = 0.05; Total.reps = 2760Iter: 25; Median = 61; E(f(x)) = 0.05; Total.reps = 2950Iter: 26; Median = 66; E(f(x)) = 0.05; Total.reps = 3150Iter: 27; Median = 62; E(f(x)) = 0.05; Total.reps = 3360; k.tol = 0; Pred = 64.3Iter: 28; Median = 64; E(f(x)) = 0.05; Total.reps = 3580; k.tol = 0; Pred = 63.5Iter: 29; Median = 64; E(f(x)) = 0.04; Total.reps = 3810; k.tol = 0; Pred = 65.0Iter: 30; Median = 64; E(f(x)) = 0.04; Total.reps = 4050; k.tol = 0; Pred = 64.8Iter: 31; Median = 66; E(f(x)) = 0.04; Total.reps = 4300; k.tol = 0; Pred = 64.7Iter: 32; Median = 64; E(f(x)) = 0.04; Total.reps = 4560; k.tol = 0; Pred = 64.9Iter: 33; Median = 65; E(f(x)) = 0.04; Total.reps = 4830; k.tol = 0; Pred = 65.1Iter: 34; Median = 72; E(f(x)) = 0.04; Total.reps = 5110; k.tol = 0; Pred = 65.0Iter: 35; Median = 67; E(f(x)) = 0.04; Total.reps = 5400; k.tol = 0; Pred = 64.9Iter: 36; Median = 66; E(f(x)) = 0.04; Total.reps = 5700; k.tol = 0; Pred = 65.3Iter: 37; Median = 65; E(f(x)) = 0.04; Total.reps = 6010; k.tol = 0; Pred = 65.3Iter: 38; Median = 66; E(f(x)) = 0.04; Total.reps = 6330; k.tol = 0; Pred = 65.4Iter: 39; Median = 66; E(f(x)) = 0.04; Total.reps = 6660; k.tol = 0; Pred = 65.1Iter: 40; Median = 63; E(f(x)) = 0.04; Total.reps = 7000; k.tol = 0; Pred = 64.8Iter: 41; Median = 64; E(f(x)) = 0.04; Total.reps = 7350; k.tol = 0; Pred = 64.6Iter: 42; Median = 63; E(f(x)) = 0.04; Total.reps = 7710; k.tol = 0; Pred = 64.5Iter: 43; Median = 61; E(f(x)) = 0.03; Total.reps = 8080; k.tol = 0; Pred = 64.5Iter: 44; Median = 63; E(f(x)) = 0.03; Total.reps = 8460; k.tol = 0; Pred = 64.5Iter: 45; Median = 66; E(f(x)) = 0.03; Total.reps = 8850; k.tol = 0; Pred = 64.4Iter: 46; Median = 63; E(f(x)) = 0.03; Total.reps = 9250; k.tol = 0; Pred = 64.3Iter: 47; Median = 63; E(f(x)) = 0.03; Total.reps = 9660; k.tol = 0; Pred = 64.2Iter: 48; Median = 61; E(f(x)) = 0.03; Total.reps = 10080; k.tol = 0; Pred = 64.3Iter: 49; Median = 64; E(f(x)) = 0.03; Total.reps = 10510; k.tol = 0; Pred = 64.2Iter: 50; Median = 63; E(f(x)) = 0.03; Total.reps = 10950; k.tol = 0; Pred = 64.2Iter: 51; Median = 66; E(f(x)) = 0.03; Total.reps = 11400; k.tol = 0; Pred = 64.1Iter: 52; Median = 64; E(f(x)) = 0.03; Total.reps = 11860; k.tol = 0; Pred = 64.0Iter: 53; Median = 63; E(f(x)) = 0.03; Total.reps = 12330; k.tol = 0; Pred = 64.0Iter: 54; Median = 66; E(f(x)) = 0.03; Total.reps = 12810; k.tol = 0; Pred = 63.9Iter: 55; Median = 65; E(f(x)) = 0.03; Total.reps = 13300; k.tol = 0; Pred = 63.9Iter: 56; Median = 66; E(f(x)) = 0.03; Total.reps = 13800; k.tol = 0; Pred = 63.8Iter: 57; Median = 66; E(f(x)) = 0.03; Total.reps = 14300; k.tol = 0; Pred = 63.8Iter: 58; Median = 66; E(f(x)) = 0.03; Total.reps = 14800; k.tol = 0; Pred = 63.8Iter: 59; Median = 66; E(f(x)) = 0.03; Total.reps = 15300; k.tol = 0; Pred = 63.8Iter: 60; Median = 64; E(f(x)) = 0.03; Total.reps = 15800; k.tol = 0; Pred = 63.8Iter: 61; Median = 65; E(f(x)) = 0.03; Total.reps = 16300; k.tol = 0; Pred = 63.9Iter: 62; Median = 66; E(f(x)) = 0.03; Total.reps = 16800; k.tol = 0; Pred = 64.0Iter: 63; Median = 66; E(f(x)) = 0.03; Total.reps = 17300; k.tol = 0; Pred = 64.0Iter: 64; Median = 66; E(f(x)) = 0.03; Total.reps = 17800; k.tol = 0; Pred = 64.0Iter: 65; Median = 66; E(f(x)) = 0.03; Total.reps = 18300; k.tol = 0; Pred = 64.0Iter: 66; Median = 64; E(f(x)) = 0.03; Total.reps = 18800; k.tol = 0; Pred = 64.0Iter: 67; Median = 65; E(f(x)) = 0.03; Total.reps = 19300; k.tol = 0; Pred = 63.8Iter: 68; Median = 66; E(f(x)) = 0.03; Total.reps = 19800; k.tol = 0; Pred = 63.9Iter: 69; Median = 64; E(f(x)) = 0.03; Total.reps = 20300; k.tol = 0; Pred = 64.0Iter: 70; Median = 66; E(f(x)) = 0.03; Total.reps = 20800; k.tol = 0; Pred = 64.1Iter: 71; Median = 64; E(f(x)) = 0.03; Total.reps = 21300; k.tol = 0; Pred = 64.1Iter: 72; Median = 65; E(f(x)) = 0.03; Total.reps = 21800; k.tol = 0; Pred = 64.1Iter: 73; Median = 66; E(f(x)) = 0.03; Total.reps = 22300; k.tol = 0; Pred = 64.1Iter: 74; Median = 64; E(f(x)) = 0.03; Total.reps = 22800; k.tol = 0; Pred = 64.2Iter: 75; Median = 64; E(f(x)) = 0.03; Total.reps = 23300; k.tol = 0; Pred = 64.1Iter: 76; Median = 64; E(f(x)) = 0.03; Total.reps = 23800; k.tol = 0; Pred = 64.2Iter: 77; Median = 65; E(f(x)) = 0.03; Total.reps = 24300; k.tol = 0; Pred = 64.2Iter: 78; Median = 66; E(f(x)) = 0.03; Total.reps = 24800; k.tol = 0; Pred = 64.1Iter: 79; Median = 66; E(f(x)) = 0.03; Total.reps = 25300; k.tol = 0; Pred = 64.1Iter: 80; Median = 66; E(f(x)) = 0.03; Total.reps = 25800; k.tol = 0; Pred = 64.1Iter: 81; Median = 64; E(f(x)) = 0.03; Total.reps = 26300; k.tol = 0; Pred = 64.1Iter: 82; Median = 65; E(f(x)) = 0.03; Total.reps = 26800; k.tol = 0; Pred = 64.0Iter: 83; Median = 66; E(f(x)) = 0.03; Total.reps = 27300; k.tol = 0; Pred = 64.0Iter: 84; Median = 66; E(f(x)) = 0.03; Total.reps = 27800; k.tol = 0; Pred = 64.0Iter: 85; Median = 64; E(f(x)) = 0.03; Total.reps = 28300; k.tol = 0; Pred = 64.0Iter: 86; Median = 64; E(f(x)) = 0.03; Total.reps = 28800; k.tol = 0; Pred = 64.0Iter: 87; Median = 65; E(f(x)) = 0.02; Total.reps = 29300; k.tol = 0; Pred = 64.1Iter: 88; Median = 65; E(f(x)) = 0.02; Total.reps = 29800; k.tol = 0; Pred = 64.1Iter: 89; Median = 65; E(f(x)) = 0.02; Total.reps = 30300; k.tol = 0; Pred = 64.0Iter: 90; Median = 65; E(f(x)) = 0.02; Total.reps = 30800; k.tol = 0; Pred = 64.0Iter: 91; Median = 65; E(f(x)) = 0.02; Total.reps = 31300; k.tol = 0; Pred = 64.0Iter: 92; Median = 65; E(f(x)) = 0.02; Total.reps = 31800; k.tol = 0; Pred = 64.0Iter: 93; Median = 63; E(f(x)) = 0.02; Total.reps = 32300; k.tol = 0; Pred = 64.0Iter: 94; Median = 64; E(f(x)) = 0.02; Total.reps = 32800; k.tol = 1; Pred = 64.0Iter: 95; Median = 65; E(f(x)) = 0.02; Total.reps = 33300; k.tol = 2; Pred = 64.0
-## 
-## Solution for N: 64.0
-## 95% Prediction Interval: [63.5, 64.5]
-## 
-## #############
-## Design row 3:
-## 
-##    N   d sig.level   b
-## 1 NA 0.8      0.05 0.8
-## 
-## Iter: 1; Median = 254; E(f(x)) = 0.20; Total.reps = 100Iter: 2; Median = 213; E(f(x)) = 0.20; Total.reps = 200Iter: 3; Median = 179; E(f(x)) = 0.20; Total.reps = 300Iter: 4; Median = 152; E(f(x)) = 0.20; Total.reps = 400Iter: 5; Median = 127; E(f(x)) = 0.20; Total.reps = 500Iter: 6; Median = 109; E(f(x)) = 0.20; Total.reps = 600Iter: 7; Median = 92; E(f(x)) = 0.20; Total.reps = 700Iter: 8; Median = 79; E(f(x)) = 0.20; Total.reps = 800Iter: 9; Median = 66; E(f(x)) = 0.20; Total.reps = 900Iter: 10; Median = 58; E(f(x)) = 0.20; Total.reps = 1000Iter: 11; Median = 48; E(f(x)) = 0.20; Total.reps = 1100Iter: 12; Median = 41; E(f(x)) = 0.19; Total.reps = 1200Iter: 13; Median = 35; E(f(x)) = 0.18; Total.reps = 1300Iter: 14; Median = 33; E(f(x)) = 0.17; Total.reps = 1400Iter: 15; Median = 29; E(f(x)) = 0.16; Total.reps = 1500Iter: 16; Median = 26; E(f(x)) = 0.16; Total.reps = 1600Iter: 17; Median = 24; E(f(x)) = 0.15; Total.reps = 1710Iter: 18; Median = 22; E(f(x)) = 0.14; Total.reps = 1830Iter: 19; Median = 24; E(f(x)) = 0.13; Total.reps = 1960Iter: 20; Median = 26; E(f(x)) = 0.12; Total.reps = 2100Iter: 21; Median = 22; E(f(x)) = 0.11; Total.reps = 2250Iter: 22; Median = 25; E(f(x)) = 0.11; Total.reps = 2410Iter: 23; Median = 27; E(f(x)) = 0.11; Total.reps = 2580Iter: 24; Median = 26; E(f(x)) = 0.10; Total.reps = 2760Iter: 25; Median = 27; E(f(x)) = 0.10; Total.reps = 2950Iter: 26; Median = 24; E(f(x)) = 0.09; Total.reps = 3150Iter: 27; Median = 26; E(f(x)) = 0.09; Total.reps = 3360; k.tol = 0; Pred = 25.8Iter: 28; Median = 24; E(f(x)) = 0.09; Total.reps = 3580; k.tol = 0; Pred = 25.4Iter: 29; Median = 26; E(f(x)) = 0.09; Total.reps = 3810; k.tol = 0; Pred = 26.0Iter: 30; Median = 25; E(f(x)) = 0.08; Total.reps = 4050; k.tol = 0; Pred = 26.3Iter: 31; Median = 29; E(f(x)) = 0.08; Total.reps = 4300; k.tol = 0; Pred = 26.4Iter: 32; Median = 27; E(f(x)) = 0.08; Total.reps = 4560; k.tol = 0; Pred = 26.2Iter: 33; Median = 26; E(f(x)) = 0.08; Total.reps = 4830; k.tol = 0; Pred = 26.3Iter: 34; Median = 27; E(f(x)) = 0.08; Total.reps = 5110; k.tol = 0; Pred = 26.2Iter: 35; Median = 25; E(f(x)) = 0.08; Total.reps = 5400; k.tol = 0; Pred = 26.3Iter: 36; Median = 27; E(f(x)) = 0.07; Total.reps = 5700; k.tol = 0; Pred = 26.3Iter: 37; Median = 27; E(f(x)) = 0.07; Total.reps = 6010; k.tol = 0; Pred = 26.3Iter: 38; Median = 26; E(f(x)) = 0.07; Total.reps = 6330; k.tol = 0; Pred = 26.2Iter: 39; Median = 27; E(f(x)) = 0.07; Total.reps = 6660; k.tol = 0; Pred = 26.0Iter: 40; Median = 27; E(f(x)) = 0.07; Total.reps = 7000; k.tol = 0; Pred = 26.0Iter: 41; Median = 24; E(f(x)) = 0.07; Total.reps = 7350; k.tol = 0; Pred = 25.9Iter: 42; Median = 27; E(f(x)) = 0.07; Total.reps = 7710; k.tol = 0; Pred = 25.8Iter: 43; Median = 24; E(f(x)) = 0.07; Total.reps = 8080; k.tol = 0; Pred = 25.8Iter: 44; Median = 25; E(f(x)) = 0.07; Total.reps = 8460; k.tol = 0; Pred = 25.8Iter: 45; Median = 25; E(f(x)) = 0.06; Total.reps = 8850; k.tol = 0; Pred = 25.8Iter: 46; Median = 25; E(f(x)) = 0.06; Total.reps = 9250; k.tol = 0; Pred = 25.8Iter: 47; Median = 25; E(f(x)) = 0.06; Total.reps = 9660; k.tol = 0; Pred = 25.7Iter: 48; Median = 25; E(f(x)) = 0.06; Total.reps = 10080; k.tol = 0; Pred = 25.8Iter: 49; Median = 27; E(f(x)) = 0.06; Total.reps = 10510; k.tol = 0; Pred = 25.7Iter: 50; Median = 26; E(f(x)) = 0.06; Total.reps = 10950; k.tol = 0; Pred = 25.9Iter: 51; Median = 27; E(f(x)) = 0.06; Total.reps = 11400; k.tol = 0; Pred = 25.8Iter: 52; Median = 27; E(f(x)) = 0.06; Total.reps = 11860; k.tol = 0; Pred = 25.7Iter: 53; Median = 27; E(f(x)) = 0.06; Total.reps = 12330; k.tol = 0; Pred = 25.7Iter: 54; Median = 25; E(f(x)) = 0.06; Total.reps = 12810; k.tol = 0; Pred = 25.8Iter: 55; Median = 27; E(f(x)) = 0.06; Total.reps = 13300; k.tol = 0; Pred = 25.8Iter: 56; Median = 26; E(f(x)) = 0.06; Total.reps = 13800; k.tol = 0; Pred = 25.7Iter: 57; Median = 27; E(f(x)) = 0.06; Total.reps = 14300; k.tol = 0; Pred = 25.7Iter: 58; Median = 27; E(f(x)) = 0.06; Total.reps = 14800; k.tol = 0; Pred = 25.7Iter: 59; Median = 25; E(f(x)) = 0.06; Total.reps = 15300; k.tol = 0; Pred = 25.6Iter: 60; Median = 25; E(f(x)) = 0.06; Total.reps = 15800; k.tol = 0; Pred = 25.6Iter: 61; Median = 26; E(f(x)) = 0.06; Total.reps = 16300; k.tol = 0; Pred = 25.6Iter: 62; Median = 25; E(f(x)) = 0.06; Total.reps = 16800; k.tol = 0; Pred = 25.5Iter: 63; Median = 27; E(f(x)) = 0.05; Total.reps = 17300; k.tol = 0; Pred = 25.5Iter: 64; Median = 25; E(f(x)) = 0.05; Total.reps = 17800; k.tol = 0; Pred = 25.5Iter: 65; Median = 25; E(f(x)) = 0.05; Total.reps = 18300; k.tol = 0; Pred = 25.5Iter: 66; Median = 26; E(f(x)) = 0.05; Total.reps = 18800; k.tol = 0; Pred = 25.5Iter: 67; Median = 27; E(f(x)) = 0.05; Total.reps = 19300; k.tol = 0; Pred = 25.5Iter: 68; Median = 25; E(f(x)) = 0.05; Total.reps = 19800; k.tol = 0; Pred = 25.5Iter: 69; Median = 27; E(f(x)) = 0.05; Total.reps = 20300; k.tol = 0; Pred = 25.5Iter: 70; Median = 25; E(f(x)) = 0.05; Total.reps = 20800; k.tol = 0; Pred = 25.5Iter: 71; Median = 26; E(f(x)) = 0.05; Total.reps = 21300; k.tol = 0; Pred = 25.6Iter: 72; Median = 27; E(f(x)) = 0.05; Total.reps = 21800; k.tol = 0; Pred = 25.6Iter: 73; Median = 25; E(f(x)) = 0.05; Total.reps = 22300; k.tol = 0; Pred = 25.5Iter: 74; Median = 27; E(f(x)) = 0.05; Total.reps = 22800; k.tol = 0; Pred = 25.5Iter: 75; Median = 27; E(f(x)) = 0.05; Total.reps = 23300; k.tol = 0; Pred = 25.5Iter: 76; Median = 26; E(f(x)) = 0.05; Total.reps = 23800; k.tol = 0; Pred = 25.5Iter: 77; Median = 27; E(f(x)) = 0.05; Total.reps = 24300; k.tol = 0; Pred = 25.5Iter: 78; Median = 27; E(f(x)) = 0.05; Total.reps = 24800; k.tol = 0; Pred = 25.4Iter: 79; Median = 27; E(f(x)) = 0.05; Total.reps = 25300; k.tol = 0; Pred = 25.5Iter: 80; Median = 27; E(f(x)) = 0.05; Total.reps = 25800; k.tol = 0; Pred = 25.5Iter: 81; Median = 27; E(f(x)) = 0.05; Total.reps = 26300; k.tol = 0; Pred = 25.5Iter: 82; Median = 25; E(f(x)) = 0.05; Total.reps = 26800; k.tol = 0; Pred = 25.4Iter: 83; Median = 26; E(f(x)) = 0.05; Total.reps = 27300; k.tol = 0; Pred = 25.4Iter: 84; Median = 24; E(f(x)) = 0.05; Total.reps = 27800; k.tol = 0; Pred = 25.5Iter: 85; Median = 24; E(f(x)) = 0.05; Total.reps = 28300; k.tol = 0; Pred = 25.4Iter: 86; Median = 26; E(f(x)) = 0.05; Total.reps = 28800; k.tol = 0; Pred = 25.5Iter: 87; Median = 25; E(f(x)) = 0.05; Total.reps = 29300; k.tol = 0; Pred = 25.5Iter: 88; Median = 26; E(f(x)) = 0.05; Total.reps = 29800; k.tol = 0; Pred = 25.5Iter: 89; Median = 24; E(f(x)) = 0.04; Total.reps = 30300; k.tol = 0; Pred = 25.5Iter: 90; Median = 26; E(f(x)) = 0.04; Total.reps = 30800; k.tol = 0; Pred = 25.5Iter: 91; Median = 26; E(f(x)) = 0.04; Total.reps = 31300; k.tol = 0; Pred = 25.5Iter: 92; Median = 25; E(f(x)) = 0.04; Total.reps = 31800; k.tol = 0; Pred = 25.5Iter: 93; Median = 26; E(f(x)) = 0.04; Total.reps = 32300; k.tol = 0; Pred = 25.4Iter: 94; Median = 24; E(f(x)) = 0.04; Total.reps = 32800; k.tol = 0; Pred = 25.4Iter: 95; Median = 24; E(f(x)) = 0.04; Total.reps = 33300; k.tol = 0; Pred = 25.4Iter: 96; Median = 26; E(f(x)) = 0.04; Total.reps = 33800; k.tol = 0; Pred = 25.4Iter: 97; Median = 25; E(f(x)) = 0.04; Total.reps = 34300; k.tol = 0; Pred = 25.4Iter: 98; Median = 24; E(f(x)) = 0.04; Total.reps = 34800; k.tol = 0; Pred = 25.4Iter: 99; Median = 26; E(f(x)) = 0.04; Total.reps = 35300; k.tol = 0; Pred = 25.4Iter: 100; Median = 24; E(f(x)) = 0.04; Total.reps = 35800; k.tol = 0; Pred = 25.4
-## 
-## Solution for N: 25.4
-## 95% Prediction Interval: [25.1, 25.7]
-
solved
+ summarise=Summarise, predCI.tol = .01, verbose=FALSE) +solved 
## # A tibble: 3 × 3
 ##         N     d sig.level
 ##     <dbl> <dbl>     <dbl>
-## 1 390.83    0.2      0.05
-## 2  63.996   0.5      0.05
-## 3  25.374   0.8      0.05
+## 1 389.23 0.2 0.05 +## 2 63.557 0.5 0.05 +## 3 25.502 0.8 0.05 
summary(solved)
## $condition_1
 ## $root
-## [1] 390.835
+## [1] 389.2322
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 384.0354 394.3622 
+## 386.0742 392.4425 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7932390 0.8065939
+## [1] 0.7949810 0.8049263
 ## 
 ## $terminated_early
 ## [1] FALSE
 ## 
 ## $time
-## [1] 01m 0.23s
+## [1] 01m 0.70s
 ## 
 ## $iterations
 ## [1] 100
@@ -597,75 +564,83 @@ 
Step 3 — Optimize N over the rows in design

 ## [1] 35800
 ## 
 ## $tab
-##            y   x  reps
-## 10 0.7870000 378  1000
-## 14 0.8172727 384  1100
-## 15 0.7700000 385   600
-## 17 0.7966825 387  2110
-## 18 0.7958439 388 11790
-## 19 0.7953052 389  6390
-## 20 0.8004287 390  9330
-## 21 0.8074468 391   940
-## 22 0.8159091 392   440
-## 23 0.8272727 393   440
+##            y   x reps
+## 12 0.7575758 372  330
+## 14 0.7968750 376  320
+## 15 0.7880000 377  500
+## 16 0.7805556 378  720
+## 17 0.7926829 380  820
+## 18 0.7900000 381  600
+## 19 0.7857143 382 1750
+## 20 0.8080000 383  500
+## 21 0.8027027 384  370
+## 22 0.7838493 385 7430
+## 23 0.7886792 386 3180
+## 24 0.7995025 387 8040
+## 25 0.8033088 388 2720
+## 26 0.8069892 389 1860
+## 27 0.7966667 390  900
+## 28 0.8055556 391  900
+## 29 0.8172131 392 1220
+## 33 0.8133333 399  450
 ## 
 ## 
 ## $condition_2
 ## $root
-## [1] 63.99584
+## [1] 63.5575
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 63.46294 64.52673 
+## 62.88036 64.24890 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7950675 0.8048432
+## [1] 0.7950432 0.8048664
 ## 
 ## $terminated_early
-## [1] TRUE
+## [1] FALSE
 ## 
 ## $time
-## [1] 51.44s
+## [1] 55.36s
 ## 
 ## $iterations
-## [1] 96
+## [1] 100
 ## 
 ## $total.replications
-## [1] 33800
+## [1] 35800
 ## 
 ## $tab
-##            y  x  reps
-## 5  0.7642857 61   980
-## 6  0.7600000 62   450
-## 7  0.7988796 63  3570
-## 8  0.7967908 64  7790
-## 9  0.8111543 65  7710
-## 10 0.8177596 66 10980
-## 11 0.8382979 67   470
+##           y  x  reps
+## 3 0.7564516 59   620
+## 4 0.7592233 60  1030
+## 5 0.7944000 61  1250
+## 6 0.7913504 62 11330
+## 7 0.7921779 63  6520
+## 8 0.8017671 64 12450
+## 9 0.8305556 65   720
 ## 
 ## 
 ## $condition_3
 ## $root
-## [1] 25.37412
+## [1] 25.50231
 ## 
 ## $predCI.root
 ##   CI_2.5  CI_97.5 
-## 25.06405 25.69477 
+## 25.09729 25.99578 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7943833 0.8055013
+## [1] 0.7944488 0.8054380
 ## 
 ## $terminated_early
 ## [1] FALSE
 ## 
 ## $time
-## [1] 54.97s
+## [1] 55.06s
 ## 
 ## $iterations
 ## [1] 100
@@ -675,24 +650,24 @@ 
Step 3 — Optimize N over the rows in design

 ## 
 ## $tab
 ##           y  x  reps
-## 2 0.7786885 24  4880
-## 3 0.7875682 25  9170
-## 4 0.8116806 26  8390
-## 5 0.8267196 27 11340
-## 6 0.8200000 29   350
+## 2 0.7465116 23 860 +## 3 0.7752072 24 13270 +## 4 0.7906009 25 6490 +## 5 0.8055385 26 13000 +## 6 0.8166667 27 360 
plot(solved, 1)
-

+

plot(solved, 2)
-

+

plot(solved, 3)
-

+

# also can plot median history and estimate precision
 plot(solved, 1, type = 'history')
-

+

plot(solved, 1, type = 'density')
## Warning in density.default(x, weights = reps/sum(reps)): Selecting bandwidth
 ## *not* using 'weights'
-

+

# verify with true power from pwr package
 library(pwr)
 pwr.t.test(d=.2, power = .8, sig.level = .05)
@@ -734,10 +709,10 @@

Step 3 — Optimize N over the rows in design

## 
 ##      Two-sample t test power calculation 
 ## 
-##               n = 390.835
+##               n = 389.2322
 ##               d = 0.2
 ##       sig.level = 0.05
-##           power = 0.7974169
+##           power = 0.7957921
 ##     alternative = two.sided
 ## 
 ## NOTE: n is number in *each* group
@@ -745,10 +720,10 @@

Step 3 — Optimize N over the rows in design

## 
 ##      Two-sample t test power calculation 
 ## 
-##               n = 63.99584
+##               n = 63.5575
 ##               d = 0.5
 ##       sig.level = 0.05
-##           power = 0.8014337
+##           power = 0.7986964
 ##     alternative = two.sided
 ## 
 ## NOTE: n is number in *each* group
@@ -756,10 +731,10 @@

Step 3 — Optimize N over the rows in design

## 
 ##      Two-sample t test power calculation 
 ## 
-##               n = 25.37412
+##               n = 25.50231
 ##               d = 0.8
 ##       sig.level = 0.05
-##           power = 0.7975794
+##           power = 0.7996433
 ##     alternative = two.sided
 ## 
 ## NOTE: n is number in *each* group
@@ -769,10 +744,10 @@

Step 3 — Optimize N over the rows in design

## 
 ##      Two-sample t test power calculation 
 ## 
-##               n = 391
+##               n = 390
 ##               d = 0.2
 ##       sig.level = 0.05
-##           power = 0.7975836
+##           power = 0.7965718
 ##     alternative = two.sided
 ## 
 ## NOTE: n is number in *each* group
@@ -824,133 +799,100 @@

Solving effect sizes

# is based on whether the prediction CI is consistently within [.795, .805] solved <- SimSolve(design=Design, b = .8, interval=c(.1, 2), generate=Generate, analyse=Analyse, - summarise=Summarise, integer=FALSE, predCI.tol=.01) -
## 
-## #############
-## Design row 1:
-## 
-##     N  d sig.level   b
-## 1 100 NA      0.05 0.8
-## 
-## Iter: 1; Median = 1.050; E(f(x)) = 0.20; Total.reps = 100Iter: 2; Median = 0.892; E(f(x)) = 0.20; Total.reps = 200Iter: 3; Median = 0.760; E(f(x)) = 0.20; Total.reps = 300Iter: 4; Median = 0.650; E(f(x)) = 0.20; Total.reps = 400Iter: 5; Median = 0.558; E(f(x)) = 0.20; Total.reps = 500Iter: 6; Median = 0.482; E(f(x)) = 0.18; Total.reps = 600Iter: 7; Median = 0.418; E(f(x)) = 0.16; Total.reps = 700Iter: 8; Median = 0.365; E(f(x)) = 0.12; Total.reps = 800Iter: 9; Median = 0.409; E(f(x)) = 0.11; Total.reps = 900Iter: 10; Median = 0.460; E(f(x)) = 0.10; Total.reps = 1000Iter: 11; Median = 0.415; E(f(x)) = 0.10; Total.reps = 1100Iter: 12; Median = 0.380; E(f(x)) = 0.09; Total.reps = 1200Iter: 13; Median = 0.411; E(f(x)) = 0.09; Total.reps = 1300Iter: 14; Median = 0.385; E(f(x)) = 0.08; Total.reps = 1400Iter: 15; Median = 0.408; E(f(x)) = 0.07; Total.reps = 1500Iter: 16; Median = 0.389; E(f(x)) = 0.07; Total.reps = 1600Iter: 17; Median = 0.360; E(f(x)) = 0.06; Total.reps = 1710Iter: 18; Median = 0.386; E(f(x)) = 0.06; Total.reps = 1830Iter: 19; Median = 0.366; E(f(x)) = 0.05; Total.reps = 1960Iter: 20; Median = 0.384; E(f(x)) = 0.05; Total.reps = 2100Iter: 21; Median = 0.398; E(f(x)) = 0.05; Total.reps = 2250Iter: 22; Median = 0.413; E(f(x)) = 0.04; Total.reps = 2410Iter: 23; Median = 0.400; E(f(x)) = 0.04; Total.reps = 2580Iter: 24; Median = 0.410; E(f(x)) = 0.04; Total.reps = 2760Iter: 25; Median = 0.402; E(f(x)) = 0.04; Total.reps = 2950Iter: 26; Median = 0.390; E(f(x)) = 0.04; Total.reps = 3150Iter: 27; Median = 0.401; E(f(x)) = 0.04; Total.reps = 3360; k.tol = 0; Pred = 0.397Iter: 28; Median = 0.392; E(f(x)) = 0.04; Total.reps = 3580; k.tol = 0; Pred = 0.395Iter: 29; Median = 0.383; E(f(x)) = 0.04; Total.reps = 3810; k.tol = 0; Pred = 0.393Iter: 30; Median = 0.368; E(f(x)) = 0.04; Total.reps = 4050; k.tol = 0; Pred = 0.393Iter: 31; Median = 0.381; E(f(x)) = 0.03; Total.reps = 4300; k.tol = 0; Pred = 0.396Iter: 32; Median = 0.388; E(f(x)) = 0.03; Total.reps = 4560; k.tol = 0; Pred = 0.398Iter: 33; Median = 0.397; E(f(x)) = 0.03; Total.reps = 4830; k.tol = 0; Pred = 0.396Iter: 34; Median = 0.390; E(f(x)) = 0.03; Total.reps = 5110; k.tol = 0; Pred = 0.398Iter: 35; Median = 0.395; E(f(x)) = 0.03; Total.reps = 5400; k.tol = 0; Pred = 0.398Iter: 36; Median = 0.401; E(f(x)) = 0.03; Total.reps = 5700; k.tol = 0; Pred = 0.396Iter: 37; Median = 0.397; E(f(x)) = 0.03; Total.reps = 6010; k.tol = 0; Pred = 0.395Iter: 38; Median = 0.392; E(f(x)) = 0.03; Total.reps = 6330; k.tol = 0; Pred = 0.395Iter: 39; Median = 0.396; E(f(x)) = 0.03; Total.reps = 6660; k.tol = 0; Pred = 0.395Iter: 40; Median = 0.392; E(f(x)) = 0.03; Total.reps = 7000; k.tol = 0; Pred = 0.395Iter: 41; Median = 0.396; E(f(x)) = 0.03; Total.reps = 7350; k.tol = 0; Pred = 0.395Iter: 42; Median = 0.399; E(f(x)) = 0.03; Total.reps = 7710; k.tol = 0; Pred = 0.395Iter: 43; Median = 0.396; E(f(x)) = 0.03; Total.reps = 8080; k.tol = 0; Pred = 0.395Iter: 44; Median = 0.394; E(f(x)) = 0.03; Total.reps = 8460; k.tol = 0; Pred = 0.395Iter: 45; Median = 0.395; E(f(x)) = 0.03; Total.reps = 8850; k.tol = 0; Pred = 0.394Iter: 46; Median = 0.394; E(f(x)) = 0.03; Total.reps = 9250; k.tol = 0; Pred = 0.395Iter: 47; Median = 0.395; E(f(x)) = 0.03; Total.reps = 9660; k.tol = 0; Pred = 0.394Iter: 48; Median = 0.394; E(f(x)) = 0.02; Total.reps = 10080; k.tol = 0; Pred = 0.395Iter: 49; Median = 0.395; E(f(x)) = 0.02; Total.reps = 10510; k.tol = 0; Pred = 0.394Iter: 50; Median = 0.394; E(f(x)) = 0.02; Total.reps = 10950; k.tol = 0; Pred = 0.394Iter: 51; Median = 0.393; E(f(x)) = 0.02; Total.reps = 11400; k.tol = 0; Pred = 0.394Iter: 52; Median = 0.389; E(f(x)) = 0.02; Total.reps = 11860; k.tol = 0; Pred = 0.394Iter: 53; Median = 0.392; E(f(x)) = 0.02; Total.reps = 12330; k.tol = 0; Pred = 0.394Iter: 54; Median = 0.394; E(f(x)) = 0.02; Total.reps = 12810; k.tol = 0; Pred = 0.395Iter: 55; Median = 0.394; E(f(x)) = 0.02; Total.reps = 13300; k.tol = 0; Pred = 0.395Iter: 56; Median = 0.395; E(f(x)) = 0.02; Total.reps = 13800; k.tol = 0; Pred = 0.395Iter: 57; Median = 0.397; E(f(x)) = 0.02; Total.reps = 14300; k.tol = 0; Pred = 0.395Iter: 58; Median = 0.395; E(f(x)) = 0.02; Total.reps = 14800; k.tol = 0; Pred = 0.396Iter: 59; Median = 0.396; E(f(x)) = 0.02; Total.reps = 15300; k.tol = 0; Pred = 0.395Iter: 60; Median = 0.395; E(f(x)) = 0.02; Total.reps = 15800; k.tol = 0; Pred = 0.395Iter: 61; Median = 0.395; E(f(x)) = 0.02; Total.reps = 16300; k.tol = 0; Pred = 0.395Iter: 62; Median = 0.394; E(f(x)) = 0.02; Total.reps = 16800; k.tol = 0; Pred = 0.395Iter: 63; Median = 0.394; E(f(x)) = 0.02; Total.reps = 17300; k.tol = 0; Pred = 0.395Iter: 64; Median = 0.394; E(f(x)) = 0.02; Total.reps = 17800; k.tol = 0; Pred = 0.395Iter: 65; Median = 0.394; E(f(x)) = 0.02; Total.reps = 18300; k.tol = 0; Pred = 0.394Iter: 66; Median = 0.393; E(f(x)) = 0.02; Total.reps = 18800; k.tol = 0; Pred = 0.394Iter: 67; Median = 0.394; E(f(x)) = 0.02; Total.reps = 19300; k.tol = 0; Pred = 0.394Iter: 68; Median = 0.394; E(f(x)) = 0.02; Total.reps = 19800; k.tol = 0; Pred = 0.395Iter: 69; Median = 0.394; E(f(x)) = 0.02; Total.reps = 20300; k.tol = 0; Pred = 0.395Iter: 70; Median = 0.395; E(f(x)) = 0.02; Total.reps = 20800; k.tol = 0; Pred = 0.395Iter: 71; Median = 0.395; E(f(x)) = 0.02; Total.reps = 21300; k.tol = 0; Pred = 0.395Iter: 72; Median = 0.395; E(f(x)) = 0.02; Total.reps = 21800; k.tol = 0; Pred = 0.395Iter: 73; Median = 0.395; E(f(x)) = 0.02; Total.reps = 22300; k.tol = 0; Pred = 0.395Iter: 74; Median = 0.395; E(f(x)) = 0.02; Total.reps = 22800; k.tol = 0; Pred = 0.395Iter: 75; Median = 0.394; E(f(x)) = 0.02; Total.reps = 23300; k.tol = 0; Pred = 0.395Iter: 76; Median = 0.394; E(f(x)) = 0.02; Total.reps = 23800; k.tol = 0; Pred = 0.395Iter: 77; Median = 0.395; E(f(x)) = 0.02; Total.reps = 24300; k.tol = 0; Pred = 0.395Iter: 78; Median = 0.394; E(f(x)) = 0.02; Total.reps = 24800; k.tol = 0; Pred = 0.395Iter: 79; Median = 0.395; E(f(x)) = 0.02; Total.reps = 25300; k.tol = 0; Pred = 0.395Iter: 80; Median = 0.395; E(f(x)) = 0.02; Total.reps = 25800; k.tol = 0; Pred = 0.395Iter: 81; Median = 0.395; E(f(x)) = 0.02; Total.reps = 26300; k.tol = 0; Pred = 0.395Iter: 82; Median = 0.395; E(f(x)) = 0.02; Total.reps = 26800; k.tol = 0; Pred = 0.396Iter: 83; Median = 0.395; E(f(x)) = 0.02; Total.reps = 27300; k.tol = 0; Pred = 0.396Iter: 84; Median = 0.395; E(f(x)) = 0.02; Total.reps = 27800; k.tol = 0; Pred = 0.396Iter: 85; Median = 0.395; E(f(x)) = 0.02; Total.reps = 28300; k.tol = 0; Pred = 0.396Iter: 86; Median = 0.396; E(f(x)) = 0.02; Total.reps = 28800; k.tol = 1; Pred = 0.395Iter: 87; Median = 0.395; E(f(x)) = 0.02; Total.reps = 29300; k.tol = 2; Pred = 0.395
-## 
-## Solution for d: 0.395
-## 95% Prediction Interval: [0.394, 0.397]
-## 
-## #############
-## Design row 2:
-## 
-##    N  d sig.level   b
-## 1 50 NA      0.05 0.8
-## 
-## Iter: 1; Median = 1.050; E(f(x)) = 0.20; Total.reps = 100Iter: 2; Median = 0.892; E(f(x)) = 0.20; Total.reps = 200Iter: 3; Median = 0.760; E(f(x)) = 0.18; Total.reps = 300Iter: 4; Median = 0.650; E(f(x)) = 0.17; Total.reps = 400Iter: 5; Median = 0.558; E(f(x)) = 0.13; Total.reps = 500Iter: 6; Median = 0.635; E(f(x)) = 0.12; Total.reps = 600Iter: 7; Median = 0.571; E(f(x)) = 0.11; Total.reps = 700Iter: 8; Median = 0.498; E(f(x)) = 0.08; Total.reps = 800Iter: 9; Median = 0.562; E(f(x)) = 0.07; Total.reps = 900Iter: 10; Median = 0.508; E(f(x)) = 0.05; Total.reps = 1000Iter: 11; Median = 0.554; E(f(x)) = 0.05; Total.reps = 1100Iter: 12; Median = 0.601; E(f(x)) = 0.04; Total.reps = 1200Iter: 13; Median = 0.560; E(f(x)) = 0.04; Total.reps = 1300Iter: 14; Median = 0.593; E(f(x)) = 0.03; Total.reps = 1400Iter: 15; Median = 0.641; E(f(x)) = 0.04; Total.reps = 1500Iter: 16; Median = 0.598; E(f(x)) = 0.03; Total.reps = 1600Iter: 17; Median = 0.632; E(f(x)) = 0.03; Total.reps = 1710Iter: 18; Median = 0.603; E(f(x)) = 0.03; Total.reps = 1830Iter: 19; Median = 0.574; E(f(x)) = 0.03; Total.reps = 1960Iter: 20; Median = 0.600; E(f(x)) = 0.03; Total.reps = 2100Iter: 21; Median = 0.579; E(f(x)) = 0.03; Total.reps = 2250Iter: 22; Median = 0.558; E(f(x)) = 0.03; Total.reps = 2410Iter: 23; Median = 0.521; E(f(x)) = 0.03; Total.reps = 2580Iter: 24; Median = 0.554; E(f(x)) = 0.02; Total.reps = 2760Iter: 25; Median = 0.571; E(f(x)) = 0.03; Total.reps = 2950Iter: 26; Median = 0.557; E(f(x)) = 0.02; Total.reps = 3150Iter: 27; Median = 0.568; E(f(x)) = 0.02; Total.reps = 3360; k.tol = 0; Pred = 0.562Iter: 28; Median = 0.559; E(f(x)) = 0.02; Total.reps = 3580; k.tol = 0; Pred = 0.565Iter: 29; Median = 0.567; E(f(x)) = 0.02; Total.reps = 3810; k.tol = 0; Pred = 0.565Iter: 30; Median = 0.560; E(f(x)) = 0.02; Total.reps = 4050; k.tol = 0; Pred = 0.564Iter: 31; Median = 0.543; E(f(x)) = 0.02; Total.reps = 4300; k.tol = 0; Pred = 0.561Iter: 32; Median = 0.517; E(f(x)) = 0.02; Total.reps = 4560; k.tol = 0; Pred = 0.561Iter: 33; Median = 0.539; E(f(x)) = 0.02; Total.reps = 4830; k.tol = 0; Pred = 0.561Iter: 34; Median = 0.558; E(f(x)) = 0.01; Total.reps = 5110; k.tol = 0; Pred = 0.563Iter: 35; Median = 0.563; E(f(x)) = 0.01; Total.reps = 5400; k.tol = 0; Pred = 0.565Iter: 36; Median = 0.569; E(f(x)) = 0.01; Total.reps = 5700; k.tol = 0; Pred = 0.564Iter: 37; Median = 0.564; E(f(x)) = 0.01; Total.reps = 6010; k.tol = 0; Pred = 0.565Iter: 38; Median = 0.568; E(f(x)) = 0.01; Total.reps = 6330; k.tol = 0; Pred = 0.564Iter: 39; Median = 0.564; E(f(x)) = 0.01; Total.reps = 6660; k.tol = 0; Pred = 0.563Iter: 40; Median = 0.560; E(f(x)) = 0.01; Total.reps = 7000; k.tol = 0; Pred = 0.562Iter: 41; Median = 0.554; E(f(x)) = 0.01; Total.reps = 7350; k.tol = 0; Pred = 0.562Iter: 42; Median = 0.560; E(f(x)) = 0.01; Total.reps = 7710; k.tol = 0; Pred = 0.562Iter: 43; Median = 0.563; E(f(x)) = 0.01; Total.reps = 8080; k.tol = 0; Pred = 0.563Iter: 44; Median = 0.566; E(f(x)) = 0.01; Total.reps = 8460; k.tol = 0; Pred = 0.564Iter: 45; Median = 0.572; E(f(x)) = 0.01; Total.reps = 8850; k.tol = 0; Pred = 0.565Iter: 46; Median = 0.592; E(f(x)) = 0.01; Total.reps = 9250; k.tol = 0; Pred = 0.565Iter: 47; Median = 0.575; E(f(x)) = 0.01; Total.reps = 9660; k.tol = 0; Pred = 0.564Iter: 48; Median = 0.566; E(f(x)) = 0.01; Total.reps = 10080; k.tol = 0; Pred = 0.565Iter: 49; Median = 0.572; E(f(x)) = 0.01; Total.reps = 10510; k.tol = 0; Pred = 0.565Iter: 50; Median = 0.567; E(f(x)) = 0.01; Total.reps = 10950; k.tol = 0; Pred = 0.565Iter: 51; Median = 0.565; E(f(x)) = 0.01; Total.reps = 11400; k.tol = 0; Pred = 0.566Iter: 52; Median = 0.566; E(f(x)) = 0.01; Total.reps = 11860; k.tol = 0; Pred = 0.565Iter: 53; Median = 0.565; E(f(x)) = 0.01; Total.reps = 12330; k.tol = 0; Pred = 0.566Iter: 54; Median = 0.567; E(f(x)) = 0.01; Total.reps = 12810; k.tol = 0; Pred = 0.565Iter: 55; Median = 0.565; E(f(x)) = 0.01; Total.reps = 13300; k.tol = 0; Pred = 0.566Iter: 56; Median = 0.566; E(f(x)) = 0.01; Total.reps = 13800; k.tol = 0; Pred = 0.566Iter: 57; Median = 0.566; E(f(x)) = 0.01; Total.reps = 14300; k.tol = 0; Pred = 0.566Iter: 58; Median = 0.564; E(f(x)) = 0.01; Total.reps = 14800; k.tol = 0; Pred = 0.565Iter: 59; Median = 0.561; E(f(x)) = 0.01; Total.reps = 15300; k.tol = 0; Pred = 0.565Iter: 60; Median = 0.564; E(f(x)) = 0.01; Total.reps = 15800; k.tol = 0; Pred = 0.566Iter: 61; Median = 0.565; E(f(x)) = 0.01; Total.reps = 16300; k.tol = 0; Pred = 0.566Iter: 62; Median = 0.566; E(f(x)) = 0.01; Total.reps = 16800; k.tol = 0; Pred = 0.566Iter: 63; Median = 0.566; E(f(x)) = 0.01; Total.reps = 17300; k.tol = 0; Pred = 0.566Iter: 64; Median = 0.566; E(f(x)) = 0.01; Total.reps = 17800; k.tol = 0; Pred = 0.566Iter: 65; Median = 0.566; E(f(x)) = 0.01; Total.reps = 18300; k.tol = 0; Pred = 0.567Iter: 66; Median = 0.567; E(f(x)) = 0.01; Total.reps = 18800; k.tol = 0; Pred = 0.567Iter: 67; Median = 0.566; E(f(x)) = 0.01; Total.reps = 19300; k.tol = 0; Pred = 0.566Iter: 68; Median = 0.566; E(f(x)) = 0.01; Total.reps = 19800; k.tol = 0; Pred = 0.566Iter: 69; Median = 0.566; E(f(x)) = 0.01; Total.reps = 20300; k.tol = 0; Pred = 0.566Iter: 70; Median = 0.566; E(f(x)) = 0.01; Total.reps = 20800; k.tol = 0; Pred = 0.566Iter: 71; Median = 0.566; E(f(x)) = 0.01; Total.reps = 21300; k.tol = 0; Pred = 0.566Iter: 72; Median = 0.566; E(f(x)) = 0.01; Total.reps = 21800; k.tol = 0; Pred = 0.566Iter: 73; Median = 0.565; E(f(x)) = 0.01; Total.reps = 22300; k.tol = 0; Pred = 0.566Iter: 74; Median = 0.566; E(f(x)) = 0.01; Total.reps = 22800; k.tol = 0; Pred = 0.566Iter: 75; Median = 0.566; E(f(x)) = 0.01; Total.reps = 23300; k.tol = 0; Pred = 0.566Iter: 76; Median = 0.566; E(f(x)) = 0.01; Total.reps = 23800; k.tol = 0; Pred = 0.566Iter: 77; Median = 0.566; E(f(x)) = 0.01; Total.reps = 24300; k.tol = 0; Pred = 0.566Iter: 78; Median = 0.567; E(f(x)) = 0.01; Total.reps = 24800; k.tol = 0; Pred = 0.566Iter: 79; Median = 0.566; E(f(x)) = 0.01; Total.reps = 25300; k.tol = 0; Pred = 0.566Iter: 80; Median = 0.566; E(f(x)) = 0.01; Total.reps = 25800; k.tol = 0; Pred = 0.566Iter: 81; Median = 0.566; E(f(x)) = 0.01; Total.reps = 26300; k.tol = 0; Pred = 0.566Iter: 82; Median = 0.566; E(f(x)) = 0.01; Total.reps = 26800; k.tol = 0; Pred = 0.566Iter: 83; Median = 0.566; E(f(x)) = 0.01; Total.reps = 27300; k.tol = 0; Pred = 0.566Iter: 84; Median = 0.566; E(f(x)) = 0.01; Total.reps = 27800; k.tol = 0; Pred = 0.566Iter: 85; Median = 0.566; E(f(x)) = 0.01; Total.reps = 28300; k.tol = 1; Pred = 0.567Iter: 86; Median = 0.566; E(f(x)) = 0.01; Total.reps = 28800; k.tol = 2; Pred = 0.567
-## 
-## Solution for d: 0.567
-## 95% Prediction Interval: [0.564, 0.571]
-## 
-## #############
-## Design row 3:
-## 
-##    N  d sig.level   b
-## 1 25 NA      0.05 0.8
-## 
-## Iter: 1; Median = 1.050; E(f(x)) = 0.15; Total.reps = 100Iter: 2; Median = 0.891; E(f(x)) = 0.11; Total.reps = 200Iter: 3; Median = 0.759; E(f(x)) = 0.05; Total.reps = 300Iter: 4; Median = 0.869; E(f(x)) = 0.05; Total.reps = 400Iter: 5; Median = 0.778; E(f(x)) = 0.04; Total.reps = 500Iter: 6; Median = 0.854; E(f(x)) = 0.03; Total.reps = 600Iter: 7; Median = 0.968; E(f(x)) = 0.05; Total.reps = 700Iter: 8; Median = 0.865; E(f(x)) = 0.04; Total.reps = 800Iter: 9; Median = 0.804; E(f(x)) = 0.03; Total.reps = 900Iter: 10; Median = 0.857; E(f(x)) = 0.03; Total.reps = 1000Iter: 11; Median = 0.813; E(f(x)) = 0.02; Total.reps = 1100Iter: 12; Median = 0.851; E(f(x)) = 0.02; Total.reps = 1200Iter: 13; Median = 0.819; E(f(x)) = 0.02; Total.reps = 1300Iter: 14; Median = 0.769; E(f(x)) = 0.02; Total.reps = 1400Iter: 15; Median = 0.815; E(f(x)) = 0.02; Total.reps = 1500Iter: 16; Median = 0.780; E(f(x)) = 0.02; Total.reps = 1600Iter: 17; Median = 0.811; E(f(x)) = 0.01; Total.reps = 1710Iter: 18; Median = 0.834; E(f(x)) = 0.01; Total.reps = 1830Iter: 19; Median = 0.861; E(f(x)) = 0.01; Total.reps = 1960Iter: 20; Median = 0.839; E(f(x)) = 0.02; Total.reps = 2100Iter: 21; Median = 0.817; E(f(x)) = 0.01; Total.reps = 2250Iter: 22; Median = 0.836; E(f(x)) = 0.01; Total.reps = 2410Iter: 23; Median = 0.819; E(f(x)) = 0.02; Total.reps = 2580Iter: 24; Median = 0.804; E(f(x)) = 0.01; Total.reps = 2760Iter: 25; Median = 0.817; E(f(x)) = 0.01; Total.reps = 2950Iter: 26; Median = 0.807; E(f(x)) = 0.01; Total.reps = 3150Iter: 27; Median = 0.816; E(f(x)) = 0.01; Total.reps = 3360; k.tol = 0; Pred = 0.807Iter: 28; Median = 0.809; E(f(x)) = 0.01; Total.reps = 3580; k.tol = 0; Pred = 0.807Iter: 29; Median = 0.789; E(f(x)) = 0.01; Total.reps = 3810; k.tol = 0; Pred = 0.806Iter: 30; Median = 0.808; E(f(x)) = 0.01; Total.reps = 4050; k.tol = 0; Pred = 0.804Iter: 31; Median = 0.792; E(f(x)) = 0.01; Total.reps = 4300; k.tol = 0; Pred = 0.803Iter: 32; Median = 0.807; E(f(x)) = 0.01; Total.reps = 4560; k.tol = 0; Pred = 0.805Iter: 33; Median = 0.813; E(f(x)) = 0.01; Total.reps = 4830; k.tol = 0; Pred = 0.806Iter: 34; Median = 0.807; E(f(x)) = 0.01; Total.reps = 5110; k.tol = 0; Pred = 0.806Iter: 35; Median = 0.798; E(f(x)) = 0.01; Total.reps = 5400; k.tol = 0; Pred = 0.806Iter: 36; Median = 0.807; E(f(x)) = 0.01; Total.reps = 5700; k.tol = 0; Pred = 0.805Iter: 37; Median = 0.800; E(f(x)) = 0.01; Total.reps = 6010; k.tol = 0; Pred = 0.806Iter: 38; Median = 0.806; E(f(x)) = 0.01; Total.reps = 6330; k.tol = 0; Pred = 0.805Iter: 39; Median = 0.801; E(f(x)) = 0.01; Total.reps = 6660; k.tol = 0; Pred = 0.806Iter: 40; Median = 0.806; E(f(x)) = 0.01; Total.reps = 7000; k.tol = 0; Pred = 0.807Iter: 41; Median = 0.809; E(f(x)) = 0.01; Total.reps = 7350; k.tol = 0; Pred = 0.806Iter: 42; Median = 0.806; E(f(x)) = 0.01; Total.reps = 7710; k.tol = 0; Pred = 0.806Iter: 43; Median = 0.803; E(f(x)) = 0.01; Total.reps = 8080; k.tol = 0; Pred = 0.805Iter: 44; Median = 0.796; E(f(x)) = 0.01; Total.reps = 8460; k.tol = 0; Pred = 0.806Iter: 45; Median = 0.802; E(f(x)) = 0.01; Total.reps = 8850; k.tol = 0; Pred = 0.805Iter: 46; Median = 0.798; E(f(x)) = 0.01; Total.reps = 9250; k.tol = 0; Pred = 0.805Iter: 47; Median = 0.781; E(f(x)) = 0.01; Total.reps = 9660; k.tol = 0; Pred = 0.805Iter: 48; Median = 0.796; E(f(x)) = 0.01; Total.reps = 10080; k.tol = 0; Pred = 0.804Iter: 49; Median = 0.784; E(f(x)) = 0.01; Total.reps = 10510; k.tol = 0; Pred = 0.804Iter: 50; Median = 0.795; E(f(x)) = 0.01; Total.reps = 10950; k.tol = 0; Pred = 0.804Iter: 51; Median = 0.801; E(f(x)) = 0.01; Total.reps = 11400; k.tol = 0; Pred = 0.803Iter: 52; Median = 0.796; E(f(x)) = 0.01; Total.reps = 11860; k.tol = 0; Pred = 0.804Iter: 53; Median = 0.800; E(f(x)) = 0.01; Total.reps = 12330; k.tol = 0; Pred = 0.804Iter: 54; Median = 0.803; E(f(x)) = 0.01; Total.reps = 12810; k.tol = 0; Pred = 0.805Iter: 55; Median = 0.805; E(f(x)) = 0.01; Total.reps = 13300; k.tol = 0; Pred = 0.804Iter: 56; Median = 0.803; E(f(x)) = 0.01; Total.reps = 13800; k.tol = 0; Pred = 0.805Iter: 57; Median = 0.805; E(f(x)) = 0.01; Total.reps = 14300; k.tol = 0; Pred = 0.805Iter: 58; Median = 0.803; E(f(x)) = 0.01; Total.reps = 14800; k.tol = 0; Pred = 0.805Iter: 59; Median = 0.805; E(f(x)) = 0.01; Total.reps = 15300; k.tol = 0; Pred = 0.805Iter: 60; Median = 0.807; E(f(x)) = 0.01; Total.reps = 15800; k.tol = 0; Pred = 0.806Iter: 61; Median = 0.810; E(f(x)) = 0.01; Total.reps = 16300; k.tol = 0; Pred = 0.806Iter: 62; Median = 0.807; E(f(x)) = 0.00; Total.reps = 16800; k.tol = 0; Pred = 0.806Iter: 63; Median = 0.809; E(f(x)) = 0.00; Total.reps = 17300; k.tol = 0; Pred = 0.807Iter: 64; Median = 0.807; E(f(x)) = 0.01; Total.reps = 17800; k.tol = 0; Pred = 0.806Iter: 65; Median = 0.805; E(f(x)) = 0.01; Total.reps = 18300; k.tol = 0; Pred = 0.805Iter: 66; Median = 0.804; E(f(x)) = 0.01; Total.reps = 18800; k.tol = 0; Pred = 0.805Iter: 67; Median = 0.805; E(f(x)) = 0.01; Total.reps = 19300; k.tol = 0; Pred = 0.805Iter: 68; Median = 0.807; E(f(x)) = 0.01; Total.reps = 19800; k.tol = 0; Pred = 0.805Iter: 69; Median = 0.805; E(f(x)) = 0.01; Total.reps = 20300; k.tol = 0; Pred = 0.805Iter: 70; Median = 0.806; E(f(x)) = 0.00; Total.reps = 20800; k.tol = 0; Pred = 0.806Iter: 71; Median = 0.808; E(f(x)) = 0.00; Total.reps = 21300; k.tol = 0; Pred = 0.806Iter: 72; Median = 0.809; E(f(x)) = 0.00; Total.reps = 21800; k.tol = 0; Pred = 0.806Iter: 73; Median = 0.807; E(f(x)) = 0.00; Total.reps = 22300; k.tol = 0; Pred = 0.806Iter: 74; Median = 0.809; E(f(x)) = 0.00; Total.reps = 22800; k.tol = 0; Pred = 0.807Iter: 75; Median = 0.812; E(f(x)) = 0.00; Total.reps = 23300; k.tol = 0; Pred = 0.807Iter: 76; Median = 0.809; E(f(x)) = 0.00; Total.reps = 23800; k.tol = 0; Pred = 0.806Iter: 77; Median = 0.808; E(f(x)) = 0.00; Total.reps = 24300; k.tol = 0; Pred = 0.807Iter: 78; Median = 0.809; E(f(x)) = 0.00; Total.reps = 24800; k.tol = 0; Pred = 0.808Iter: 79; Median = 0.811; E(f(x)) = 0.00; Total.reps = 25300; k.tol = 0; Pred = 0.808Iter: 80; Median = 0.815; E(f(x)) = 0.00; Total.reps = 25800; k.tol = 0; Pred = 0.809Iter: 81; Median = 0.824; E(f(x)) = 0.00; Total.reps = 26300; k.tol = 0; Pred = 0.809Iter: 82; Median = 0.815; E(f(x)) = 0.00; Total.reps = 26800; k.tol = 0; Pred = 0.809Iter: 83; Median = 0.812; E(f(x)) = 0.00; Total.reps = 27300; k.tol = 0; Pred = 0.809Iter: 84; Median = 0.815; E(f(x)) = 0.00; Total.reps = 27800; k.tol = 0; Pred = 0.809Iter: 85; Median = 0.812; E(f(x)) = 0.00; Total.reps = 28300; k.tol = 0; Pred = 0.808Iter: 86; Median = 0.810; E(f(x)) = 0.00; Total.reps = 28800; k.tol = 0; Pred = 0.808Iter: 87; Median = 0.809; E(f(x)) = 0.00; Total.reps = 29300; k.tol = 0; Pred = 0.808Iter: 88; Median = 0.808; E(f(x)) = 0.00; Total.reps = 29800; k.tol = 0; Pred = 0.808Iter: 89; Median = 0.807; E(f(x)) = 0.00; Total.reps = 30300; k.tol = 0; Pred = 0.809Iter: 90; Median = 0.808; E(f(x)) = 0.00; Total.reps = 30800; k.tol = 0; Pred = 0.809Iter: 91; Median = 0.807; E(f(x)) = 0.00; Total.reps = 31300; k.tol = 0; Pred = 0.809Iter: 92; Median = 0.807; E(f(x)) = 0.00; Total.reps = 31800; k.tol = 0; Pred = 0.809Iter: 93; Median = 0.808; E(f(x)) = 0.00; Total.reps = 32300; k.tol = 0; Pred = 0.809Iter: 94; Median = 0.808; E(f(x)) = 0.00; Total.reps = 32800; k.tol = 1; Pred = 0.809Iter: 95; Median = 0.808; E(f(x)) = 0.00; Total.reps = 33300; k.tol = 2; Pred = 0.809
-## 
-## Solution for d: 0.809
-## 95% Prediction Interval: [0.805, 0.814]
-
solved
+ summarise=Summarise, integer=FALSE, predCI.tol=.01, verbose=FALSE) +solved 
## # A tibble: 3 × 3
 ##       N       d sig.level
 ##   <dbl>   <dbl>     <dbl>
-## 1   100 0.39535      0.05
-## 2    50 0.56696      0.05
-## 3    25 0.80897      0.05
+## 1 100 0.39880 0.05 +## 2 50 0.56325 0.05 +## 3 25 0.80580 0.05 
summary(solved)
## $condition_1
 ## $root
-## [1] 0.3953463
+## [1] 0.3987976
 ## 
 ## $predCI.root
 ##    CI_2.5   CI_97.5 
-## 0.3938603 0.3967689 
+## 0.3970078 0.4006544 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7950923 0.8047359
+## [1] 0.7950401 0.8048781
 ## 
 ## $terminated_early
 ## [1] TRUE
 ## 
 ## $time
-## [1] 45.39s
+## [1] 52.42s
 ## 
 ## $iterations
-## [1] 88
+## [1] 96
 ## 
 ## $total.replications
-## [1] 29800
+## [1] 33800
 ## 
 ## 
 ## $condition_2
 ## $root
-## [1] 0.5669643
+## [1] 0.5632504
 ## 
 ## $predCI.root
 ##    CI_2.5   CI_97.5 
-## 0.5635415 0.5706042 
+## 0.5596615 0.5668974 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.7950938 0.8048253
+## [1] 0.7952681 0.8046467
 ## 
 ## $terminated_early
 ## [1] TRUE
 ## 
 ## $time
-## [1] 44.50s
+## [1] 45.50s
 ## 
 ## $iterations
-## [1] 87
+## [1] 89
 ## 
 ## $total.replications
-## [1] 29300
+## [1] 30300
 ## 
 ## 
 ## $condition_3
 ## $root
-## [1] 0.8089741
+## [1] 0.8057966
 ## 
 ## $predCI.root
 ##    CI_2.5   CI_97.5 
-## 0.8047063 0.8137177 
+## 0.8014145 0.8100785 
 ## 
 ## $b
 ## [1] 0.8
 ## 
 ## $predCI.b
-## [1] 0.795160 0.804754
+## [1] 0.7951135 0.8048062
 ## 
 ## $terminated_early
 ## [1] TRUE
 ## 
 ## $time
-## [1] 51.28s
+## [1] 44.73s
 ## 
 ## $iterations
-## [1] 96
+## [1] 89
 ## 
 ## $total.replications
-## [1] 33800
+## [1] 30300 
plot(solved, 1)
-

+

plot(solved, 2)
-

+

plot(solved, 3)
-

+

Verify with true power from pwr package.

library(pwr)
 pwr.t.test(n=100, power = .8, sig.level = .05)
@@ -992,9 +934,9 @@

Solving effect sizes

## Two-sample t test power calculation ## ## n = 100 -## d = 0.3953463 +## d = 0.3987976 ## sig.level = 0.05 -## power = 0.794455 +## power = 0.8012967 ## alternative = two.sided ## ## NOTE: n is number in *each* group @@ -1003,9 +945,9 @@

Solving effect sizes

## Two-sample t test power calculation ## ## n = 50 -## d = 0.5669643 +## d = 0.5632504 ## sig.level = 0.05 -## power = 0.8014962 +## power = 0.7963325 ## alternative = two.sided ## ## NOTE: n is number in *each* group @@ -1014,15 +956,15 @@

Solving effect sizes

## Two-sample t test power calculation ## ## n = 25 -## d = 0.8089741 +## d = 0.8057966 ## sig.level = 0.05 -## power = 0.8002581 +## power = 0.7971657 ## alternative = two.sided ## ## NOTE: n is number in *each* group -
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+
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