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decrease default bootstrap to make examples run faster
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benkeser committed May 20, 2021
1 parent 3d3f434 commit 5838419
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2 changes: 1 addition & 1 deletion R/cdf_estimation.R
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Expand Up @@ -136,7 +136,7 @@ drord <- function(
param = c("weighted_mean", "log_odds", "mann_whitney"),
ci = "wald",
alpha = 0.05,
nboot = 1e4,
nboot = 1e3,
return_models = TRUE,
est_dist = TRUE,
stratify = FALSE,
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22 changes: 11 additions & 11 deletions docs/articles/using_drord.html

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2 changes: 1 addition & 1 deletion docs/pkgdown.yml
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Expand Up @@ -3,5 +3,5 @@ pkgdown: 1.6.1
pkgdown_sha: ~
articles:
using_drord: using_drord.html
last_built: 2021-05-20T20:01Z
last_built: 2021-05-20T20:30Z

2 changes: 1 addition & 1 deletion docs/reference/drord.html

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2 changes: 1 addition & 1 deletion man/drord.Rd

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2 changes: 1 addition & 1 deletion vignettes/using_drord.Rmd
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Expand Up @@ -216,7 +216,7 @@ fit3$out_mod$treat1
## Bootstrap confidence intervals
By default, `drord` will used closed-form inference. While this is generally faster, we may instead prefer to use bootstrap confidence intervals, which should provide more robust behavior when working models are misspecified. Bootstrap intervals can be requested via the `ci = "bca"`, with option `nboot` determining the number of bootstrap resamples performed. The bootstrap employed by the package is the bias corrected and accelerated bootstrap [@efron1994introduction]. **In practice, we recommend using many bootstrap samples** (e.g., the package default, `nboot = 1e4`), so that inference is not dependent on the random seed that is set; however, here we illustrate using a small number of bootstrap samples for fast compilation of this vignette. To increase speed, we also turn off estimation of confidence intervals for the CDF and PMF by setting `est_dist = FALSE`.
By default, `drord` will used closed-form inference. While this is generally faster, we may instead prefer to use bootstrap confidence intervals, which should provide more robust behavior when working models are misspecified. Bootstrap intervals can be requested via the `ci = "bca"`, with option `nboot` determining the number of bootstrap resamples performed. The bootstrap employed by the package is the bias corrected and accelerated bootstrap [@efron1994introduction]. **In practice, we recommend using many bootstrap samples** (e.g., `nboot = 1e4`), so that inference is not dependent on the random seed that is set; however, here we illustrate using a small number of bootstrap samples for fast compilation of this vignette. To increase speed, we also turn off estimation of confidence intervals for the CDF and PMF by setting `est_dist = FALSE`.
```{r}
(fit4 <- drord(out = covid19$out, treat = covid19$treat,
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