Sample size calculation with R based on the book
[1] M.Kieser: Fallzahlberechnung in der medizinischen Forschung [2018], 1th Edition.
There are the following functions for sample size calculation:
- n_ancova,
- n_chisq,
- n_chisq_mult_groups,
- n_ftest,
- n_ttest,
- n_ztest,
and for power calculation
- power_binomial,
- power_chisq_mult_groups,
- power_ftest,
- power_ttest,
- power_ztest.
Sample Size Calculation for the Analysis of Covariances (ANCOVA) for test on mean difference for two samples correlated to a covariate. See pages 18 - 20 in [1] for further details.
Sample size Calculation for the Chi-Square Test for two independent samples with binary data using the absolute rate difference quantifying the effect of an intervention. See pages 21 - 26 in [1] for further details.
Sample size calculation for the Chi-Square test comparing rates of \eqn{k > 2} independent samples. See page 30 in [1] for further details.
Sample size calculation for the f-Test comparing means of \eqn{k > 2} independent samples. See page 29 in [1] for further details.
Sample size calculation for the t-Test comparing two independent samples. See pages 16 - 18 in [1] for further details.
Sample size calculation for the z-Test comparing two independent samples. See pages 13 - 16 in [1] for further details.
Power Calculation for the Chi-Square Test for two independent samples with binary data using the absolute rate difference quantifying the effect of an intervention. See pages 21 - 26 in [1] for further details.
Power calculation for the Chi-Square test comparing rates of \eqn{k > 2} independent samples. See page 30 in [1] for further details.
Power calculation for the f-Test comparing means of \eqn{k > 2} independent samples. See page 29 in [1] for further details.
Power calculation for the t-Test comparing two independent samples. See pages 16 - 18 in [1] for further details.
###power_ztest Power calculation for the z-Test comparing two independent samples. See pages 13 - 16 in [1] for further details.