pwrss - Statistical Power and Sample Size Calculation Tools
Statistical power and minimum required sample size
calculations for (1) testing a proportion (one-sample) against
a constant, (2) testing a mean (one-sample) against a constant,
(3) testing difference between two proportions (independent
samples), (4) testing difference between two means or groups
(parametric and non-parametric tests for independent and paired
samples), (5) testing a correlation (one-sample) against a
constant, (6) testing difference between two correlations
(independent samples), (7) testing a single coefficient in
multiple linear regression, logistic regression, and Poisson
regression (with standardized or unstandardized coefficients,
with no covariates or covariate adjusted), (8) testing an
indirect effect (with standardized or unstandardized
coefficients, with no covariates or covariate adjusted) in the
mediation analysis (Sobel, Joint, and Monte Carlo tests), (9)
testing an R-squared against zero in linear regression, (10)
testing an R-squared difference against zero in hierarchical
regression, (11) testing an eta-squared or f-squared (for main
and interaction effects) against zero in analysis of variance
(could be one-way, two-way, and three-way), (12) testing an
eta-squared or f-squared (for main and interaction effects)
against zero in analysis of covariance (could be one-way,
two-way, and three-way), (13) testing an eta-squared or
f-squared (for between, within, and interaction effects)
against zero in one-way repeated measures analysis of variance
(with non-sphericity correction and repeated measures
correlation), and (14) testing goodness-of-fit or independence
for contingency tables. Alternative hypothesis can be
formulated as "not equal", "less", "greater", "non-inferior",
"superior", or "equivalent" in (1), (2), (3), and (4); as "not
equal", "less", or "greater" in (5), (6), (7) and (8); but
always as "greater" in (9), (10), (11), (12), (13), and (14).
Reference: Bulus and Polat (2023) <https://osf.io/ua5fc>.
