tTestPwr

numeric, degrees of freedom of the t-distribution

numeric, significance level, defaults to 0.05

sig.level

Compute Power of a Wald Test
computes the power of a scaled Wald test given a standard error,
an effect size, the degrees of freedom of the t-distribution and
a significance level.
Computes the exact power, see second example

Tools for power and sample size
calculation as well as design diagnostics for
longitudinal mixed model settings, with a focus on stepped wedge designs.
All calculations are oracle estimates i.e. assume random effect variances
to be known (or guessed) in advance.
The method is introduced in Hussey and Hughes (2007) <doi:10.1016/j.cct.2006.05.007>,
extensions are discussed in Li et al. (2020) <doi:10.1177/0962280220932962>.

Philipp Mildenberger

SteppedPower

Power Calculation for Stepped Wedge Designs

Federico Marini

tTestPwr function

Compute Power of a Wald Test

computes the power of a scaled Wald test given a standard error,
an effect size, the degrees of freedom of the t-distribution and
a significance level.
Computes the exact power, see second example — tTestPwr

Compute Power of a Wald Test

computes the power of a scaled Wald test given a standard error,
an effect size, the degrees of freedom of the t-distribution and
a significance level.
Computes the exact power, see second example

Compute Power of a Wald Testcomputes the power of a scaled Wald test given a standard error,
an effect size, the degrees of freedom of the t-distribution and
a significance level.
Computes the exact power, see second example

tTestPwr: Compute Power of a Wald Test
computes the power of a scaled Wald test given a standard error, an effect size, the degrees of freedom of the t-distribution and a significance level. Computes the exact power, see second example

Description

Usage

Arguments

Value

Examples