PowerUpR (version 0.1.3)

power.ira1r1: Model 1.0: Statistical Power Calculator for Individual Random Assignment Designs, Completely Randomized Controlled Trials

Description

power.ira1r1 calculates statistical power for completely randomized controlled trials where individuals are randomly assigned to treatment and control groups.

Usage

power.ira1r1(mdes=.25, alpha=.05, two.tail=TRUE,
               P=.50, g1=0, R12=0,
               n, ...)

Arguments

mdes

minimum detectable effect size.

alpha

probability of type I error.

two.tail

logical; TRUE for two-tailed hypothesis testing, FALSE for one-tailed hypothesis testing.

P

proportion of units randomly assigned to treatment.

g1

number of covariates.

R12

proportion of variance in the outcome explained by covariates.

n

sample size.

...

to handle extra parameters passed from other functions, do not define any additional parameters.

Value

fun

function name.

par

list of parameters used in power calculation.

df

degrees of freedom

M

multiplier for MDES calcuation given degrees of freedom, \(\alpha\) and \(\beta\) (1-power).

power

statistical power (1 - type II error).

Details

Power formula was derived within power analysis framework descibed by Hedges & Rhoads (2009). Further definition of design parameters can be found in Dong & Maynard (2013).

References

Dong, N., & Maynard, R. A. (2013). PowerUp!: A Tool for Calculating Minum Detectable Effect Sizes and Minimum Required Sample Sizes for Experimental and Quasi-Experimental Design Studies,Journal of Research on Educational Effectiveness, 6(1), 24-6. Hedges, L. & Rhoads, C.(2009). Statistical Power Analysis in Education Research (NCSER 2010-3006). Washington, DC: National Center for Special Education Research, Institute of Education Sciences, U.S. Department of Education. This report is available on the IES website at http://ies.ed.gov/ncser/.

See Also

mdes.ira1r1, mrss.ira1r1, optimal.ira1r1

Examples

## Not run: ------------------------------------
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#    power.ira1r1(n=55)
# 
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