ss.aipe.c: Sample size planning for an ANOVA contrast from the Accuracy in Parameter Estimation (AIPE) perspective

Description

A function to calculate the appropriate sample size per group for the (unstandardized) ANOVA contrast so that the width of the confidence interval is sufficiently narrow.

Usage

ss.aipe.c(error.variance = NULL, c.weights, width, conf.level = 0.95, 
assurance = NULL, certainty = NULL, MSwithin = NULL, SD = NULL, ...)

Value

n: the necessary sample size per group

Arguments

error.variance: the common error variance; i.e., the mean square error
c.weights: the contrast weights
width: the desired full width of the obtained confidence interval
conf.level: the desired confidence interval coverage, (i.e., 1 - Type I error rate)
assurance: parameter to ensure that the obtained confidence interval width is narrower than the desired width with a specified degree of certainty (must be NULL or between zero and unity)
certainty: an alias for assurance
MSwithin: an alias for error.variance
SD: the standard deviation of the common error in ANOVA model
...: allows one to potentially include parameter values for inner functions

Author

Ken Kelley (University of Notre Dame; KKelley@ND.Edu), Keke Lai

References

Kelley, K., Maxwell, S. E., & Rausch, J. R. (2003). Obtaining power or obtaining precesion: Delineating methods of sample size planning. Evaluation and the Health Professions, 26, 258--287.

Maxwell, S. E., & Delaney, H. D. (2004). Designing experiments and analyzing data: A model comparison perspective. Mahwah, NJ: Erlbaum.

Examples

Run this code

# Suppose the population error variance of some three-group ANOVA model
# is believed to be 40. The researcher is interested in the difference 
# between the mean of group 1 and the average of means of group 2 and 3. 
# To plan the sample size so that, with 90 percent certainty, the 
# obtained 95 percent full confidence interval width is no wider than 3:

ss.aipe.c(error.variance=40, c.weights=c(1, -0.5, -0.5), width=3, assurance=.90)

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