ss.aipe.c {MBESS} | R Documentation |
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, ...)
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 |
MSwithin |
an alias for |
SD |
the standard deviation of the common error in ANOVA model |
... |
allows one to potentially include parameter values for inner functions |
Value
n |
the necessary sample size per group |
Note
Be sure to use the error varaince and not its square root (i.e., the standard deviation of the errors).
Author(s)
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.
See Also
ss.aipe.sc
, ss.aipe.c.ancova
, ci.c
Examples
# 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)