Sample Size Planning for the Squared Multiple Correlation Coefficient: Accuracy in Parameter Estimation via Narrow Confidence Intervals

Multivariate Behavioral Research
Ken Kelley

Abstract

Methods of sample size planning are developed from the accuracy in parameter approach in the multiple regression context in order to obtain a sufficiently narrow confidence interval for the population squared multiple correlation coefficient when regressors are random. Approximate and exact methods are developed that provide necessary sample size so that the expected width of the confidence interval will be sufficiently narrow. Modifications of these methods are then developed so that necessary sample size will lead to sufficiently narrow confidence intervals with no less than some desired degree of assurance. Computer routines have been developed and are included within the MBESS R package so that the methods discussed in the article can be implemented. The methods and computer routines are demonstrated using an empirical example linking innovation in the health services industry with previous innovation, personality factors, and group climate characteristics.

References

Nov 1, 1989·Psychological Bulletin·C Gatsonis, A R Sampson
Sep 16, 2003·Evaluation & the Health Professions·Ken KelleyJoseph R Rausch
Jan 12, 2005·Behavior Research Methods, Instruments, & Computers : a Journal of the Psychonomic Society, Inc·William P DunlapLeann Myers
Oct 17, 2007·Annual Review of Psychology·Scott E MaxwellJoseph R Rausch
Jan 11, 2008·Behavior Research Methods·Ken Kelley
Jul 1, 1991·Multivariate Behavioral Research·S B Green
Jan 1, 2000·Multivariate Behavioral Research·J Algina, S Olejnik

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Software Mentioned

R2
SAS
MBESS
BEMS
Unix
Windows
MBESS R
R R Development Core Team
Linux
MultipleR2

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