Power and Reliability for Correlation and ANOVA.

Unfortunately, researchers do not usually have measurement instruments that provide perfectly reliable scores. Therefore, the researcher may want to account for the level of unreliability by appropriately increasing the sample size. For example, the results of a pilot study may indicate that a particular instrument is not as reliable with a given population as it has been with other populations. A series of Monte Carlo analyses were conducted to determine the sample sizes required when measurements are not perfectly reliable. The methods investigated were: (1) Pearson correlation; (2) Spearman rank correlation; and (3) analysis of variance (ANOVA). Using this information, a researcher can use the tables provided to determine an appropriate sample size for their study. Tables are also provided to illustrate the reduction in power from decreased reliability for given sample sizes. The computer program will be made available through the World Wide Web to help researchers determine the actual statistical power they can expect for their studies with less than perfect reliability. (Contains 1 figure, 6 tables, 6 charts, and 27 references.) (Author/SLD)