Why Can Methods for Comparing Means Have Relatively Low Power, and What Can You Do to Correct the Problem?

J. Cohen, Statistical Power Analysis for the Behavioral Sciences, 2nd ed. (Erlbaum, Hillsdale, NJ, 1988). This is the source of the system of power analysis described here; the power values and sam ple sizes of the illustrations derive from this book's tables. 2. J. Neyman and E.S. Pearson, On the use and interpretation of certain test criteria for purposes of statistical inference, Biometrika, 20A, 175-240, 263-294 (1928); J. Neyman and E.S. Pearson, On the problem of the most efficient tests of statistical hypotheses, Transactions of the Royal Society of London Series A, 231, 289-337 (1933). 3. J. Cohen, Things I have learned (so far), American Psychologist, 45, 1304-1312 (1990). 4. For an article-length treatment of sample size determination using the .80 convention and a = .01, .05, and .10, see J. Cohen, A power primer, Psychological Bulletin (in press). A useful alternative treatment is offered in H.C. Kraemer and S. Thie mann, How Many Subjects? Statistical Power Anal ysis in Research (Sage, Newbury Park, CA, 1987). 5. J. Cohen, The statistical power of abnormal social psychological research: A review, Journal of Abnormal and Social Psychology, 65, 145-153 (1962). 6. P. Sedlmeier and G. Gigerenzer, Do studies of statistical power have an effect on the power of studies? Psychological Bulletin, 105, 309-316 (1989).