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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Statistical Power Analysis of Dissertations Completed by Students Majoring in Educational Leadership at Tennessee Universities

Deng, Heping 01 May 2000 (has links) (PDF)
The purpose of this study was to estimate the level of statistical power demonstrated in recent dissertations in the field of educational leadership. Power tables provided in Cohen's (1988) Statistical Power Analysis for the Behavioral Sciences were used to determine the power of the statistical tests conducted in dissertations selected from five universities in Tennessee. The meta-analytic approach was used to summarize and synthesize the findings. The population of this study consisted of all dissertations successfully defended by doctoral students majoring in educational leadership/administration at East Tennessee State University, the University of Tennessee at Knoxville, Tennessee State University, the University of Memphis, and Vanderbilt University from January 1, 1996 through December 31, 1998. Dissertations were included if statistical significance testing was used, if the reported tests were referenced in associated power tables from Cohen's (1988) Statistical Power Analysis for the Behavioral Sciences, and if sample sizes were reported in the study. Eighty out of 221 reviewed dissertations were analyzed and statistical power was calculated for each of the 2629 significance tests. The mean statistical power level was calculated for each dissertation. The mean power was .34 to detect small effects, .79 to detect medium effects, and .94 to detect large effects with the dissertation as the unit of analysis. The mean power level across all significance tests was .29 to detect small effects, .75 to detect medium effects, and .93 to detect large effects. These results demonstrated the highest statistical power levels for detecting large and medium effects. The statistical power estimates were quite low when a small effect size was assumed. Researchers had a very low probability of finding true significant differences when looking for small effects. Though the degree of statistical power demonstrated in analyzed dissertations was satisfactory for large and medium effect sizes, neither power level nor Type II error was mentioned in any of the 80 dissertations that were analyzed. Therefore, it is hard to determine whether these dissertations were undertaken with consideration of Type II error or the level of statistical power. The mean sample size used for the 2,629 significance tests was 2.5 times the mean optimal sample size, although most significance tests used samples that were much smaller than optimal sample size. It is recommended that doctoral students in educational leadership receive additional training on the importance of statistical power and the process for estimating appropriate sample size.

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