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Unraveling the mystique of power analysis
Abstract:
Power analysis provides one method for assessing the efficacy of alternative research designs. The purpose of this article is to simplify the methods for calculating power analysis to determine an adequate sample size. Although attention to type I errors (alpha error) is prevalent among nurse researchers, there is less appreciation for research problems resulting from a type II error. Without the a priori examination of the power of the test of significance, there is no assurance that the sample is sufficient to discern significant differences. Formulas for calculating effect size are provided for t tests, correlations, chi-square, analysis of variance, and regression. Examples of calculating the effect size by using four different statistical tests based on research studies are presented: t tests with unequal variance between groups, chi-square, an analysis of variance, and regression. Power analysis is an additional procedure to ensure that the sample size is adequate for the research project about to be undertaken.
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