ERIC Number: ED249266
Record Type: RIE
Publication Date: 1984-Apr
Reference Count: 0
Power Differences among Tests of Combined Significance.
Becker, Betsy Jane
Power is an indicator of the ability of a statistical analysis to detect a phenomenon that does in fact exist. The issue of power is crucial for social science research because sample size, effects, and relationships studied tend to be small and the power of a study relates directly to the size of the effect of interest and the sample size. Quantitative synthesis methods can provide ways to overcome the problem of low power by combining the results of many studies. In the study at hand, large-sample (approximate) normal distribution theory for the non-null density of the individual p value is used to obtain power functions for significance value summaries. Three p-value summary methods are examined. Tippett's counting method, Fisher's inverse chi-square summary, and the logit method. Results for pairs of studies and for a set of five studies are reported. They indicate that the choice of a "most-powerful" summary will depend on the number of studies to be summarized, the sizes of the effects in the populations studied, and the sizes of the samples chosen from those populations. (BW)
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: N/A
Authoring Institution: N/A
Note: Paper presented at the Annual Meeting of the American Educational Research Association (68th, New Orleans, LA, April 23-27, 1984).