A VISUAL APPROACH TO STATISTICAL POWER ANALYSIS ON THE MICROCOMPUTER

被引:10
作者
BORENSTEIN, M
COHEN, J
ROTHSTEIN, HR
POLLACK, S
KANE, JM
机构
[1] BIOSTAT PROGRAMMING ASSOCIATES,TEANECK,NJ
[2] CUNY BERNARD M BARUCH COLL,NEW YORK,NY 10010
[3] ST JOHNS UNIV,JAMAICA,NY 11439
[4] YESHIVA UNIV ALBERT EINSTEIN COLL MED,BRONX,NY 10461
来源
BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS | 1992年 / 24卷 / 04期
关键词
D O I
10.3758/BF03203606
中图分类号
B841 [心理学研究方法];
学科分类号
040201 ;
摘要
Computer programs for statistical power analysis typically require the user to provide a series of values and respond by reporting the corresponding power. These programs provide essentially the same functions as a published text, albeit in a more convenient form. In this paper, we describe a program that instead uses innovative graphic techniques to provide insight into the interaction among the factors that determine power. For example, for t tests, the means and standard deviations of the two distributions, sample sizes, and alpha are displayed as bar graphs. As the researcher modifies these values, the corresponding values of beta (also displayed as a bar graph) and power are updated and displayed immediately. By displaying all of the factors that are instrumental in determining power, the program ensures that each will be addressed By allowing the user to determine the impact that any modifications will have on power, the program encourages an appropriate balance between alpha and beta while working within the constraints imposed by a limited sample size. The program also allows the user to generate tables and graphs to document the impact of the various factors on power. In addition, the program enables the user to run on-screen Monte Carlo simulations to demonstrate the importance of adequate statistical power, and as such, it can serve as a unique educational tool.
引用
收藏
页码:565 / 572
页数:8
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