Power and Precision, Version 2
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Power and Precision, Version 2

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作者: Michael T·Borenstein  |  Hanna Rothstein  |  Jacob Cohen
出版年: 2001-7
定价: $ 113.00
ISBN: 9780805863260



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内容简介:

"Power and Precision" is a stand-alone program that is used to find the sample size for a planned study. This program features an unusually clear interface and many tools to assist the user in developing an understanding of power analysis. Incorporating the ability to create tables, graphs, and reports with a single click, it includes a number of features that are helpful for teaching power analysis, as well as others that allow the researcher to explain and justify the selection of a sample size for grant applications. Easy to use, the program includes an interactive guide that walks the user through every step required for the analysis, and it creates detailed reports of the results. The program allows the user to select from a variety of computational options, including exact computations for virtually all procedures. It features the ability to take account of precision (the confidence interval width), as well as statistical power. Tables and graphs provide an immediate picture that can be used to explore all available options for increasing power. The program includes modules for means, proportions, correlations, analysis of variance/covariance, and multiple regression. Version 2 adds modules for survival analysis, logistic regression, and equivalence testing. The program comes with a 220-page manual that includes a comprehensive introduction to power analysis, as well as worked examples and algorithms for all procedures. Key Features: *Work interactively--modify any element of the effect size, the sample size, or alpha, and immediately see the impact on power. *Create reports--create a detailed report with a single click; copy and paste this report into the study proposal or grant application. *Create tables and graphs--create tables and graphs to study the impact of each factor and include them in the proposal or grant application to justify the sample size.

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