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精神医学中的生物统计学(16) 把握度分析在横断面研究和纵向研究设计中的应用(英文) 被引量:1

Biostatistics in psychiatry (16) Power analysis for cross-sectional and longitudinal study designs
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摘要 1.Introduction Power and sample size estimation constitutes an important component of designing and planning modern scientific studies.It provides information for assessing the feasibility of a study to detect treatment effects and for estimating the resources needed to conduct the project.This tutorial discusses the basic concepts of power analysis and the major differences between hypothesis testing and power analyses.We also 1. Introduction Power and sample size estimation constitutes an impor- tant component of designing and planning modern scientific studies. It provides information for assessing the feasibility of a study to detect treatment effects and for estimating the resources needed to conduct the project. This tutorial discusses the basic concepts of power analysis and the major differences between hypothesis testing and power analyses. We also discuss the advantages of longitudinal studies compared to cross-sectional studies and the statistical issues involved when designing such studies. These points are illustrated with a series of examples.
出处 《上海精神医学》 2013年第4期259-262,共4页 Shanghai Archives of Psychiatry
基金 supported in part by the Clinical and Translational Science Collaborative of Cleveland,UL1TR000439 the University of Rochester,5-27607,from the National Institutes of Health
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  • 1Jennrich RI, Schluchter MD. Unbalanced repeated-measures models with structured covariance matrices. Biometrics 1986; 42: 805-820.
  • 2R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing: Vienna, Austria, 2012. ISBN 3-900051-07-0, URL http://www. R-project.org/' R Package 'pwr'http://cran.r-project.org/ web/packages/pwr/index.html.
  • 3Castelloe JM. Sample Size Computations and Power Analysis with the SAS System. Proceedings of the Twenty-Fifth Annual SAS Users Group International Conference; [April 9-12, 2000]; Indianapolis, Indiana, USA; Cary, N~: SAS Institute Inc.; 265-25.
  • 4Hintze J. PASS 11. NCSS, LLC. Kaysville, Utah, USA, 2011.

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