A Monte Carlo Comparison Study of the Power of the Analysis of Covariance, Simple Difference, and Residual Change Scores in Testing Two-Wave Data.
作者信息
Kisbu-Sakarya Yasemin, MacKinnon David P, Aiken Leona S
机构信息
Arizona State University.
出版信息
Educ Psychol Meas. 2013 Feb;73(1):47-62. doi: 10.1177/0013164412450574.
Abstract
摘要
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本文引用的文献
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A Simulation Study on the Performance of the Simple Difference and Covariance-Adjusted Scores in Randomized Experimental Designs.随机实验设计中简单差值分数和协方差调整分数性能的模拟研究
J Educ Meas. 2011 Spring;48(1):31-43. doi: 10.1111/j.1745-3984.2010.00129.x.
2
"Residual change" analysis is not equivalent to analysis of covariance.“残差变化”分析并不等同于协方差分析。
J Clin Epidemiol. 2005 May;58(5):540-1; author reply 542. doi: 10.1016/j.jclinepi.2004.12.002.
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Statistical power for nonequivalent pretest-posttest designs. The impact of change-score versus ANCOVA models.非等组前测后测设计的统计功效。变化分数模型与协方差分析模型的影响。
Eval Rev. 2001 Feb;25(1):3-28. doi: 10.1177/0193841X0102500101.
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Dealing with baseline differences: two principles and two dilemmas.应对基线差异：两项原则与两个困境。
Int J Psychophysiol. 1999 Jan;31(2):155-61. doi: 10.1016/s0167-8760(98)00048-8.
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