Wirtz P W, Carbonari J P, Muenz L R, Stout R L, Tonigan J S, Connors G J
Department of Management Science, George Washington University, Washington, D.C. 20052.
J Stud Alcohol Suppl. 1994 Dec;12:76-82. doi: 10.15288/jsas.1994.s12.76.
This article presents a classical approach for analyzing repeated measures designs with specific application to treatment matching studies. The generic treatment matching hypothesis is formulated under the multivariate general linear model, transforming the dependent variables to account for the repeated measures structure of the data. Issues of primary importance in the use of this approach (such as correcting for inflated Type I error and robustness of statistical tests to parametric assumptions) are discussed. The article concludes with an assessment of the strengths and weaknesses of this approach compared with alternative approaches.
本文介绍了一种用于分析重复测量设计的经典方法，并特别应用于治疗匹配研究。一般的治疗匹配假设是在多元一般线性模型下制定的，对因变量进行变换以考虑数据的重复测量结构。讨论了使用该方法时的一些首要问题（如校正膨胀的I型错误以及统计检验对参数假设的稳健性）。文章最后评估了该方法与其他替代方法相比的优缺点。
