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Analysis of multi-level correlated data in the framework of generalized estimating equations via xtmultcorr procedures in Stata and qls functions in Matlab

机译:通过Stata中的xtmultcorr过程和Matlab中的qls函数在广义估计方程框架中分析多级相关数据

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Many medical studies yield data with multiple sources of correlation. For example, in a study of repeated measurements collected on each eye of spouses, three sources of correlation may be present, due to the fact that measurements within the same family will be more similar if they are measured on the same eye (left versus right), within the same person (husband versus wife), or at the same measurement occasion. This article reviews an algorithm for analysis of data with two or more sources of correlation (Shults, Whitt, Kumanyika, 2004) that can be implemented using quasi-least squares, an approach in the framework of generalized estimating equations. It then describes and demonstrates implementation of this algorithm with xtmultcorr procedures in Stata and the qls functions in Matlab. The Stata and Matlab procedures are available on the website for the Longitudinal Analysis for Diverse Populations project: http://www.cceb.upenn.edu/~sratclif/QLSproject.html.
机译:许多医学研究产生的数据具有多种相关性。例如,在对配偶的每只眼睛上进行的重复测量的研究中,可能存在三个相关来源,因为如果在同一只眼睛上进行测量,则同一家庭内的测量将更加相似(左与右) ),在同一个人(丈夫还是妻子)中或在相同的测量场合。本文介绍了一种用于分析具有两个或多个相关源的数据的算法(Shults,Whitt,Kumanyika,2004年),该算法可以使用拟最小二乘法实现,这是广义估计方程框架中的一种方法。然后用Stata中的xtmultcorr过程和Matlab中的qls函数描述并演示了该算法的实现。可在网站上获得Stata和Matlab程序,以进行多元总体纵向分析项目:http://www.cceb.upenn.edu/~sratclif/QLSproject.html。

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