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分析认知测试数据:分布与非参数随机效应。

Analysing cognitive test data: Distributions and non-parametric random effects.

作者信息

Muniz-Terrera Graciela, Hout Ardo van den, Rigby R A, Stasinopoulos D M

机构信息

MRC Unit for Lifelong Health and Aging, London, UK

Department of Statistical Science, University College London, UK.

出版信息

Stat Methods Med Res. 2016 Apr;25(2):741-53. doi: 10.1177/0962280212465500. Epub 2012 Nov 6.

Abstract

An important assumption in many linear mixed models is that the conditional distribution of the response variable is normal. This assumption is violated when the models are fitted to an outcome variable that counts the number of correctly answered questions in a questionnaire. Examples include investigations of cognitive decline where models are fitted to Mini Mental State Examination scores, the most widely used test to measure global cognition. Mini Mental State Examination scores take integer values in the 0-30 range, and its distribution has strong ceiling and floor effects. This article explores alternative distributions for the outcome variable in mixed models fitted to mini mental state examination scores from a longitudinal study of ageing. Model fit improved when a beta-binomial distribution was chosen as the distribution for the response variable.

摘要

许多线性混合模型中的一个重要假设是响应变量的条件分布呈正态分布。当这些模型应用于对问卷中正确回答问题的数量进行计数的结果变量时,这一假设就会被违反。例如在认知衰退研究中,模型应用于简易精神状态检查表(Mini Mental State Examination,MMSE)得分,这是测量整体认知最广泛使用的测试。MMSE得分在0至30分的范围内取整数值,其分布具有很强的天花板效应和地板效应。本文从一项老龄化纵向研究中,探索了应用于MMSE得分的混合模型中结果变量的替代分布。当选择β-二项分布作为响应变量的分布时,模型拟合得到了改善。

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