Move over ANOVA - Progress in analyzing repeated-measures data and its reflection in papers published in the archives of general psychiatry
Move over ANOVA - Progress in analyzing repeated-measures data and its reflection in papers published in the archives of general psychiatry
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DOI：
10.1001/archpsyc.61.3.310
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发表时间：
2004-03-01
影响因子：
--
通讯作者：
Krystal, JH
中科院分区：
文献类型：
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作者：
Gueorguieva, R;Krystal, JH
背景资料：重复测量数据的分析对研究人员提出了挑战，也是普通精神病学档案中正在讨论的主题。传统的统计分析方法（终点分析以及单变量和多变量重复测量方差分析[分别为rANOVA和rMANOVA]）具有已知的缺点。更复杂的混合效应模型提供了灵活性，最近开发的软件使研究人员可以使用它们。目标：回顾重复测量分析的方法，并讨论混合效应模型的优点和潜在的误用。此外，为了评估从传统到混合效应方法在普通精神病学档案中发表的报告中的转变程度。数据来源：1989年至2001年的普通精神病学档案，以及退伍军人事务部合作研究425。研究选择：重复测量设计的研究，至少2组，以及连续反应变量。数据提取：第一作者根据最先进的统计方法对这些研究进行了排名，顺序如下：混合效应模型、rMANOVA、rANOVA和终点分析。数据综合：在过去10年中，混合效应模型的使用大幅增加。在200 1，30%的临床试验报告的档案中的一般精神病学使用mixed-effects analysis.Conclusions：重复测量方差分析继续被广泛用于重复测量数据的分析，尽管风险的解释。混合效应模型使用所有可用数据，可以正确解释同一受试者重复测量之间的相关性，对时间效应建模具有更大的灵活性，并且可以更适当地处理缺失数据。其灵活性使其成为分析重复测量数据的首选。
Background: The analysis of repeated-measures data presents challenges to investigators and is a topic for ongoing discussion in the Archives of General Psychiatry. Traditional methods of statistical analysis (end-point analysis and univariate and multivariate repeated-measures analysis of variance [rANOVA and rMANOVA, respectively]) have known disadvantages. More sophisticated mixed-effects models provide flexibility, and recently developed software makes them available to researchers.Objectives: To review methods for repeated-measures analysis and discuss advantages and potential misuses of mixed-effects models. Also, to assess the extent of the shift from traditional to mixed-effects approaches in published reports in the Archives of General Psychiatry.Data Sources: The Archives of General Psychiatry from 1989 through 2001, and the Department of Veterans Affairs Cooperative Study 425.Study Selection: Studies with a repeated-measures design, at least 2 groups, and a continuous response variable.Data Extraction: The first author ranked the studies according to the most advanced statistical method used in the following order: mixed-effects model, rMANOVA, rANOVA, and end-point analysis.Data Synthesis: The use of mixed-effects models has substantially increased during the last 10 years. In 200 1, 30% of clinical trials reported in the Archives of General Psychiatry used mixed-effects analysis.Conclusions: Repeated-measures ANOVAs continue to be used widely for the analysis of repeated-measures data, despite risks to interpretation. Mixed-effects models use all available data, can properly account for correlation between repeated measurements on the same subject, have greater flexibility to model time effects, and can handle missing data more appropriately. Their flexibility makes them the preferred choice for the analysis of repeated-measures data.