p Beyond t test and ANOVA: applications of mixed-effects models for more rigorous statistical analysis in neuroscience research

Yu Zhaoxia; Guindani Michele; Grieco Steven F.Chen LujiaHolmes Todd C.Xu Xiangmin

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p Beyond t test and ANOVA: applications of mixed-effects models for more rigorous statistical analysis in neuroscience research

机译：p Beyond t test and ANOVA: applications of mixed-effects models for more rigorous statistical analysis in neuroscience research

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In basic neuroscience research, data are often clustered or collected with repeated measures, hence correlated. The most widely used methods such as t test and ANOVA do not take data dependence into account and thus are often misused. This Primer introduces linear and generalized mixed-effects models that consider data dependence and provides clear instruction on how to recognize when they are needed and how to apply them. The appropriate use of mixed-effects models will help researchers improve their experimental design and will lead to data analyses with greater validity and higher reproducibility of the experimental findings.

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来源
《Neuron》 |2022年第1期|21-35|共15页
作者
Yu Zhaoxia; Guindani Michele; Grieco Steven F.Chen LujiaHolmes Todd C.Xu Xiangmin;
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作者单位

Donald Bren Sch Informat & Comp Sci,Univ Calif Irvine;

Sch Med,Univ Calif Irvine;

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原文格式 PDF
正文语种英语
中图分类神经病学;
关键词
LONGITUDINAL DATA-ANALYSIS; GENERALIZED LINEAR-MODELS; RANK-SUM TEST; CLUSTERED DATA; R PACKAGE; BIOMEDICAL-RESEARCH; MULTILEVEL MODELS; INFERENCE; SUBJECT; ERROR;

p Beyond t test and ANOVA: applications of mixed-effects models for more rigorous statistical analysis in neuroscience research

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