Statistical Inference of Clustered Data Factor Model Based on Principal Component Method
Clustered data is widely used in neuroscience and social investigation and has at-tracted much attention from statisticians.Classical factor analysis methods are often used to characterize the association between covariables in non-clustered data.However,the correla-tion between many observed individuals or variables in clustered data is not fully considered under the framework of factor model.In this paper,factor analysis model is established for clustered data,and statistical inference is made by principal component analysis method.The effectiveness of the method is demonstrated by random simulation.The case analysis compares the clustered data with internal relation and without internal relation.The result shows that considering internal relation of clustered data is better.
clustered datafactor analysis modelprincipal component analysiscompara-tive study
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NSTL
万方数据
