Evaluating latent class analysis models in qualitative phenotype identification

被引：456

作者：

Yang, CC ^{[1
]}

机构：

[1] Natl Taichung Teachers Coll, Grad Sch Educ Measurement & Stat, Taichung 403, Taiwan

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2006年 / 50卷 / 04期

关键词：

phenotype identifications; latent class analysis; information criteria; model selections; E-M algorithm;

D O I：

10.1016/j.csda.2004.11.004

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The paper is aimed to investigate the performance of information criteria in selecting latent class analysis models which are often used in research of phenotype identification. Six information criteria and a sample size adjustment (Psychometrika 52 (1987) 333) are compared under various sample sizes and model dimensionalities. The simulation design is particularly meaningful for phenotypic research in practice. Results show that improvements by the sample size adjustment are considerable. In addition, the sample size and model dimensionality effects are found to be influential in the simulation study. (c) 2004 Elsevier B.V. All rights reserved.

引用

页码：1090 / 1104

页数：15

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