Latent variable techniques for categorical data

被引:1
|
作者
Lancaster, G
Green, M
机构
[1] Univ Liverpool, Div Stat & OR, Med Stat Unit, Liverpool L69 3BX, Merseyside, England
[2] Univ Lancaster, Ctr Appl Stat, Lancaster LA1 4YW, England
基金
英国经济与社会研究理事会;
关键词
latent variable; item-response analysis; linear score model; empirical Bayes estimate; linear score; log-bilinear model;
D O I
10.1023/A:1014886619553
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Two useful statistical methods for generating a latent variable are described and extended to incorporate polytomous data and additional covariates. Item response analysis is not well-known outside its area of application, mainly because the procedures to fit the models are computer intensive and not routinely available within general statistical software packages. The linear score technique is less computer intensive, straightforward to implement and has been proposed as a good approximation to item response analysis. Both methods have been implemented in the standard statistical software package GLIM 4.0, and are compared to determine their effectiveness.
引用
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页码:153 / 161
页数:9
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