Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Latent variable models for categorical data
AU - Lancaster, Gillian
AU - Green, Michael
PY - 2002
Y1 - 2002
N2 - 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 todetermine their effectiveness.
AB - 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 todetermine their effectiveness.
KW - latent variable
KW - item-response analysis
KW - linear score model
KW - empirical Bayes estimate
KW - linear score
KW - log-bilinear model
U2 - 10.1023/A:1014886619553
DO - 10.1023/A:1014886619553
M3 - Journal article
VL - 12
SP - 153
EP - 161
JO - Statistics and Computing
JF - Statistics and Computing
SN - 0960-3174
IS - 2
ER -