Latent class model diagnostics - a review and some proposals

This contribution has two purposes. First, to review established methods for latent class model diagnostics and, second, to present and discuss less well-known methods. To the first group belong: (a) overall goodness-of-fit tests using, for large samples, the asymptotic chi-square approximation (Pearson, likelihood ratio, Read-Cressie power divergence statistic) and, for sparse data, resampling techniques such as parametric bootstrap; (b) residual analysis of the pattern frequencies for which also bootstrapping their reference distributions in the presence of smaller samples is recommended. Less well-known are (a) a chi-square goodness-of-fit test not being based on the full information provided by the pattern frequencies but rather using partial information available from lower-order marginals of the contingency table formed by the items, (b) a simple test for the odds ratios of pairs of items, (c) the Rudas-Clogg-Lindsay index of lack of fit of which (d) a new variant is considered, too. The methods are applied to both generated and empirical data to demonstrate their usefulness in latent class model diagnosis.

[1]  C. R. Rao,et al.  Linear Statistical Inference and its Applications , 1968 .

[2]  P. Holland,et al.  Discrete Multivariate Analysis. , 1976 .

[3]  Calyampudi R. Rao,et al.  Linear Statistical Inference and Its Applications. , 1975 .

[4]  W. G. Cochran Some Methods for Strengthening the Common χ 2 Tests , 1954 .

[5]  P L Fidler,et al.  Goodness-of-Fit Testing for Latent Class Models. , 1993, Multivariate behavioral research.

[6]  S. Haberman The Analysis of Residuals in Cross-Classified Tables , 1973 .

[7]  K. Pearson On the Criterion that a Given System of Deviations from the Probable in the Case of a Correlated System of Variables is Such that it Can be Reasonably Supposed to have Arisen from Random Sampling , 1900 .

[8]  S. Zeger,et al.  Latent Class Model Diagnosis , 2000, Biometrics.

[9]  J. Tukey,et al.  Transformations Related to the Angular and the Square Root , 1950 .

[10]  Lilian M. de Menezes On fitting latent class models for binary data: The estimation of standard errors , 1999 .

[11]  Anton K. Formann,et al.  Linear Logistic Latent Class Analysis , 1982 .

[12]  Clifford C. Clogg,et al.  Some latent structure models for the analysis of likert-type data , 1979 .

[13]  Erling B. Andersen,et al.  The Statistical Analysis of Categorical Data , 1990 .

[14]  B. Efron,et al.  The Jackknife: The Bootstrap and Other Resampling Plans. , 1983 .

[15]  S. S. Wilks The Large-Sample Distribution of the Likelihood Ratio for Testing Composite Hypotheses , 1938 .

[16]  Jeroen K. Vermunt,et al.  'EM: A general program for the analysis of categorical data 1 , 1997 .

[17]  Mark Reiser,et al.  Analysis of residuals for the multionmial item response model , 1996 .

[18]  M. Reiser,et al.  3. A Goodness-of-Fit Test for the Latent Class Model When Expected Frequencies are Small , 1999 .

[19]  A. Formann Linear Logistic Latent Class Analysis for Polytomous Data , 1992 .

[20]  B. Lindsay,et al.  A New Index of Fit Based on Mixture Methods for the Analysis of Contingency Tables , 1994 .

[21]  Scott M. Smith,et al.  Computer Intensive Methods for Testing Hypotheses: An Introduction , 1989 .