# Efficient estimation and local identification in latent class analysis

## Author

Listed:
• Richard McHugh

## Abstract

No abstract is available for this item.

## Suggested Citation

• Richard McHugh, 1956. "Efficient estimation and local identification in latent class analysis," Psychometrika, Springer;The Psychometric Society, vol. 21(4), pages 331-347, December.
• Handle: RePEc:spr:psycho:v:21:y:1956:i:4:p:331-347
DOI: 10.1007/BF02296300
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File URL: http://hdl.handle.net/10.1007/BF02296300

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## References listed on IDEAS

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1. T. Anderson, 1954. "On estimation of parameters in latent structure analysis," Psychometrika, Springer;The Psychometric Society, vol. 19(1), pages 1-10, March.
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## Citations

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Cited by:

1. Frank Rijmen & Paul Boeck & Han Maas, 2005. "An IRT Model with a Parameter-Driven Process for Change," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 651-669, December.
2. Perez-Mayo, Jesus, 2003. "Measuring deprivation in Spain," IRISS Working Paper Series 2003-09, IRISS at CEPS/INSTEAD.
3. F. Bartolucci & A. Farcomeni & F. Pennoni, 2014. "Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 433-465, September.
4. Henk Kelderman, 1989. "Item bias detection using loglinear irt," Psychometrika, Springer;The Psychometric Society, vol. 54(4), pages 681-697, September.
5. Anton K. Formann, 2003. "Latent Class Model Diagnosis from a Frequentist Point of View," Biometrics, The International Biometric Society, vol. 59(1), pages 189-196, March.
6. Paul Westers & Henk Kelderman, 1992. "Examining differential item functioning due to item difficulty and alternative attractiveness," Psychometrika, Springer;The Psychometric Society, vol. 57(1), pages 107-118, March.
7. Gongjun Xu & Stephanie Zhang, 2016. "Identifiability of Diagnostic Classification Models," Psychometrika, Springer;The Psychometric Society, vol. 81(3), pages 625-649, September.
8. Francesco Bartolucci & Fulvia Pennoni, 2007. "A Class of Latent Markov Models for Capture–Recapture Data Allowing for Time, Heterogeneity, and Behavior Effects," Biometrics, The International Biometric Society, vol. 63(2), pages 568-578, June.
9. K. Humphreys & D. Titterington, 2003. "Variational approximations for categorical causal modeling with latent variables," Psychometrika, Springer;The Psychometric Society, vol. 68(3), pages 391-412, September.
10. Dereje W. Gudicha & Fetene B. Tekle & Jeroen K. Vermunt, 2016. "Power and Sample Size Computation for Wald Tests in Latent Class Models," Journal of Classification, Springer;The Classification Society, vol. 33(1), pages 30-51, April.
11. A. Felipe & P. Miranda & L. Pardo, 2015. "Minimum $$\phi$$ ϕ -Divergence Estimation in Constrained Latent Class Models for Binary Data," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 1020-1042, December.
12. Guan-Hua Huang & Karen Bandeen-Roche, 2004. "Building an identifiable latent class model with covariate effects on underlying and measured variables," Psychometrika, Springer;The Psychometric Society, vol. 69(1), pages 5-32, March.
13. Anton Formann & Ivo Ponocny, 2002. "Latent change classes in dichotomous data," Psychometrika, Springer;The Psychometric Society, vol. 67(3), pages 437-457, September.
14. Robert Mislevy & Mark Wilson, 1996. "Marginal maximum likelihood estimation for a psychometric model of discontinuous development," Psychometrika, Springer;The Psychometric Society, vol. 61(1), pages 41-71, March.

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