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Model Selection Information Criteria for Non-Nested Latent Class Models

Author

Listed:
  • Ting Hsiang Lin
  • C. Mitchell Dayton

Abstract

Latent class models have been developed for assessment of hierarchic relations in scaling and behavioral analysis. This article investigated the use of three model selection information criteria—Akaike AIC, Schwarz SIC, and Bozdogan CAIC—for non-nested models. In general, SIC and CAIC were superior to AIC for relatively simple models, whereas AIC was superior for more complex models, although accuracy was often quite low for such models. In addition, some effects were detected for error rates in the models.

Suggested Citation

  • Ting Hsiang Lin & C. Mitchell Dayton, 1997. "Model Selection Information Criteria for Non-Nested Latent Class Models," Journal of Educational and Behavioral Statistics, , vol. 22(3), pages 249-264, September.
    • Handle: RePEc:sae:jedbes:v:22:y:1997:i:3:p:249-264
    DOI: 10.3102/10769986022003249
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    Cited by:

    1. Henry de-Graft Acquah, 2013. "The Role of Model Complexity and the Performance of the Selection Criteria in Asymmetric Price Transmission Models," Journal of Economics and Behavioral Studies, AMH International, vol. 5(3), pages 157-163.
    2. Katayama, Hajime & Meagher, Kieron J. & Wait, Andrew, 2018. "Authority and communication in firms," Journal of Economic Behavior & Organization, Elsevier, vol. 155(C), pages 315-348.
    3. Kumar, Sunil & Husain, Zakir & Mukherjee, Diganta, 2017. "Assessing consistency of consumer confidence data using latent class analysis with time factor," Economic Analysis and Policy, Elsevier, vol. 55(C), pages 35-46.
    4. Wang, Rui & Saboo, Alok R. & Grewal, Rajdeep, 2015. "A managerial capital perspective on chief marketing officer succession," International Journal of Research in Marketing, Elsevier, vol. 32(2), pages 164-178.

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