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Pairwise likelihood approach to grouped continuous model and its extension

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  • de Leon, A.R.

Abstract

A pseudo-likelihood estimation method for the grouped continuous model and its extension to mixed ordinal and continuous data is proposed as an alternative to maximum likelihood estimation. The method, based on the pairwise likelihood approach, advocates simply pooling marginal pairwise likelihoods to approximate the full likelihood. In addition to being consistent and asymptotically normally distributed, maximum pairwise likelihood estimates are computationally simple to obtain. Simulations show that the estimates are quite accurate, yielding minimal bias and small root mean-squared errors. The methodology is illustrated using real-data examples.

Suggested Citation

  • de Leon, A.R., 2005. "Pairwise likelihood approach to grouped continuous model and its extension," Statistics & Probability Letters, Elsevier, vol. 75(1), pages 49-57, November.
    • Handle: RePEc:eee:stapro:v:75:y:2005:i:1:p:49-57
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    3. Katsikatsou, Myrsini & Moustaki, Irini & Md Jamil, Haziq, 2022. "Pairwise likelihood estimation for confirmatory factor analysis models with categorical variables and data that are missing at random," LSE Research Online Documents on Economics 108933, London School of Economics and Political Science, LSE Library.
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