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Pairwise likelihood estimation and limited-information goodness-of-fit test statistics for binary factor analysis models under complex survey sampling

Author

Listed:
  • Jamil, Haziq
  • Moustaki, Irini
  • Skinner, Chris J.

Abstract

This paper discusses estimation and limited-information goodness-of-fit test statistics in factor models for binary data using pairwise likelihood estimation and sampling weights. The paper extends the applicability of pairwise likelihood estimation for factor models with binary data to accommodate complex sampling designs. Additionally, it introduces two key limited-information test statistics: the Pearson chi-squared test and the Wald test. To enhance computational efficiency, the paper introduces modifications to both test statistics. The performance of the estimation and the proposed test statistics under simple random sampling and unequal probability sampling is evaluated using simulated data.

Suggested Citation

  • Jamil, Haziq & Moustaki, Irini & Skinner, Chris J., 2024. "Pairwise likelihood estimation and limited-information goodness-of-fit test statistics for binary factor analysis models under complex survey sampling," LSE Research Online Documents on Economics 125419, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:125419
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    File URL: http://eprints.lse.ac.uk/125419/
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    More about this item

    Keywords

    composite likelihood; pairwise likelihood; goodness-of-fit tests; complex sampling; factor analysis;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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