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

Haziq Jamil, Irini Moustaki and Chris J. Skinner

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

Keywords: composite likelihood; pairwise likelihood; goodness-of-fit tests; complex sampling; factor analysis (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2025-02-28
New Economics Papers: this item is included in nep-ecm
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Published in British Journal of Mathematical and Statistical Psychology, 28, February, 2025, 78(1), pp. 258 - 285. ISSN: 0007-1102

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