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A general 3-step maximum likelihood approach to estimate the effects of multiple latent categorical variables on a distal outcome

Zhu, Yajing, Steele, Fiona and Moustaki, Irini (2017) A general 3-step maximum likelihood approach to estimate the effects of multiple latent categorical variables on a distal outcome. Structural Equation Modeling, 24 (5). pp. 643-656. ISSN 1070-5511

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Identification Number: 10.1080/10705511.2017.1324310

Abstract

The 3-step approach has been recently advocated over the simultaneous 1-step approach to model a distal outcome predicted by a latent categorical variable. We generalize the 3-step approach to situations where the distal outcome is predicted by multiple and possibly associated latent categorical variables. Although the simultaneous 1-step approach has been criticized, simulation studies have found that the performance of the two approaches is similar in most situations (Bakk & Vermunt, 2016). This is consistent with our findings for a 2-LV extension when all model assumptions are satisfied. Results also indicate that under various degrees of violation of the normality and conditional independence assumption for the distal outcome and indicators, both approaches are subject to bias but the 3-step approach is less sensitive. The differences in estimates using the two approaches are illustrated in an analysis of the effects of various childhood socioeconomic circumstances on body mass index at age 50.

Item Type: Article
Official URL: http://www.tandfonline.com/toc/hsem20/
Additional Information: © 2017 Taylor & Francis Group, LLC
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
Sets: Departments > Statistics
Date Deposited: 21 Jun 2017 09:06
Last Modified: 20 Sep 2019 02:27
URI: http://eprints.lse.ac.uk/id/eprint/81850

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