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Modeling within-household associations in household panel studies

Steele, Fiona, Clarke, Paul and Kuha, Jouni (2019) Modeling within-household associations in household panel studies. Annals of Applied Statistics, 13 (1). pp. 367-392. ISSN 1932-6157

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Identification Number: 10.1214/18-AOAS1189

Abstract

Household panel data provide valuable information about the extent of similarity in coresidents' attitudes and behaviours. However, existing analysis approaches do not allow for the complex association structures that arise due to changes in household composition over time. We propose a flexible marginal modeling approach where the changing correlation structure between individuals is modeled directly and the parameters estimated using second-order generalized estimating equations (GEE2). A key component of our correlation model specification is the 'superhousehold', a form of social network in which pairs of observations from different individuals are connected (directly or indirectly) by coresidence. These superhouseholds partition observations into clusters with nonstandard and highly variable correlation structures. We thus conduct a simulation study to evaluate the accuracy and stability of GEE2 for these models. Our approach is then applied in an analysis of individuals' attitudes towards gender roles using British Household Panel Survey data. We find strong evidence of between-individual correlation before, during and after coresidence, with large differences among spouses, parent-child, other family, and unrelated pairs. Our results suggest that these dependencies are due to a combination of non-random sorting and causal effects of coresidence.

Item Type: Article
Official URL: https://www.imstat.org/journals-and-publications/a...
Additional Information: © 2018 Institute of Mathematical Statistics
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HQ The family. Marriage. Woman
Sets: Departments > Statistics
Date Deposited: 04 Jun 2018 15:43
Last Modified: 16 Jun 2019 23:02
URI: http://eprints.lse.ac.uk/id/eprint/88162

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