A Log-Linear Modelling Approach to Assessing The Consistency of Ego Reports of Dyadic Outcomes With Applications to Fertility and Sexual Partnerships
Year: 2014
Type: article
Abstract: We propose a log-linear model to assess the consistency of ego reports of dyadic outcomes. We do so specifically in the context where males and females report on shared events, and we demonstrate how inconsistencies can be assessed by using a log-linear model that estimates separate mixing totals for each set of reports. This modelling approach immediately allows us to determine where inconsistencies in reports occur. To demonstrate how our method can be easily implemented for survey data, we apply it to both the 1992 National Health and Social Life Survey and the 2002 National Survey of Family Growth. Our analysis identifies inconsistencies in male and female reports of concurrent partnerships and the number of biological children.
DOI: 10.1111/rssa.12067
Authors: Ryan Admiraal, Mark S. Handcock
Institutions: Murdoch University, University of California, Los Angeles
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
SDG: Gender equality
Open Access status: bronze
Funders: National Science Foundation, Australian Government, Office for Learning and Teaching, National Institutes of Health, Office of Naval Research, National Institute of Child Health and Human Development, California Center for Population Research, University of California, Los Angeles, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G2507980080, G2998923865, G4154686922, Innovations in Network Modeling for HIV Prevention Studies, G6298873131, California Center for Population Research (CCPR) at UCLA, Statistical Methods for Respondent Driven Sampling Data, G8876996369, Valid Inference for Respondent Driven Sampling of Hidden Networked Populations
OpenAlex ID: W2126087795