Skinner, Chris J. and Steele, Fiona (2020) Estimation of dyadic characteristics of family networks using sample survey data. Annals of Applied Statistics, 14 (2). pp. 706-726. ISSN 1932-6157, http://eprints.lse.ac.uk/102338/
We consider the use of sample survey data to estimate dyadic characteristics of family networks, with an application to non-coresident parent-child dyads. We suppose that survey respondents report either from a parent or child perspective about a dyad, depending on their membership of the dyad. We construct separate estimators of com- mon dyadic characteristics using data from both a parent and a child perspective and show how comparisons of these estimators can shed light on data quality issues including differential missingness and re- porting error. In our application we find that a simple missingness model explains some striking patterns of discrepancies between the estimators and consider the use of poststratification and a related re- definition of count variables to adjust for these discrepancies. We also develop approaches to combining the separate estimators efficiently to estimate means and frequency distributions within subpopulations.
Steele, Fiona and Grundy, Emily (2020) Random effects dynamic panel models for unequally-spaced multivariate categorical repeated measures: an application to child-parent exchanges of support. Journal of the Royal Statistical Society. Series C: Applied Statistics. ISSN 0964-1998 (In Press) http://eprints.lse.ac.uk/106255/
Exchanges of practical or financial help between people living in different households are a major component of intergenerational exchanges within families and an increasingly important source of support for individuals in need. Using longitudinal data, bivariate dynamic panel models can be applied to study the effects of changes in individual circumstances on help given to and received from non-coresident parents and the reciprocity of exchanges. However, the use of a rotating module for collection of data on exchanges leads to data where the response measurements are unequally spaced and taken less frequently than for the time-varying covariates. Existing approaches to this problem focus on fixed effects linear models for univariate continuous responses. We propose a random effects estimator for a family of dynamic panel models that can handle continuous, binary or ordinal multivariate responses. The performance of the estimator is assessed in a simulation study. A bivariate probit dynamic panel model is then applied to estimate the effects of partnership and employment transitions in the previous year and the presence and age of children in the current year on an individual’s propensity to give or receive help. Annual data on respondents’ partnership and employment status and dependent children and data on exchanges of help collected at 2- and 5-year intervals are used.
Irini Moustaki “Modelling intergenerational exchanges using models for multivariate longitudinal data with latent variables in the presence of zero excess”, City University of New York (CUNY) Graduate Center, 1 April 2019.
Irini Moustaki “Modelling intergenerational exchanges using models for multivariate longitudinal data with latent variables in the presence of zero excess”, Center for Practice and Research at the Intersection of Information, Society and Methodology (PRIISM), NYU Steinhardt, 17 April 2019.
Jouni Kuha “Latent variables models for intergenerational exchanges of family support”, International Meeting of the Psychometric Society, Santiago (Chile), 15-19 July 2109.
Irini Moustaki “multivariate longitudinal data with zero inflation: a study of intergenerational exchanges”, International Meeting of the Psychometric Society, Santiago (Chile), 15-19 July 2019.
Fiona Steele “Dynamic models for longitudinal multivariate data with responses measured at unequal intervals”, Statistical Analysis of Multi-Outcome Data, University of Manchester, 6-7 June 2019 (keynote).
Fiona Steele “Random effects dynamic panel models for unequally-spaced outcomes”, Understanding Society Scientific Conference, University of Essex, 3 July 2019.
Fiona Steele “Random effects dynamic panel models for unequally-spaced outcomes”, International Workshop on Statistical Modeling, Guimarães, Portugal, 8-12 July 2019.
Fiona Steele “Random effects dynamic panel models for unequally-spaced outcomes”, 12th International Conference of the ERCIM Working Group on Computational and Methodological Statistics, University of London, 14-16 December 2019 (invited presentation).