Use this URL to cite or link to this record in EThOS:
Title: Multilevel structural equation models for the interrelationships between multiple dimensions of childhood socioeconomic circumstances, partnership stability and midlife health
Author: Zhu, Yajing
ISNI:       0000 0004 7659 3527
Awarding Body: London School of Economics and Political Science (LSE)
Current Institution: London School of Economics and Political Science (University of London)
Date of Award: 2018
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Recent studies have contributed to understanding of the mechanisms behind the association between childhood circumstances and later life. It has been hypothesized that experiences in childhood operate through influencing trajectories of life events and functional changes in health-related behaviours that can mediate the effects of childhood socioeconomic circumstances (SECs) on later health. Using data from the 1958 British birth cohort, we propose a multilevel structural equation modelling (SEM) approach to investigate the mediating effects of partnership stability, an example of life events in adulthood. Childhood circumstances are abstract concepts with multiple dimensions, each measured by a number of indicators over four childhood waves (at ages 0, 7, 11 and 16). Latent class models are fitted to each set of these indicators and the derived categorical latent variables characterise the patterns of change in four dimensions of childhood SECs. To relate these latent variables to a distal outcome, we first extend the 3-step maximum likelihood (ML) method to handle multiple, associated categorical latent variables and investigate sensitivity of the proposed estimation approach to departures from model assumptions. We then extend the 3-step ML approach to estimate models with multiple outcomes of mixed types and at different levels in a hierarchical data structure. The final multilevel SEM is comprised of latent class models and a joint regression model that relates these categorical latent variables to partnership transitions in adulthood and midlife health, while allowing for informative dropout. Most likely class memberships are treated as imperfect measurements of the latent classes. Life events (e.g. partnership transitions), distal outcomes (e.g. midlife health) and dropout indicators are viewed as items of one or more individual-level latent variables. To account for endogeneity and indirect associations, the effects of childhood SECs on partnership transitions for ages 16-50 and distal health at age 50 are jointly modelled by allowing for a residual association across equations due to shared but differential influences of time-invariant unobservables on each response. Finally, sensitivity analyses are performed to investigate the extent to which the specifications of the dropout model influence the estimated effects of childhood SECs on midlife health.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Keywords: HA Statistics