Structural equation and log-linear modeling: a comparison of methods in the analysis of a study on caregivers' health

Structural equation and log-linear modeling: a comparison of methods in the analysis of a study on caregivers' health

Zhu B; Walter SD; Rosenbaum P; Russell DJ; Raina P

Bmc Medical Research Methodology

2006

Child; Cross-Sectional Studies; Female; Humans; Male; Adult; Logistic Models; Questionnaires; Self Concept; Socioeconomic Factors; Ontario; Health Status; Linear Models; Adaptation; Psychological; Family/psychology; social support; disabled children; Cerebral Palsy; Telemeres; Caregivers/psychology/statistics & numerical data

BACKGROUND: In this paper we compare the results in an analysis of determinants of caregivers' health derived from two approaches, a structural equation model and a log-linear model, using the same data set. METHODS: The data were collected from a cross-sectional population-based sample of 468 families in Ontario, Canada who had a child with cerebral palsy (CP). The self-completed questionnaires and the home-based interviews used in this study included scales reflecting socio-economic status, child and caregiver characteristics, and the physical and psychological well-being of the caregivers. Both analytic models were used to evaluate the relationships between child behaviour, caregiving demands, coping factors, and the well-being of primary caregivers of children with CP. RESULTS: The results were compared, together with an assessment of the positive and negative aspects of each approach, including their practical and conceptual implications. CONCLUSION: No important differences were found in the substantive conclusions of the two analyses. The broad confirmation of the Structural Equation Modeling (SEM) results by the Log-linear Modeling (LLM) provided some reassurance that the SEM had been adequately specified, and that it broadly fitted the data.

2006

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