Structural equation and log-linear modeling: a comparison of methods in the analysis of a study on caregivers' health - Rosenbaum Peter L; Walter Stephen D; Zhu Bin; Russell Dianne J; Raina Parminder (BMC Medical Research Methodology, 2006)
Abstract 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.