Extension to the PATHMOX Approach to Detect Which Constructs Differentiate Segments and to Test Factor Invariance: Application to Mental Health Data
In this paper we propose an extension to the PATHMOX segmentation algorithm to detect which endogenous latent variables and predictors are responsible for heterogeneity. We also address the problem of factor invariance in the terminal nodes of PATHMOX. We demonstrate the utility of such methodology on real mental health data by investigating the relationship between dementia, depression and delirium.
KeywordsPATHMOX Latent variables Segmentation
The data analyzed in this paper were collected with funding from the Canadian Institutes of Health Research (IAO69519), Canadian Institute of Aging & Institute of Gender and Health (CRG-82953) and the Alzheimer Society of Canada and the Canadian Nurses Foundation (07-91). Data were used with permission by J. McCusker and M. G. Cole.
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