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Longitudinal measurement in health‐related surveys. A Bayesian joint growth model for multivariate ordinal responses
Author(s) -
Verhagen Josine,
Fox JeanPaul
Publication year - 2012
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.5692
Subject(s) - multivariate statistics , random effects model , statistics , ordinal data , bayesian probability , psychology , ordinal scale , depression (economics) , item response theory , ordinal regression , latent variable model , longitudinal study , mental health , latent variable , econometrics , mathematics , medicine , psychometrics , psychiatry , meta analysis , economics , macroeconomics
Longitudinal surveys measuring physical or mental health status are a common method to evaluate treatments. Multiple items are administered repeatedly to assess changes in the underlying health status of the patient. Traditional models to analyze the resulting data assume that the characteristics of at least some items are identical over measurement occasions. When this assumption is not met, this can result in ambiguous latent health status estimates. Changes in item characteristics over occasions are allowed in the proposed measurement model, which includes truncated and correlated random effects and a growth model for item parameters. In a joint estimation procedure adopting MCMC methods, both item and latent health status parameters are modeled as longitudinal random effects. Simulation study results show accurate parameter recovery. Data from a randomized clinical trial concerning the treatment of depression by increasing psychological acceptance showed significant item parameter shifts. For some items, the probability of responding in the middle category versus the highest or lowest category increased significantly over time. The resulting latent depression scores decreased more over time for the experimental group than for the control group and the amount of decrease was related to the increase in acceptance level. Copyright © 2012 John Wiley & Sons, Ltd.