An approximate marginal logistic distribution for the analysis of longitudinal ordinal data.

Subject-specific and marginal models have been developed for the analysis of longitudinal ordinal data. Subject-specific models often lack a population-average interpretation of the model parameters due to the conditional formulation of random intercepts and slopes. Marginal models frequently lack an underlying distribution for ordinal data, in particular when generalized estimating equations are applied. To overcome these issues, latent variable models underneath the ordinal outcomes with a multivariate logistic distribution can be applied. In this article, we extend the work of O'Brien and Dunson (2004), who studied the multivariate t-distribution with marginal logistic distributions. We use maximum likelihood, instead of a Bayesian approach, and incorporated covariates in the correlation structure, in addition to the mean model. We compared our method with GEE and demonstrated that it performs better than GEE with respect to the fixed effect parameter estimation when the latent variables have an approximately elliptical distribution, and at least as good as GEE for other types of latent variable distributions.

Patterns of Dupuytren disease in fingers: studying correlations with a multivariate ordinal logit model.

BACKGROUND: Dupuytren disease affects fingers in a variable fashion. Knowledge about specific disease patterns (phenotype) based on location and severity of the disease is lacking. METHODS: In this cross-sectional study, 344 primary affected hands with Dupuytren disease were physically examined. The Pearson correlation coefficient between the coexistence of Dupuytren disease in pairs of fingers was calculated, and agglomerative hierarchical clustering was applied to identify possible clusters of affected fingers. With a multivariate ordinal logit model, the authors studied the correlation on severity, taking into account age and sex, and tested hypotheses on independence between groups of fingers. RESULTS: The ring finger was most frequently affected by Dupuytren disease, and contractures were seen in 15.1 percent of affected rays. The severity of thumb and index finger, middle and ring fingers, and middle and little fingers was significantly correlated. Occurrences in pairs of fingers were highest in the middle and ring fingers and lowest in the thumb and index finger. Correlation between the ring and little fingers and a correlation between fingers from the ulnar and radial sides could not be demonstrated. CONCLUSIONS: Rays on the ulnar side of the hand are predominantly affected. The middle finger is substantially correlated with other fingers on the ulnar side, and the thumb and index finger are correlated; however, there was no evidence that the ulnar side and the radial side were correlated in any way, which suggests that occurrence on one side of the hand does not predict Dupuytren disease on the other side of the hand. CLINCIAL QUESTION/LEVEL OF EVIDENCE: Risk, III.