Mixture distributions in multi-state modelling: some considerations in a study of psoriatic arthritis.


Type
Article
Change log
Authors
O'Keeffe, Aidan G 
Tom, Brian DM 
Farewell, Vernon T 
Abstract

In many studies, interest lies in determining whether members of the study population will undergo a particular event of interest. Such scenarios are often termed 'mover-stayer' scenarios, and interest lies in modelling two sub-populations of 'movers' (those who have a propensity to undergo the event of interest) and 'stayers' (those who do not). In general, mover-stayer scenarios within data sets are accounted for through the use of mixture distributions, and in this paper, we investigate the use of various random effects distributions for this purpose. Using data from the University of Toronto psoriatic arthritis clinic, we present a multi-state model to describe the progression of clinical damage in hand joints of patients with psoriatic arthritis. We consider the use of mover-stayer gamma, inverse Gaussian and compound Poisson distributions to account for both the correlation amongst joint locations and the possible mover-stayer situation with regard to clinical hand joint damage. We compare the fits obtained from these models and discuss the extent to which a mover-stayer scenario exists in these data. Furthermore, we fit a mover-stayer model that allows a dependence of the probability of a patient being a stayer on a patient-level explanatory variable.

Description
Keywords
Arthritis, Psoriatic, Biostatistics, Disease Progression, Hand Joints, Humans, Likelihood Functions, Models, Biological, Models, Statistical, Poisson Distribution, Probability
Journal Title
Stat Med
Conference Name
Journal ISSN
0277-6715
1097-0258
Volume Title
32
Publisher
Wiley
Sponsorship
MRC (unknown)