Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling.
Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.
1 Department of Methodology and Statistics, Maastricht University, Maastricht, the Netherlands.
Sven L
SL
Klijn
2 Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht, the Netherlands.
Matty P
MP
Weijenberg
3 Department of Health Promotion, Maastricht, the Netherlands.
Paul
P
Lemmens
4 Department of Epidemiology, GROW School for Oncology and Developmental Biology, CAPHRI School for Public Health and Primary Care, Maastricht University, Maastricht, the Netherlands.
Piet A
PA
van den Brandt
1 Department of Methodology and Statistics, Maastricht University, Maastricht, the Netherlands.
Valéria
V
Lima Passos
D000428:Alcohol Drinking / Q000009:adverse effects; D002318:Cardiovascular Diseases / Q000209:etiology; D003627:Data Interpretation, Statistical; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D013223:Statistics as Topic
Group-based trajectory model; class-enumeration; finite mixture model; model dimensionality; model selection; proc traj