Computes the odds of correct classification (OCC) for each cluster. In other words, it computes the proportion of trajectories that can be expected to be correctly classified by the model for each cluster.
OCC(object)
The model, of type lcModel
.
The OCC per cluster, as a numeric vector
of length nClusters(object)
.
Empty clusters will output NA
.
An OCC of 1 indicates that the cluster assignment is no better than by random chance.
Nagin DS (2005). Group-based modeling of development. Harvard University Press. ISBN 9780674041318, doi:10.4159/9780674041318 . Klijn SL, Weijenberg MP, Lemmens P, van den Brandt PA, Passos VL (2017). “Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling.” Statistical Methods in Medical Research, 26(5), 2424-2436. van der Nest G, Lima Passos V, Candel MJ, van Breukelen GJ (2020). “An overview of mixture modelling for latent evolutions in longitudinal data: Modelling approaches, fit statistics and software.” Advances in Life Course Research, 43, 100323. ISSN 1040-2608, doi:10.1016/j.alcr.2019.100323 .