Table 1

Framework of eight steps to construct a latent class trajectory model

StepStep descriptionCriteria for selection
1Scope model by provisionally selecting a plausible number of classes based on available literature and the structure based on plausible clinical patterns.Examine linearity of the shape of standardised residual plots for each of the classes in a model with no random effects.
2Refine the model from step 1 to confirm the optimal number of classes, typically testing K=1–7 classes.Lowest Bayesian information criteria value.
3Refine optimal model structure from fixed through to unrestricted random effects of the model using the favoured K derived in step 2.
4Run model adequacy assessments as described in online supplementary table S3 including posterior probability of assignments (APPA), odds of correct classification (OCC) and relative entropy.
  • APPA: average of maximum probabilities should be greater than 70% for all classes.

  • OCC values greater than 5.0.

  • Relative entropy values greater than 0.5.

5Investigate graphical presentation
  • Plot mean trajectories across time for each class in a single graph.

  • Plot mean trajectories with 95% predictive intervals for each class (one class per graph).

  • Plot individual class ‘spaghetti plots’ across time for a random sample.

6Run additional tools to assess discrimination including Degrees of separation (DoS) and Elsensohn’s envelope of residuals
  • DoS greater than zero.

  • Envelope of residuals is assessed in plots by observing clear separations between classes.

7Assess for clinical characterisation and plausibility.
  • Tabulation of characteristics by latent classes. Are the trajectory patterns clinically meaningful? Perhaps, consider classes with a minimum percentage of the population.

  • Are the trajectory patterns clinically plausible?

  • Concordance of class characteristics with those for other well-established variables.

8Conduct sensitivity analyses, for example, testing models without complete data at all time points.General assessment of patterns of trajectories compared with main model.