picture. Fitting a mixture model to data in Fig. 3b permits two classes to be distinguished. In addition to sample size, it is necessary to consider how the sample is drawn. Any oversampling of subgroups that exists within the population will increase the probability of detecting those subgroups in a sample, and oversampling the tails of a continuum can create artificial groups. Finally, the results of a latent structure analysis are not necessarily generalizable to different populations. For instance, an analysis carried out on a sample from a clinical population can provide a more fine-grained focus on differences between affected individuals compared to analyses of samples drawn from the general population. Similarly, results might differ across, for example, age, gender or ethnicity.
