Methods to assign individuals to latent classes, or taxon and complement, have been described for all three approaches (Meehl, 1995; Dolan & van der Maas, 1998; Walters & Ruscio, 2010; Fraley et al. 2012). In taxometrics, subjects can be assigned based on a cut-off on the variable chosen as the X variable, usually the hitmax point. Model-based clustering and LVMM estimations result in probabilities for each individual of belonging to each of the latent classes. The highest of these probabilities can be used to assign an individual to a class. Note that assigned class membership should not be used without caution in subsequent analysis. As pointed out by Vermunt (2010; see also Asparouhov & Muthén, 2013), to obtain adequate standard errors in subsequent analyses it is necessary to take into account the uncertainty of assigning subjects to classes. Naively using class assignments in subsequent regression analyses or tests of mean differences will result in standard errors that are too small, and therefore an inflation of statistical significance (Vermunt, 2010).
