Fit indices for possible latent-class analysis (LCA) models.

*Based on these considerations, Model 2 (the 2-cluster solution) was chosen as the optimal fit to our newborn population. Abbreviations: LL, log-likelihood; BIC, Bayesian Information Criterion; AIC, Akaike Information Criterion. These statistical indicators weigh out the fit and parsimony by adjusting the LL to account for the number of parameters in the model. The lower the BIC and AIC values, the better the model. Npar, number of parameters; L2, likelihood-ratio goodness-of-fit value for the current model. df, degrees of freedom; Class Err, classification error. When classification of cases is based on modal assignment (to the class having the highest membership probability), the proportion of cases that are expected to be misclassified is reported by this statistical indicator. The closer this value is to 0 (zero) the better.