Identifying atypical cortisol patterns in young children: The benefits of group-based trajectory modeling.

The introduction of growth curve modeling into the field of neuroendocrinology has enabled researchers to examine mean patterns of change in unbalanced and/or incomplete repeated measures data. However, growth curve modeling assumes population homogeneity, or that all individuals follow roughly the same pattern of change, with differences expressed as deviation around the mean curve. Group-based trajectory modeling, in contrast, is designed for heterogeneous populations and as a result is able to identify atypical patterns of change over time that may exist within a population.