The nomothetic approach (i.e., the study of interindividual variation) dominates analyses of clinical data, even though its assumption of homogeneity across people and time is often violated. The idiographic approach (i.e., the study of intraindividual variation) is best suited for analyses of heterogeneous clinical data, but its person-specific methods and results have been criticized as unwieldy. Group iterative multiple model estimation (GIMME) combines the assets of the nomothetic and idiographic approaches by creating person-specific maps that contain a group-level structure. The maps show how intensively measured variables predict and are predicted by each other at different time scales. In this article, GIMME is introduced conceptually and mathematically, and then applied to an empirical data set containing the negative affect, detachment, disinhibition, and hostility composite ratings from the daily diaries of 25 individuals with personality pathology. Results are discussed with the aim of elucidating GIMME's potential for clinical research and practice.

Our findings suggest that activity diversity may play an important role in older adults' concurrent well-being and also in their long-term longitudinal improvements of well-being.

This is the first study to demonstrate differential longitudinal cognitive training transfer effects to three performance-based physical functioning measures. Future research should investigate mechanisms of far-transfer effects.

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drafted the letter. Edward R. Marcantonio acquired the data. Yoojin Jung and Long Ngo analyzed the data. All the authors interpreted the data and critically revised and approved the final submission for important intellectual content.