The article by Patrick J. Curran and Daniel J. Bauer explores the importance of disaggregating within-person and between-person effects in longitudinal models, particularly in the behavioral sciences. The authors highlight that while longitudinal data offer advantages such as increased power and the ability to establish temporal precedence, they are often underutilized in social science research due to the lack of discussion on effect disaggregation and analytical challenges. They review existing methods, propose a general approach, and demonstrate their utility through simulated data. The review emphasizes the need for better methods to handle the complex issues arising from repeated measures data, which can complicate the disaggregation of within- and between-person effects. The authors also discuss potential limitations and future research directions, offering recommendations for practical application. The article underscores the critical role of longitudinal data in evaluating within-person processes and the importance of developing robust methods to fully capitalize on these data.The article by Patrick J. Curran and Daniel J. Bauer explores the importance of disaggregating within-person and between-person effects in longitudinal models, particularly in the behavioral sciences. The authors highlight that while longitudinal data offer advantages such as increased power and the ability to establish temporal precedence, they are often underutilized in social science research due to the lack of discussion on effect disaggregation and analytical challenges. They review existing methods, propose a general approach, and demonstrate their utility through simulated data. The review emphasizes the need for better methods to handle the complex issues arising from repeated measures data, which can complicate the disaggregation of within- and between-person effects. The authors also discuss potential limitations and future research directions, offering recommendations for practical application. The article underscores the critical role of longitudinal data in evaluating within-person processes and the importance of developing robust methods to fully capitalize on these data.