This study proposes a new model, termed the multiple membership piecewise growth model (MM-PGM), to handle individual mobility across clusters frequently encountered in longitudinal studies, especially in educational research wherein some students could attend multiple schools during the course of the study. A real data set containing some students who switched elementary schools was used to demonstrate and explain the MM-PGM. Parameter and model fit differences were compared between the MM-PGM and two other techniques for handling student mobility: the first school-PGM, which only used school membership at the first measurement occasion, and the delete-PGM, which removed mobile students from the analysis. Results indicated that the three approaches of handling mobile students led to different conclusions about the impact of school-level predictors of growth parameters and the school-level variability in the growth rates. Furthermore, deleting mobile students altered the impact of student-level predictors compared to the other two approaches.