Abstract
This chapter presents multilevel analysis as a useful tool for analyzing data where individuals are nested in varying social contexts such as classrooms, schools, or neighborhoods; time points are nested in individuals (longitudinal analyses); or situations are nested in individuals (diaries). Discussed are two-level models where individuals are nested in social contexts, time points, or situations, and three-level models where longitudinal changes or diary data are studied in varying social contexts. These models are illustrated with data from a longitudinal study of immigrant adolescents and their native classmates in varying classrooms and neighborhoods. More advanced topics such as multilevel moderation, multilevel mediation, and multilevel structural equation modeling are also covered, and statistical software options for these analyses are described.
Chapter prepared for: Cabrera, N. J., & Leyendecker, B. (Eds.), Handbook of positive development of minority children. Amsterdam, NL: Springer.
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The results differ somewhat from those reported by Motti-Stefanidi et al. (2012a) in their Table 4 mainly because the latter are estimates for Grade 1 from a longitudinal analysis of Grades 1–3 and were controlled for gender.
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Asendorpf, J.B. (2017). Measuring Positive Development I: Multilevel Analysis. In: Cabrera, N., Leyendecker, B. (eds) Handbook on Positive Development of Minority Children and Youth. Springer, Cham. https://doi.org/10.1007/978-3-319-43645-6_3
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