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Applied Longitudinal Data AnalysisModeling Change and Event Occurrence$
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Judith D. Singer and John B. Willett

Print publication date: 2003

Print ISBN-13: 9780195152968

Published to Oxford Scholarship Online: September 2009

DOI: 10.1093/acprof:oso/9780195152968.001.0001

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Doing Data Analysis with the Multilevel Model for Change

Doing Data Analysis with the Multilevel Model for Change

Chapter:
(p.75) 4 Doing Data Analysis with the Multilevel Model for Change
Source:
Applied Longitudinal Data Analysis
Author(s):

Judith D. Singer

John B. Willett

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195152968.003.0004

This chapter delves deeper into the specification, estimation, and interpretation of the multilevel model for change. Following introduction of a new data set, it presents a composite formulation of the model that combines the level-1 and level-2 submodels together into a single equation. The new composite model leads naturally to consideration of alternative methods of estimation. The chapter not only describes two new methods—generalized least squares (GLS) and iterative generalized least squares (IGLS) within each, it distinguishes further between two types of approaches, the full and the restricted. The remainder of the chapter focuses on real-world issues of data analysis.

Keywords:   change, multilevel mode, alcohol use, estimation, Wald statistics, fixed effects, least squares method, IGLS

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