Using the SPSS Mixed Procedure to Fit Cross-Sectional and Longitudinal Multilevel Models
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- 1 October 2005
- journal article
- Published by SAGE Publications in Educational and Psychological Measurement
- Vol. 65 (5) , 717-741
- https://doi.org/10.1177/0013164405278558
Abstract
Beginning with Version 11, SPSS implemented the MIXED procedure, which is capable of performing many common hierarchical linear model analyses. The purpose of this article was to provide a tutorial for performing cross-sectional and longitudinal analyses using this popular software platform. In doing so, the authors borrowed heavily from Singer’s overview of SAS PROC MIXED, duplicating her analyses using the SPSS MIXED procedure.Keywords
This publication has 16 references indexed in Scilit:
- Effects of Misspecifying the First-Level Error Structure in Two-Level Models of ChangeMultivariate Behavioral Research, 2002
- Flexible Modelling of the Covariance Matrix in a Linear Random Effects ModelBiometrical Journal, 2000
- Use of multilevel covariance structure analysis to evaluate the multilevel nature of theoretical constructsSocial Work Research, 2000
- Simple and flexible SAS and SPSS programs for analyzing lag-sequential categorical dataBehavior Research Methods, Instruments & Computers, 1999
- Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth ModelsJournal of Educational and Behavioral Statistics, 1998
- Special Issue: Hierarchical Linear Models: Problems and ProspectsJournal of Educational and Behavioral Statistics, 1995
- The Effect of Different Forms of Centering in Hierarchical Linear ModelsMultivariate Behavioral Research, 1995
- Multilevel time series models with applications to repeated measures dataStatistics in Medicine, 1994
- Multilevel Analysis MethodsSociological Methods & Research, 1994
- Estimating the Dimension of a ModelThe Annals of Statistics, 1978