Multilevel modeling for repeated measures: Difference between revisions

Revision as of 21:31, 27 April 2012

Revision as of 21:35, 27 April 2012

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*'''Fixed Effects:''' Fixed regression coefficients may be obtained for an overall equation that represents how, averaging across subjects, the subjects change over time.

*'''Random Effects:''' Random effects are the variance components that arise from measuring the relationship of the predictors to Y for each subject separately. These variance components include: (1) differences in the intercepts of these equations at the level of the subject; (2) differences across subjects in the slopes of these equations; and (3) covariance between subject slopes and intercepts across all subjects. When random coefficients are specified, each subject has its own regression equation, making it possible to evaluate whether subjects differ in their means and/or response patterns over time.

*'''Estimation Procedures & Comparing Models:''' These procedures are identical to those used in multilevel analysis where subjects are clustered in groups.