Transcription of Using lme4: Mixed-Effects Modeling in R
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Using lme4: Mixed-Effects Modeling in R
SimpleLongitudinalInteractionsTheoryGLMM Item ResponseNLMMU sing lme4 : Mixed-Effects Modeling in RDouglas BatesUniversity of Wisconsin - Madisonand R Development Core 11, 2008 SimpleLongitudinalInteractionsTheoryGLMM Item ResponseNLMMO utlineOrganizing and plotting data; simple, scalar random effectsModels for longitudinal dataInteractions of grouping factors and other covariatesEvaluating the log-likelihoodGeneralized Linear mixed ModelsItem Response Models as GLMMsNonlinear mixed ModelsSimpleLongitudinalInteractionsTheo ryGLMMItem ResponseNLMMO utlineOrganizing and plotting data; simple, scalar random effectsModels for longitudinal dataInteractions of grouping factors and other covariatesEvaluating the log-likelihoodGeneralized Linear mixed ModelsItem Response Models as GLMMsNonlinear mixed ModelsSimpleLongitudinalInteractionsTheo ryGLMMItem ResponseNLMMO utlineOrganizing and plotting data; simple, scalar random effectsModels for longitudinal dataInteractions of grouping factors and other covariatesEvaluating the log-likelihoodGeneralized Linear mixed ModelsItem Response Models as GLMMsNonlinear mixed ModelsSimpleLongit
Simple, scalar random-e ects terms In a simple, scalar random-e ects term, the expression on the left of the ‘|’ is ‘1’. Such a term generates one random e ect (i.e. a scalar) for each level of the grouping factor. Each random-e ects term contributes a set of columns to Z. For a simple, scalar r.e. term these are the indicator columns
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