The GLIMMIX Procedure
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Overview
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Getting Started
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SyntaxPROC GLIMMIX StatementBY StatementCLASS StatementCODE StatementCONTRAST StatementCOVTEST StatementEFFECT StatementESTIMATE StatementFREQ StatementID StatementLSMEANS StatementLSMESTIMATE StatementMODEL StatementNLOPTIONS StatementOUTPUT StatementPARMS StatementRANDOM StatementSLICE StatementSTORE StatementWEIGHT StatementProgramming StatementsUser-Defined Link or Variance Function
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DetailsGeneralized Linear Models TheoryGeneralized Linear Mixed Models TheoryGLM Mode or GLMM ModeStatistical Inference for Covariance ParametersDegrees of Freedom MethodsEmpirical Covariance ("Sandwich") EstimatorsExploring and Comparing Covariance MatricesProcessing by SubjectsRadial Smoothing Based on Mixed ModelsOdds and Odds Ratio EstimationParameterization of Generalized Linear Mixed ModelsResponse-Level Ordering and ReferencingComparing the GLIMMIX and MIXED ProceduresSingly or Doubly Iterative FittingDefault Estimation TechniquesDefault OutputNotes on Output StatisticsODS Table NamesODS Graphics
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ExamplesBinomial Counts in Randomized BlocksMating Experiment with Crossed Random EffectsSmoothing Disease Rates; Standardized Mortality RatiosQuasi-likelihood Estimation for Proportions with Unknown DistributionJoint Modeling of Binary and Count DataRadial Smoothing of Repeated Measures DataIsotonic Contrasts for Ordered AlternativesAdjusted Covariance Matrices of Fixed EffectsTesting Equality of Covariance and Correlation MatricesMultiple Trends Correspond to Multiple Extrema in Profile LikelihoodsMaximum Likelihood in Proportional Odds Model with Random EffectsFitting a Marginal (GEE-Type) ModelResponse Surface Comparisons with Multiplicity AdjustmentsGeneralized Poisson Mixed Model for Overdispersed Count DataComparing Multiple B-SplinesDiallel Experiment with Multimember Random EffectsLinear Inference Based on Summary DataWeighted Multilevel Model for Survey DataQuadrature Method for Multilevel Model
- References
Type III Tests of Fixed Effects
The "Type III Tests of Fixed Effects" table contains hypothesis tests for the significance of each of the fixed effects specified
in the MODEL
statement. By default, PROC GLIMMIX computes these tests by first constructing a Type III 
matrix for each effect; see Chapter 15: The Four Types of Estimable Functions.
The matrix is then used to construct the test statistic
![\[ F = \frac{ \widehat{\bbeta }' \bL '(\bL \bQ \bL ')^{-1} \bL \widehat{\bbeta } }{\mr{rank}(\bL \bQ \bL ')} \]](images/statug_glimmix0930.png)
where the matrix 
depends on the estimation method and options. For example, in a GLMM, the default is 
, where 
is the marginal variance of the pseudo-response. If you specify the DDFM
=KENWARDROGER option, is the estimated variance matrix of the fixed effects, adjusted by the method of Kenward and Roger (1997). If the EMPIRICAL=
option is in effect, corresponds to the selected sandwich estimator.
You can use the HTYPE= option in the MODEL statement to obtain tables of Type I (sequential) tests and Type II (adjusted) tests in addition to or instead of the table of Type III (partial) tests.
The ODS names of the "Type I Tests of Fixed Effects" through the "Type III Tests of Fixed Effects" tables are Tests1 through Tests3, respectively.