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 Data
- References
The DDFM=CONTAIN method is carried out as follows: Denote the fixed effect in question as A and search the G-side random effect list for the effects that syntactically contain A. For example, the effect B(A) contains A, but the effect C does not, even if it has the same levels as B(A).
Among the random effects that contain A, compute their rank contributions to the ![$[\mb {X\, \, \, Z}]$](images/statug_glimmix0749.png){kind=small}
matrix (in order). The denominator degrees of freedom that is assigned to A is the smallest of these rank contributions. If no effects are found, the denominator degrees of freedom for A is set equal to the residual degrees of freedom, ![$n - \mr {rank}[\mb {X\, \, \, Z}]$](images/statug_glimmix0750.png){kind=small}
. This choice of degrees of freedom is the same as for the tests performed for balanced split-plot designs and should be adequate
for moderately unbalanced designs.
Note: If you have a 
matrix with a large number of columns, the overall memory requirements and the computing time after convergence can be substantial
for the containment method. In this case, you might want to use a different degrees-of-freedom method, such as DDFM=RESIDUAL,
DDFM=NONE, or DDFM=BETWITHIN.