PROC MIXED: ODS Table Names :: SAS/STAT(R) 9.2 User's Guide, Second Edition

The MIXED Procedure

ODS Table Names

Each table created by PROC MIXED has a name associated with it, and you must use this name to reference the table when using ODS statements. These names are listed in Table 56.22.

Table 56.22 ODS Tables Produced by PROC MIXED
Table Name	Description	Required Statement / Option
AccRates	acceptance rates for posterior sampling	PRIOR
AsyCorr	asymptotic correlation matrix of covariance parameters	PROC MIXED ASYCORR
AsyCov	asymptotic covariance matrix of covariance parameters	PROC MIXED ASYCOV
Base	base densities used for posterior sampling	PRIOR
Bound	computed bound for posterior rejection sampling	PRIOR
CholG	Cholesky root of the estimated $\text{[math]}$ matrix	RANDOM / GC
CholR	Cholesky root of blocks of the estimated $\text{[math]}$ matrix	REPEATED / RC
CholV	Cholesky root of blocks of the estimated $\text{[math]}$ matrix	RANDOM / VC
ClassLevels	level information from the CLASS statement	default output
Coef	$\text{[math]}$ matrix coefficients	E option in MODEL, CONTRAST, ESTIMATE, or LSMEANS
Contrasts	results from the CONTRAST statements	CONTRAST
ConvergenceStatus	convergence status	default
CorrB	approximate correlation matrix of fixed-effects parameter estimates	MODEL / CORRB
CovB	approximate covariance matrix of fixed-effects parameter estimates	MODEL / COVB
CovParms	estimated covariance parameters	default output
Diffs	differences of LS-means	LSMEANS / DIFF (or PDIFF)
Dimensions	dimensions of the model	default output
Estimates	results from ESTIMATE statements	ESTIMATE
FitStatistics	fit statistics	default
G	estimated $\text{[math]}$ matrix	RANDOM / G
GCorr	correlation matrix from the estimated $\text{[math]}$ matrix	RANDOM / GCORR
HLM1	Type 1 Hotelling-Lawley-McKeon tests of fixed effects	MODEL / HTYPE=1 and REPEATED / HLM TYPE=UN
HLM2	Type 2 Hotelling-Lawley-McKeon tests of fixed effects	MODEL / HTYPE=2 and REPEATED / HLM TYPE=UN
HLM3	Type 3 Hotelling-Lawley-McKeon tests of fixed effects	REPEATED / HLM TYPE=UN
HLPS1	Type 1 Hotelling-Lawley-Pillai- Samson tests of fixed effects	MODEL / HTYPE=1 and REPEATED / HLPS TYPE=UN
HLPS2	Type 2 Hotelling-Lawley-Pillai- Samson tests of fixed effects	MODEL / HTYPE=1 and REPEATED / HLPS TYPE=UN
HLPS3	Type 3 Hotelling-Lawley-Pillai- Samson tests of fixed effects	REPEATED / HLPS TYPE=UN
Influence	influence diagnostics	MODEL / INFLUENCE
InfoCrit	information criteria	PROC MIXED IC
InvCholG	inverse Cholesky root of the estimated $\text{[math]}$ matrix	RANDOM / GCI
InvCholR	inverse Cholesky root of blocks of the estimated $\text{[math]}$ matrix	REPEATED / RCI
InvCholV	inverse Cholesky root of blocks of the estimated $\text{[math]}$ matrix	RANDOM / VCI
InvCovB	inverse of approximate covariance matrix of fixed-effects parameter estimates	MODEL / COVBI
InvG	inverse of the estimated $\text{[math]}$ matrix	RANDOM / GI
InvR	inverse of blocks of the estimated $\text{[math]}$ matrix	REPEATED / RI
InvV	inverse of blocks of the estimated $\text{[math]}$ matrix	RANDOM / VI
IterHistory	iteration history	default output
LComponents	single-degree-of-freedom estimates corresponding to rows of the $\text{[math]}$ matrix for fixed effects	MODEL / LCOMPONENTS
LRT	likelihood ratio test	default output
LSMeans	LS-means	LSMEANS
MMEq	mixed model equations	PROC MIXED MMEQ
MMEqSol	mixed model equations solution	PROC MIXED MMEQSOL
ModelInfo	model information	default output
NObs	number of observations read and used	default output
ParmSearch	parameter search values	PARMS
Posterior	posterior sampling information	PRIOR
R	blocks of the estimated $\text{[math]}$ matrix	REPEATED / R
RCorr	correlation matrix from blocks of the estimated $\text{[math]}$ matrix	REPEATED / RCORR
Search	posterior density search table	PRIOR / PSEARCH
Slices	tests of LS-means slices	LSMEANS / SLICE=
SolutionF	fixed-effects solution vector	MODEL / S
SolutionR	random-effects solution vector	RANDOM / S
Tests1	Type 1 tests of fixed effects	MODEL / HTYPE=1
Tests2	Type 2 tests of fixed effects	MODEL / HTYPE=2
Tests3	Type 3 tests of fixed effects	default output
Type1	Type 1 analysis of variance	PROC MIXED METHOD=TYPE1
Type2	Type 2 analysis of variance	PROC MIXED METHOD=TYPE2
Type3	Type 3 analysis of variance	PROC MIXED METHOD=TYPE3
Trans	transformation of covariance parameters	PRIOR / PTRANS
V	blocks of the estimated $\text{[math]}$ matrix	RANDOM / V
VCorr	correlation matrix from blocks of the estimated $\text{[math]}$ matrix	RANDOM / VCORR

In Table 56.22, "Coef" refers to multiple tables produced by the E, E1, E2, or E3 option in the MODEL statement and the E option in the CONTRAST, ESTIMATE, and LSMEANS statements. You can create one large data set of these tables with a statement similar to the following:

   ods output Coef=c;

To create separate data sets, use the following statement:

   ods output Coef(match_all)=c;

Here the resulting data sets are named C, C1, C2, etc. The same principles apply to data sets created from the "R," "CholR," "InvCholR," "RCorr," "InvR," "V," "CholV," "InvCholV," "VCorr," and "InvV" tables.

In Table 56.22, the following changes have occurred from SAS 6. The "Predicted," "PredMeans," and "Sample" tables from SAS 6 no longer exist and have been replaced by output data sets; see descriptions of the MODEL statement options OUTPRED= and OUTPREDM= and the PRIOR statement option OUT= for more details. The "ML" and "REML" tables from SAS 6 have been replaced by the "IterHistory" table. The "Tests," "HLM," and "HLPS" tables from SAS 6 have been renamed "Tests3," "HLM3," and "HLPS3," respectively.

Table 56.23 lists the variable names associated with the data sets created when you use the ODS OUTPUT option in conjunction with the preceding tables. In Table 56.23, $\text{[math]}$ is used to denote a generic number that depends on the particular data set and model you select, and it can assume a different value each time it is used (even within the same table). The phrase model specific appears in rows of the affected tables to indicate that columns in these tables depend on the variables you specify in the model.

Caution: There is a danger of name collisions with the variables in the model specific tables in Table 56.23 and variables in your input data set. You should avoid using input variables with the same names as the variables in these tables.

Table 56.23 Variable Names for the ODS Tables Produced in PROC MIXED
Table Name	Variables
AsyCorr	Row, CovParm, CovP1–CovP $\text{[math]}$
AsyCov	Row, CovParm, CovP1–CovP $\text{[math]}$
BaseDen	Type, Parm1–Parm $\text{[math]}$
Bound	Technique, Converge, Iterations, Evaluations, LogBound, CovP1–CovP $\text{[math]}$ , TCovP1–TCovP $\text{[math]}$
CholG	model specific, Effect, Subject, Sub1–Sub $\text{[math]}$ , Group, Group1–Group $\text{[math]}$ , Row, Col1–Col $\text{[math]}$
CholR	Index, Row, Col1–Col $\text{[math]}$
CholV	Index, Row, Col1–Col $\text{[math]}$
ClassLevels	Class, Levels, Values
Coef	model specific, LMatrix, Effect, Subject, Sub1–Sub $\text{[math]}$ , Group, Group1–Group $\text{[math]}$ , Row1–Row $\text{[math]}$
Contrasts	Label, NumDF, DenDF, ChiSquare, FValue, ProbChiSq, ProbF
CorrB	model specific, Effect, Row, Col1–Col $\text{[math]}$
CovB	model specific, Effect, Row, Col1–Col $\text{[math]}$
CovParms	CovParm, Subject, Group, Estimate, StandardError, ZValue, ProbZ, Alpha, Lower, Upper
Diffs	model specific, Effect, Margins, ByLevel, AT variables, Diff, StandardError, DF, tValue, Tails, Probt, Adjustment, Adjp, Alpha, Lower, Upper, AdjLow, AdjUpp
Dimensions	Descr, Value
Estimates	Label, Estimate, StandardError, DF, tValue, Tails, Probt, Alpha, Lower, Upper
FitStatistics	Descr, Value
G	model specific, Effect, Subject, Sub1–Sub $\text{[math]}$ , Group, Group1–Group $\text{[math]}$ , Row, Col1–Col $\text{[math]}$
GCorr	model specific, Effect, Subject, Sub1–Sub $\text{[math]}$ , Group, Group1–Group $\text{[math]}$ , Row, Col1–Col $\text{[math]}$
HLM1	Effect, NumDF, DenDF, FValue, ProbF
HLM2	Effect, NumDF, DenDF, FValue, ProbF
HLM3	Effect, NumDF, DenDF, FValue, ProbF
HLPS1	Effect, NumDF, DenDF, FValue, ProbF
HLPS2	Effect, NumDF, DenDF, FValue, ProbF
HLPS3	Effect, NumDF, DenDF, FValue, ProbF
Influence	dependent on option modifiers, Effect, Tuple, Obs1–Obs $\text{[math]}$ , Level, Iter, Index, Predicted, Residual, Leverage, PressRes, PRESS, Student, RMSE, RStudent, CookD, DFFITS, MDFFITS, CovRatio, CovTrace, CookDCP, MDFFITSCP, CovRatioCP, CovTraceCP, LD, RLD, Parm1–Parm $\text{[math]}$ , CovP1–CovP $\text{[math]}$ , Notes
InfoCrit	Neg2LogLike, Parms, AIC, AICC, HQIC, BIC, CAIC
InvCholG	model specific, Effect, Subject, Sub1–Sub $\text{[math]}$ , Group, Group1–Group $\text{[math]}$ , Row, Col1–Col $\text{[math]}$
InvCholR	Index, Row, Col1–Col $\text{[math]}$
InvCholV	Index, Row, Col1–Col $\text{[math]}$
InvCovB	model specific, Effect, Row, Col1–Col $\text{[math]}$
InvG	model specific, Effect, Subject, Sub1–Sub $\text{[math]}$ , Group, Group1–Group $\text{[math]}$ , Row, Col1–Col $\text{[math]}$
InvR	Index, Row, Col1–Col $\text{[math]}$
InvV	Index, Row, Col1–Col $\text{[math]}$
IterHistory	CovP1–CovP $\text{[math]}$ , Iteration, Evaluations, M2ResLogLike, M2LogLike, Criterion
LComponents	Effect, TestType, LIndex, Estimate, StdErr, DF, tValue, Probt
LRT	DF, ChiSquare, ProbChiSq
LSMeans	model specific, Effect, Margins, ByLevel, AT variables, Estimate, StandardError, DF, tValue, Probt, Alpha, Lower, Upper, Cov1–Cov $\text{[math]}$ , Corr1–Corr $\text{[math]}$
MMEq	model specific, Effect, Subject, Sub1–Sub $\text{[math]}$ , Group, Group1–Group $\text{[math]}$ , Row, Col1–Col $\text{[math]}$
MMEqSol	model specific, Effect, Subject, Sub1–Sub $\text{[math]}$ , Group, Group1–Group $\text{[math]}$ , Row, Col1–Col $\text{[math]}$
ModelInfo	Descr, Value
Nobs	Label, N, NObsRead, NObsUsed, SumFreqsRead, SumFreqsUsed
ParmSearch	CovP1–CovP $\text{[math]}$ , Var, ResLogLike, M2ResLogLike2, LogLike, M2LogLike, LogDetH
Posterior	Descr, Value
R	Index, Row, Col1–Col $\text{[math]}$
RCorr	Index, Row, Col1–Col $\text{[math]}$
Search	Parm, TCovP1–TCovP $\text{[math]}$ , Posterior
Slices	model specific, Effect, Margins, ByLevel, AT variables, NumDF, DenDF, FValue, ProbF
SolutionF	model specific, Effect, Estimate, StandardError, DF, tValue, Probt, Alpha, Lower, Upper
SolutionR	model specific, Effect, Subject, Sub1–Sub $\text{[math]}$ , Group, Group1–Group $\text{[math]}$ , Estimate, StdErrPred, DF, tValue, Probt, Alpha, Lower, Upper
Tests1	Effect, NumDF, DenDF, ChiSquare, FValue, ProbChiSq, ProbF
Tests2	Effect, NumDF, DenDF, ChiSquare, FValue, ProbChiSq, ProbF
Tests3	Effect, NumDF, DenDF, ChiSquare, FValue, ProbChiSq, ProbF
Type1	Source, DF, SS, MS, EMS, ErrorTerm, ErrorDF, FValue, ProbF
Type2	Source, DF, SS, MS, EMS, ErrorTerm, ErrorDF, FValue, ProbF
Type3	Source, DF, SS, MS, EMS, ErrorTerm, ErrorDF, FValue, ProbF
Trans	Prior, TCovP, CovP1–CovP $\text{[math]}$
V	Index, Row, Col1–Col $\text{[math]}$
VCorr	Index, Row, Col1–Col $\text{[math]}$

Some of the variables listed in Table 56.23 are created only when you specify certain options in the relevant PROC MIXED statements.

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