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 65.26.
Table 65.26: ODS Tables Produced by PROC MIXED
Table Name 
Description 
Required Statement / Option 

AccRates 
Acceptance rates for posterior sampling 

AsyCorr 
Asymptotic correlation matrix of 

AsyCov 
Asymptotic covariance matrix of 

Base 
Base densities used for posterior sampling 

Bound 
Computed bound for posterior rejection sampling 

CholG 
Cholesky root of the estimated matrix 
RANDOM / GC 
CholR 
Cholesky root of blocks of the estimated matrix 
REPEATED / RC 
CholV 
Cholesky root of blocks of the estimated matrix 
RANDOM / VC 
ClassLevels 
Level information from the CLASS statement 
Default output 
Coef 
matrix coefficients 

Contrasts 
Results from the CONTRAST


ConvergenceStatus 
Convergence status 
Default 
CorrB 
Approximate correlation matrix of fixedeffects parameter estimates 

CovB 
Approximate covariance matrix of fixedeffects parameter estimates 

CovParms 
Estimated covariance parameters 
Default output 
Diffs 
Differences of LSmeans 

Dimensions 
Dimensions of the model 
Default output 
Estimates 
Results from ESTIMATE statements 

FitStatistics 
Fit statistics 
Default 
G 
Estimated matrix 

GCorr 
Correlation matrix from the 

HLM1 
Type 1 HotellingLawleyMcKeon tests of fixed effects 

HLM2 
Type 2 HotellingLawleyMcKeon tests of fixed effects 

HLM3 
Type 3 HotellingLawleyMcKeon tests of fixed effects 

HLPS1 
Type 1 HotellingLawleyPillai 

HLPS2 
Type 2 HotellingLawleyPillai 

HLPS3 
Type 3 HotellingLawleyPillai 

Influence 
Influence diagnostics 

InfoCrit 
Information criteria 

InvCholG 
Inverse Cholesky root of the 

InvCholR 
Inverse Cholesky root of blocks of the estimated matrix 

InvCholV 
Inverse Cholesky root of blocks of the estimated matrix 

InvCovB 
Inverse of approximate covariance matrix of fixedeffects parameter estimates 

InvG 
Inverse of the estimated 

InvR 
Inverse of blocks of the estimated matrix 

InvV 
Inverse of blocks of the estimated matrix 

IterHistory 
Iteration history 
Default output 
LComponents 
Singledegreeoffreedom estimates that correspond to rows of the matrix for fixed effects 

LRT 
Likelihood ratio test 
Default output 
LSMeans 
LSmeans 

MMEq 
Mixed model equations 

MMEqSol 
Mixed model equations solution 

ModelInfo 
Model information 
Default output 
NObs 
Number of observations read and used 
Default output 
ParmSearch 
Parameter search values 

Posterior 
Posterior sampling information 

Ranks 
Ranks of design matrices and () 

R 
Blocks of the estimated matrix 

RCorr 
Correlation matrix from blocks of the estimated matrix 

Search 
Posterior density search table 

Slices 
Tests of LSmeans slices 

SolutionF 
Fixedeffects solution vector 

SolutionR 
Randomeffects solution vector 

Tests1 
Type 1 tests of fixed effects 

Tests2 
Type 2 tests of fixed effects 

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 

V 
Blocks of the estimated matrix 

VCorr 
Correlation matrix from blocks of the estimated matrix 
In Table 65.26, "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 65.26, 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 OUTP= and OUTPM= 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 65.27 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 65.27, n 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 65.27 and variables in your input data set. You should avoid using input variables with the same names as the variables in these tables.
Table 65.27: Variable Names for the ODS Tables Produced in PROC MIXED
Table Name 
Variables 

AsyCorr 
Row, CovParm, CovP1–CovPn 
AsyCov 
Row, CovParm, CovP1–CovPn 
Base 
Type, Parm1–Parmn 
Bound 
Technique, Converge, Iterations, Evaluations, LogBound, CovP1–CovPn, TCovP1–TCovPn 
CholG 
Model specific, Effect, Subject, Sub1–Subn, Group, Group1–Groupn, Row, Col1–Coln 
CholR 
Index, Row, Col1–Coln 
CholV 
Index, Row, Col1–Coln 
ClassLevels 
Class, Levels, Values 
Coef 
Model specific, LMatrix, Effect, Subject, Sub1–Subn, Group, Group1–Groupn, Row1–Rown 
Contrasts 
Label, NumDF, DenDF, ChiSquare, FValue, ProbChiSq, ProbF 
CorrB 
Model specific, Effect, Row, Col1–Coln 
CovB 
Model specific, Effect, Row, Col1–Coln 
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–Subn, Group, Group1–Groupn, Row, Col1–Coln 
GCorr 
Model specific, Effect, Subject, Sub1–Subn, Group, Group1–Groupn, Row, Col1–Coln 
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–Obsk, Level, Iter, Index, Predicted, Residual, Leverage, PressRes, PRESS, Student, RMSE, RStudent, CookD, DFFITS, MDFFITS, CovRatio, CovTrace, CookDCP, MDFFITSCP, CovRatioCP, CovTraceCP, LD, RLD, Parm1–Parmp, CovP1–CovPq, Notes 
InfoCrit 
Neg2LogLike, Parms, AIC, AICC, HQIC, BIC, CAIC 
InvCholG 
Model specific, Effect, Subject, Sub1–Subn, Group, Group1–Groupn, Row, Col1–Coln 
InvCholR 
Index, Row, Col1–Coln 
InvCholV 
Index, Row, Col1–Coln 
InvCovB 
Model specific, Effect, Row, Col1–Coln 
InvG 
Model specific, Effect, Subject, Sub1–Subn, Group, Group1–Groupn, Row, Col1–Coln 
InvR 
Index, Row, Col1–Coln 
InvV 
Index, Row, Col1–Coln 
IterHistory 
CovP1–CovPn, 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–Covn, Corr1–Corrn 
MMEq 
Model specific, Effect, Subject, Sub1–Subn, Group, Group1–Groupn, Row, Col1–Coln 
MMEqSol 
Model specific, Effect, Subject, Sub1–Subn, Group, Group1–Groupn, Row, Col1–Coln 
ModelInfo 
Descr, Value 
Nobs 
Label, N, NObsRead, NObsUsed, SumFreqsRead, SumFreqsUsed 
ParmSearch 
CovP1–CovPn, Var, ResLogLike, M2ResLogLike2, LogLike, M2LogLike, LogDetH 
Posterior 
Descr, Value 
R 
Index, Row, Col1–Coln 
RCorr 
Index, Row, Col1–Coln 
Search 
Parm, TCovP1–TCovPn, 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–Subn, Group, Group1–Groupn, 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–CovPn 
V 
Index, Row, Col1–Coln 
VCorr 
Index, Row, Col1–Coln 
Some of the variables listed in Table 65.27 are created only when you specify certain options in the relevant PROC MIXED statements.