Table 25.2 summarizes the statements and options used with the MDC procedure.
Table 25.2: MDC Functional Summary
|
Description |
Statement |
Option |
|---|---|---|
|
Data Set Options |
||
|
Formats the data for use by PROC MDC |
MDCDATA |
|
|
Specifies the input data set |
MDC |
DATA= |
|
Specifies the output data set for CLASS STATEMENT |
CLASS |
OUT = |
|
Writes parameter estimates to an output data set |
MDC |
OUTEST= |
|
Includes covariances in the OUTEST= data set |
MDC |
COVOUT |
|
Writes linear predictors and predicted probabilities to an output data set |
OUTPUT |
OUT= |
|
Declaring the Role of Variables |
||
|
Specifies the ID variable |
ID |
|
|
Specifies BY-group processing variables |
BY |
|
|
Printing Control Options |
||
|
Requests all printing options |
MODEL |
ALL |
|
Displays correlation matrix of the estimates |
MODEL |
CORRB |
|
Displays covariance matrix of the estimates |
MODEL |
COVB |
|
Displays detailed information about optimization iterations |
MODEL |
ITPRINT |
|
Suppresses all displayed output |
MODEL |
NOPRINT |
|
Model Estimation Options |
||
|
Specifies the choice variables |
MODEL |
CHOICE=() |
|
Specifies the convergence criterion |
MODEL |
CONVERGE= |
|
Specifies the type of covariance matrix |
MODEL |
COVEST= |
|
Specifies the starting point of the Halton sequence |
MODEL |
HALTONSTART= |
|
Specifies options specific to the HEV model |
MODEL |
HEV=() |
|
Sets the initial values of parameters used by the iterative optimization algorithm |
MODEL |
INITIAL=() |
|
Specifies the maximum number of iterations |
MODEL |
MAXITER= |
|
Specifies the options specific to mixed logit |
MODEL |
MIXED=() |
|
Specifies the number of choices for each person |
MODEL |
NCHOICE= |
|
Specifies the number of simulations |
MODEL |
NSIMUL= |
|
Specifies the optimization technique |
MODEL |
OPTMETHOD= |
|
Specifies the type of random number generators |
MODEL |
RANDNUM= |
|
Specifies that initial values are generated using random numbers |
MODEL |
RANDINIT |
|
Specifies the rank dependent variable |
MODEL |
RANK |
|
Specifies optimization restart options |
MODEL |
RESTART=() |
|
Specifies a restriction on inclusive parameters |
MODEL |
SAMESCALE |
|
Specifies a seed for pseudo-random number generation |
MODEL |
SEED= |
|
Specifies a stated preference data restriction on inclusive parameters |
MODEL |
SPSCALE |
|
Specifies the type of the model |
MODEL |
TYPE= |
|
Specifies normalization restrictions on multinomial probit error variances |
MODEL |
UNITVARIANCE=() |
|
Controlling the Optimization Process |
||
|
Specifies upper and lower bounds for the parameter estimates |
BOUNDS |
|
|
Specifies linear restrictions on the parameter estimates |
RESTRICT |
|
|
Specifies nonlinear optimization options |
NLOPTIONS |
|
|
Nested Logit Related Options |
||
|
Specifies the tree structure |
NEST |
LEVEL()= |
|
Specifies the type of utility function |
UTILITY |
U()= |
|
Output Control Options |
||
|
Outputs predicted probabilities |
OUTPUT |
P= |
|
outputs estimated linear predictor |
OUTPUT |
XBETA= |
|
Test Request Options |
||
|
Requests Wald, Lagrange multiplier, and likelihood ratio tests |
TEST |
ALL |
|
Requests the Wald test |
TEST |
WALD |
|
Requests the Lagrange multiplier test |
TEST |
LM |
|
Requests the likelihood ratio test |
TEST |
LR |