PROC MIANALYZE Statement

PROC MIANALYZE < options > ;

Table 10.1: Summary of PROC MIANALYZE Options

Tasks		Options
Specify input data sets
	a COV, CORR, or EST type data set	DATA=
	parameter estimates and covariance matrices	PARMS=, COVB=
	parameter estimates and (X'X)^-1 matrices	PARMS=, XPXI=
Specify statistical analysis
	parameters under the null hypothesis	THETA0=
	level for the confidence interval	ALPHA=
	complete-data degrees of freedom	EDF=
	multivariate inferences	MULT

ALPHA=p

specifies that confidence limits are to be constructed for the parameter estimates with confidence level 100(1-p)%, where 0<p<1. The default is p=0.05.

COVB=SAS-data-set

names an input SAS data set that contains covariance matrices of the parameter estimates from imputed data sets. If you provide a COVB= data set, you must also provide a PARMS= data set.

DATA=SAS-data-set

names a specially structured input SAS data set that contains estimates from imputed data sets. This data set must have a TYPE of EST, COV, or CORR:

if TYPE=EST, the data set contains the parameter estimates and associated covariance matrices.
if TYPE=COV, the data set contains the sample means, sample sizes, and covariance matrices. Each covariance matrix for variables is divided by the sample size n to create the covariance matrix for parameter estimates.
if TYPE=CORR, the data set contains the sample means, sample sizes, standard errors, and correlation matrices. The covariance matrices are computed from the correlation matrices and associated standard errors. Each covariance matrix for variables is divided by the sample size n to create the covariance matrix for parameter estimates.

If you do not specify an input data set with the DATA=, COVB=, or XPXI= option, then the most recently created SAS data set is used as an input DATA= data set.

EDF=number

specifies the complete-data degrees of freedom for the parameter estimates. This is used to compute an adjusted degrees of freedom for each parameter estimate. By default, EDF= $\infty$ and the degrees of freedom for each parameter estimate is not adjusted.

MULT

MULTIVARIATE

requests multivariate inference for the variables.

PARMS=SAS-data-set

names an input SAS data set that contains parameter estimates computed from imputed data sets. If you provide a PARMS= data set, you must also provide a COVB= or XPXI= data set.

THETA0=numbers

MU0=numbers

specifies the parameter values ${{\theta}}_{0}$ under the null hypothesis ${\theta}={{\theta}}_{0}$ in the t tests for location for the variables. If only one number ${{\theta}}_{0}$ is specified, that number is used for all variables. If more than one number is specified, the specified numbers correspond to variables in the VAR statement in the order in which they appear in the VAR statement.

XPXI=SAS-data-set

names an input SAS data set that contains the (X'X)^-1 matrices associated with the parameter estimates computed from imputed data sets. If you provide an XPXI= data set, you must also provide a PARMS= data set. In this case, PROC MIANALYZE reads the standard errors of the estimates from the PARMS= data. The standard errors and (X'X)^-1 matrices are used to derive the covariance matrices.