OUTPUT Statement

The GENMOD Procedure

OUTPUT Statement

OUTPUT < OUT=SAS-data-set >
< keyword=name ...keyword=name > / ;

The OUTPUT statement creates a new SAS data set that contains all the variables in the input data set and, optionally, the estimated linear predictors (XBETA) and their standard error estimates, the weights for the Hessian matrix, predicted values of the mean, confidence limits for predicted values, and residuals.

You can also request these statistics with the OBSTATS, PREDICTED, RESIDUALS, CL, or XVARS options in the MODEL statement. You can then create a SAS data set containing them with ODS OUTPUT commands. You may prefer to specify the OUTPUT statement for requesting these statistics since

the OUTPUT statement produces no tabular output
the OUTPUT statement creates a SAS data set more efficiently than ODS. This can be an advantage for large data sets.
you can specify the individual statistics to be included in the SAS data set

If you use the multinomial distribution with one of the cumulative link functions for ordinal data, the data set also contains variables named _ORDER_ and _LEVEL_ that indicate the levels of the ordinal response variable and the values of the variable in the input data set corresponding to the sorted levels. These variables indicate that the predicted value for a given observation is the probability that the response variable is as large as the value of the Value variable.

The estimated linear predictor, its standard error estimate, and the predicted values and their confidence intervals are computed for all observations in which the explanatory variables are all nonmissing, even if the response is missing. By adding observations with missing response values to the input data set, you can compute these statistics for new observations or for settings of the explanatory variables not present in the data without affecting the model fit.

The following list explains specifications in the OUTPUT statement.

OUT= SAS-data-set

specifies the output data set. If you omit the OUT=option, the output data set is created and given a default name using the DATAn convention.

keyword=name

specifies the statistics to be included in the output data set and names the new variables that contain the statistics. Specify a keyword for each desired statistic (see the following list of keywords), an equal sign, and the name of the new variable or variables to contain the statistic. You can list only one variable after the equal sign. Although you can use the OUTPUT statement without any keyword=name specifications, the output data set then contains only the original variables and, possibly, the variables Level and Value (if you use the multinomial model with ordinal data). Note that the residuals are not available for the multinomial model with ordinal data. Formulas for the statistics are given in the section "Predicted Values of the Mean" and the "Residuals" section. The keywords allowed and the statistics they represent are as follows:

HESSWGT: diagonal element of the weight matrix used in computing the Hessian matrix
LOWER | L: lower confidence limit for the predicted value of the mean, or the lower confidence limit for the probability that the response is less than or equal to the value of Level or Value. The confidence coefficient is determined by the ALPHA=number option in the MODEL statement as (1 - number)×100%. The default confidence coefficient is 95%.
PREDICTED | PRED | PROB | P: predicted value of the mean or the predicted probability that the response variable is less than or equal to the value of Level or Value if the multinomial model for ordinal data is used (in other words, Pr $({\rm Y} \le Value)$ , where Y is the response variable)
RESCHI: Pearson (Chi) residual for identifying observations that are poorly accounted for by the model
RESDEV: deviance residual for identifying poorly fitted observations
RESLIK: likelihood residual for identifying poorly fitted observations
STDXBETA: standard error estimate of XBETA (see the XBETA keyword)
STDRESCHI: standardized Pearson (Chi) residual for identifying observations that are poorly accounted for by the model
STDRESDEV: standardized deviance residual for identifying poorly fitted observations
UPPER | U: upper confidence limit for the predicted value of the mean, or the lower confidence limit for the probability that the response is less than or equal to the value of Level or Value. The confidence coefficient is determined by the ALPHA=number option in the MODEL statement as (1 - number)×100%. The default confidence coefficient is 95%.
XBETA: estimate of the linear predictor ${x_{i}}'{{\beta}}$ for observation i, or ${\alpha}_j+{x_{i}}'{{\beta}}$ , where j is the corresponding ordered value of the response variable for the multinomial model with ordinal data. If there is an offset, it is included in ${x_{i}}'{{\beta}}$ .

Chapter Contents
Previous
Next
Top