OUTPUT Statement

The NLIN Procedure

OUTPUT Statement

OUTPUT OUT= SAS-data-set keyword=names <, ... ,keyword=names>;

The OUTPUT statement specifies an output data set to contain statistics calculated for each observation. For each statistic, specify the keyword, an equal sign, and a variable name for the statistic in the output data set. All of the names appearing in the OUTPUT statement must be valid SAS names, and none of the new variable names can match a variable already existing in the data set to which PROC NLIN is applied.

If an observation includes a missing value for one of the independent variables, both the predicted value and the residual value are missing for that observation. If the iterations fail to converge, all the values of all the variables named in the OUTPUT statement are missing values.

You can specify the following options in the OUTPUT statement. For a description of computational formulas, see Chapter 3, "Introduction to Regression Procedures."

OUT=SAS data set: specifies the SAS data set to be created by PROC NLIN when an OUTPUT statement is included. The new data set includes all the variables in the data set to which PROC NLIN is applied. Also included are any ID variables specified in the ID statement, plus new variables with names that are specified in the OUTPUT statement.

The following values can be calculated and output to the new data set. However, with METHOD=DUD, the following statistics are not available: H, L95, L95M, STDP, STDR, STUDENT, U95, and U95M. These statistics are all calculated using H, the variable containing the leverage. For METHOD=DUD, the approximate Hessian is not available since no derivatives are specified with this method.
H=name: specifies a variable to contain the leverage, x_i (X'X)^-1 x_i', where $X=\partial{F} / \partial {\beta}$ and x_i is the ith row of X. If you specify the special variable _WEIGHT_, the leverage is w_i x_i(X'WX)^-1 x_i'.
L95M=name: specifies a variable to contain the lower bound of an approximate 95% confidence interval for the expected value (mean). See also the description for the U95M= option, which follows.
L95=name: specifies a variable to contain the lower bound of an approximate 95% confidence interval for an individual prediction. This includes the variance of the error as well as the variance of the parameter estimates. See also the description for the U95= option, which follows.
PARMS=names: specifies variables in the output data set to contain parameter estimates. These can be the same variable names as listed in the PARAMETERS statement; however, you can choose new names for the parameters identified in the sequence from the PARAMETERS statement. Note that, for each of these new variables, the values are the same for every observation in the new data set.
PREDICTED=name
P=name: specifies a variable in the output data set to contain the predicted values of the dependent variable.
RESIDUAL=name
R=name: specifies a variable in the output data set to contain the residuals (actual values minus predicted values).
SSE=name
ESS=name: specifies a variable to include in the new data set. The values for the variable are the residual sums of squares finally determined by the procedure. The values of the variable are the same for every observation in the new data set.
STDI=name: specifies a variable to contain the standard error of the individual predicted value.
STDP=name: specifies a variable to contain the standard error of the mean predicted value.
STDR=name: specifies a variable to contain the standard error of the residual.
STUDENT=name: specifies a variable to contain the studentized residuals, which are residuals divided by their standard errors.
U95M=name: specifies a variable to contain the upper bound of an approximate 95% confidence interval for the expected value (mean). See also the description for the L95M= option.
U95=name: specifies a variable to contain the upper bound of an approximate 95% confidence interval for an individual prediction. See also the description for the L95= option.
WEIGHT=name: specifies a variable in the output data set that contains values of the special variable _WEIGHT_.

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