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The SURVEYREG Procedure

Overview

The SURVEYREG procedure performs regression analysis for sample survey data. This procedure can handle complex survey sample designs, including designs with stratification, clustering, and unequal weighting. The procedure fits linear models for survey data and computes regression coefficients and their variance-covariance matrix. The procedure also provides significance tests for the model effects and for any specified estimable linear functions of the model parameters. Using the regression model, the procedure can compute predicted values for the sample survey data.

PROC SURVEYREG computes the regression coefficient estimators by generalized least squares estimation using element-wise regression. The procedure assumes that the regression coefficients are the same across strata and primary sampling units (PSUs). To estimate the variance-covariance matrix for the regression coefficients, PROC SURVEYREG uses the Taylor expansion theory for estimating sampling errors of estimators based on complex sample designs (Woodruff 1971; Fuller 1975; S{\rm \ddot{a}}rndal, Swenson, and Wretman 1992, Chapter 5 and Chapter 13). This method obtains a linear approximation for the estimator and then uses the variance estimator for this approximation to estimate the variance of the estimator itself.

PROC SURVEYREG uses ODS (Output Delivery System) to place results in output data sets. This is a departure from older SAS procedures that provide OUTPUT statements for similar functionality.

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