*Introduction to Survey Sampling and Analysis
Procedures* |

## Survey Data Analysis

The SURVEYMEANS and SURVEYREG procedures perform statistical
analysis for survey data. These analytical procedures take
into account the design used to select the sample. The
sample design can be a complex sample design with
stratification, clustering, and unequal weighting.
You can use the SURVEYMEANS procedure to compute the
following statistics:

- population total estimate and its standard deviation
and corresponding
*t* test
- population mean estimate and its standard error and
corresponding
*t* test
- proportion estimate for a categorical variable and
corresponding
*t* test
- confidence limits for the population
total estimates, the population mean estimates, and
the proportion estimates
- data summary information

PROC SURVEYREG 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.

PROC SURVEYMEANS presently does not perform domain analysis
(subgroup analysis). However, note that you can produce a
domain analysis with PROC SURVEYREG (see
Example 62.7). This capability will be
available in a future release of the SURVEYMEANS procedure.

The SURVEYMEANS and SURVEYREG procedures use the Taylor
expansion method to estimate sampling errors of estimators
based on complex sample designs. This method obtains a
linear approximation for the estimator and then uses the
variance estimate for this approximation to estimate the
variance of the estimate itself (Woodruff 1971, Fuller
1975). When there are clusters, or primary sampling units
(PSUs), in the sample
design, the procedures estimate the variance from the
variation among the PSUs. When the design is stratified,
the procedures pool stratum variance estimates to compute
the overall variance estimate.
For a multistage sample design, the variance estimation
method depends only on the first stage of the sample design.
Thus, the required input includes only first-stage cluster
(PSU) and first-stage stratum identification. You do not
need to input design information about any additional stages
of sampling. This variance estimation method assumes that
the first-stage sampling fraction is small or that the
first-stage sample is drawn with replacement, as it often is
in practice.

For more information on variance estimation for sample
survey data, refer to Lee, Forthoffer, and Lorimor (1989),
Cochran (1977), Kish (1965), Srndal,
Swenson, and Wretman (1992), Wolter (1985), and Hansen,
Hurwitz, and Madow (1953).

In addition to the traditional Taylor expansion method,
other methods for variance estimation for survey data
include balanced repeated replication and jackknife repeated
replication. These methods usually give similar, satisfactory
results (Wolter 1985, Srndal,
Swenson, and Wretman 1992); the SURVEYMEANS and SURVEYREG
procedures currently provide only the Taylor expansion
method.

See Chapter 61, "The SURVEYMEANS Procedure," and Chapter 62, "The SURVEYREG Procedure," for
complete details.

Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.