Accounting for the complex sampling design of NHANES is **critical when
calculating statistical estimates and estimating standard errors** of means, geometric means, percentages and other
statistics. Replication and linearization are two statistical methods that can
be used to properly address these complex design issues. SAS
Survey, SUDAAN, and Stata use linearization for calculating standard errors for a variety of
statistics, such as means, geometric means and percentages.

Currently, SUDAAN offers six options for designating survey design (see SUDAAN manual for more details about the use and implications of all design options). SUDAAN assumes a with replacement (WR) design if the design parameter is omitted.

In the next task, you will be using the **with replacement (WR)** design for
analyzing NHANES data.

** **In order to implement the WR sampling option in
SUDAAN, design variables specifying the first stage of the cluster design and
the sample weight are needed.

For more detailed information and sample code, see "Task 2a: How to Use SUDAAN Code to Specify Sampling Parameters in NHANES."

In SAS, a group of procedures, known as the Survey procedures, produce
estimates from complex sample survey data. These procedures can also produce
variance estimates through linearization (see variance estimation module)
and confidence limits on many estimates. In SAS 9.1 Survey Procedures, Taylor Series
Linearization is the only variance estimation method available. In SAS 9.2 Survey Procedures, Jackknife and Balanced Repeated Replication (BRR) variance estiamation methods are also available. In the SAS Survey procedure, the sample design is not
directly specified in the *proc* statement, as in SUDAAN, but rather, strata and PSU
variables are specified in separate statements. Similarly, SAS Survey procedure
also specifies the *weight* statement. For more detailed information and
sample code, see "Task 2b: How to Use SAS Survey Code to Specify Sampling
Parameters in NHANES."

Taylor Series Linearization, Jackknife, Bootstrap and Balanced Repeated Replication (BRR) variance estimation methods are available in Stata.

A sample weight is assigned to each sample person. It is a measure of the number of people in the population represented by that sample person in NHANES, reflecting the unequal probability of selection, nonresponse adjustment, and adjustment to independent population controls. When unequal selection probability is applied, as in the NHANES 1999-2002 sample, the sample weights are used to produce an unbiased national estimate. More information about sample weights and how they are created can be found in the Weighting module.

The unmasked first stage sampling units are not included in the data
release files. Instead, masked variance units are released. The sample design
variables used in SUDAAN and SAS Survey procedures are masked variance units. **Using these masked
variance units yields variance estimates that closely approximate those obtained
using the unmasked variance units**. See the
Strata and Masked Variances Units section in "Key Concepts About NHANES Survey Design."