PROC SURVEYFREQ provides domain analysis through its multiway table capability. *Domain analysis* refers to the computation of statistics for domains (subpopulations), in addition to the computation of statistics for the
entire study population. Formation of subpopulations can be unrelated to the sample design, and so the domain sample sizes
can actually be random variables. Domain analysis takes this variability into account by using the entire sample to estimate
the variance of domain estimates. Domain analysis is also known as subgroup analysis, subpopulation analysis, and subdomain
analysis. For more information about domain analysis, see Lohr (2010), Cochran (1977), Fuller etÂ al. (1989).

To request domain analysis, you should include the domain variable(s) in your TABLES
statement request. For example, specifying `DOMAIN`

* `A`

* `B`

in a TABLES statement produces separate two-way tables of `A`

by `B`

for each level of `DOMAIN`

. If your domains are formed by more than one variable, you can specify `DomainVariable_1`

* `DomainVariable_2`

* `A`

* `B`

, for example, to obtain two-way tables of `A`

by `B`

for each domain formed by the different combinations of levels for `DomainVariable_1`

and `DomainVariable_2`

. See Example 97.2 for an example of domain analysis.

If you specify `DOMAIN`

* `A`

in a TABLES
statement, the values of the variable `DOMAIN`

form the table rows. The two-way table lists levels of the variable `A`

within each level of the row variable `DOMAIN`

. Specify the ROW
option in the TABLES statement to obtain the row percentages and their standard errors. This provides the one-way distribution
of `A`

for each domain (level of the variable `DOMAIN`

).

Including the domain variables in a TABLES
statement request provides a different analysis from the analysis that you obtain by using a BY
statement; a BY statement provides completely separate analyses of the BY groups. You can use the BY statement to analyze
the data set by subgroups, but it is critical to note that this does *not* produce a valid domain analysis. The BY statement is appropriate only when the number of units in each subgroup is known
with certainty. For example, you can use a BY statement to obtain stratum level estimates when the stratum sample sizes are
fixed. When the subgroup sample size is a random variable, you should include the domain variables in your TABLES statement
request.