DOMAIN Statement |
The DOMAIN statement requests analysis for domains (subpopulations) in addition to analysis for the entire study population. The DOMAIN statement names the variables that identify domains, which are called domain variables.
It is common practice to compute statistics for domains. The formation of these domains might be unrelated to the sample design. Therefore, the sample sizes for the domains are random variables. Use a DOMAIN statement to incorporate this variability into the variance estimation.
Note that a DOMAIN statement is different from a BY statement. In a BY statement, you treat the sample sizes as fixed in each subpopulation, and you perform analysis within each BY group independently. See the section Domain Analysis for more details.
Use the DOMAIN statement on the entire data set to perform a domain analysis. Creating a new data set from a single domain and analyzing that with PROC SURVEYMEANS yields inappropriate estimates of variance.
A domain variable can be either character or numeric. The procedure treats domain variables as categorical variables. If a variable appears by itself in a DOMAIN statement, each level of this variable determines a domain in the study population. If two or more variables are joined by asterisks (*), then every possible combination of levels of these variables determines a domain. The procedure performs a descriptive analysis within each domain that is defined by the domain variables.
When determining levels of a DOMAIN variable, an observation with missing values for this DOMAIN variable is excluded, unless you specify the MISSING option. For more information, see the section Missing Values.
The formatted values of the domain variables determine the categorical variable levels. Thus, you can use formats to group values into levels. See the FORMAT procedure in the Base SAS Procedures Guide and the FORMAT statement and SAS formats in SAS Formats and Informats: Reference for more information.
You can specify the following option in the DOMAIN statement after a slash (/):
computes the degrees of freedom by using the number of non-empty strata for an analysis variable in a domain.
In a domain analysis, it is possible that some strata contain no sampling units for a specific domain. Or some strata in the domain might be empty due to missing values. By default, the procedure counts these empty strata when computing the degrees of freedom.
However, if you specify the DFADJ option, the procedure excludes any empty strata when computing the degrees of freedom. Prior to SAS 9.2, the procedure excluded empty strata by default.
See the section Degrees of Freedom for more information. See the section Data and Sample Design Summary for details about valid observations.
The DFADJ option has no effect on categorical variables when you specify the MISSING option, which treats missing values as a valid nonmissing level.