The SURVEYMEANS Procedure |
DOMAIN Statement |
The DOMAIN statement requests analysis for subpopulations, or domains, 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. In order to incorporate this variability into the variance estimation, you should use a DOMAIN statement.
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 Statistics for more details.
You should 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 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 defined by the domain variables.
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 Language Reference: Dictionary 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 nonempty strata for an analysis variable in a domain.
Given a specific domain, it is possible that there is no sampling unit in the sample falling into a domain for a stratum or there is no valid observations from a stratum in a domain due to missing values. Therefore, a domain might contain empty strata. By default, the procedure counts these empty strata when calculating the degrees of freedom.
However, if you specify the DFADJ option, the procedure makes an adjustment by excluding these empty strata when compute the degrees of freedom. Note that prior to SAS 9.2, the procedure made this adjustment 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.
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