The SURVEYFREQ Procedure
| REPWEIGHTS Statement |
- REPWEIGHTS variables < / options> ;
The REPWEIGHTS statement names variables that provide replicate weights for BRR or jackknife variance estimation, which you request with the VARMETHOD=BRR or VARMETHOD=JACKKNIFE option in the PROC SURVEYFREQ statement. If you do not provide replicate weights for these methods by using a REPWEIGHTS statement, then PROC SURVEYFREQ constructs replicate weights for the analysis. See the sections Balanced Repeated Replication (BRR) and The Jackknife Method for information about replicate weights.
Each REPWEIGHTS variable should contain the weights for a single replicate, and the number of replicates equals the number of REPWEIGHTS variables. The REPWEIGHTS variables must be numeric, and the variable values must be nonnegative numbers.
If you provide replicate weights with a REPWEIGHTS statement, you do not need to specify a CLUSTER or STRATA statement. If you use a REPWEIGHTS statement and do not specify the VARMETHOD= option in the PROC SURVEYFREQ statement, the procedure uses VARMETHOD=JACKKNIFE by default.
If you specify a REPWEIGHTS statement but do not include a WEIGHT statement, PROC SURVEYFREQ uses the average of each observation’s replicate weights as the observation’s weight.
You can specify the following options in the REPWEIGHTS statement after a slash (/):
- DF=df
-
specifies the degrees of freedom for the analysis. The value of df must be a positive number. By default, the degrees of freedom equals the number of REPWEIGHTS variables. See the section Degrees of Freedom for details.
PROC SURVEYFREQ uses the DF= value in computing confidence limits for proportions, totals, and other statistics. See the section Confidence Limits for Proportions for details. PROC SURVEYFREQ also uses the DF= value in computing the denominator degrees of freedom for the F statistics in the Rao-Scott and Wald chi-square tests. See the sections Rao-Scott Chi-Square Test, Rao-Scott Likelihood Ratio Chi-Square Test, Wald Chi-Square Test, and Wald Log-Linear Chi-Square Test for more information.
- JKCOEFS=value
-
specifies the jackknife coefficient for VARMETHOD=JACKKNIFE. The coefficient value must be a nonnegative number. See the section The Jackknife Method for details about jackknife coefficients.
You can use this option to specify a single value of the jackknife coefficient, which the procedure uses for all replicates. To specify different coefficients for different replicates, use the JKCOEFS=(values) or JKCOEFS=SAS-data-set option.
- JKCOEFS=<(>values<)>
-
specifies jackknife coefficients for VARMETHOD=JACKKNIFE, where each coefficient corresponds to an individual replicate identified by a REPWEIGHTS variable. You can separate values with blanks or commas. The coefficient values must be nonnegative numbers. The number of values must equal the number of replicate weight variables named in the REPWEIGHTS statement. List these values in the same order in which you list the corresponding replicate weight variables in the REPWEIGHTS statement.
See the section The Jackknife Method for details about jackknife coefficients.
To specify different coefficients for different replicates, you can also use the JKCOEFS=SAS-data-set option. To specify a single jackknife coefficient for all replicates, use the JKCOEFS=value option.
- JKCOEFS=SAS-data-set
-
names a SAS data set that contains the jackknife coefficients for VARMETHOD=JACKKNIFE. You provide the jackknife coefficients in the JKCOEFS= data set variable JKCoefficient. Each coefficient value must be a nonnegative number. The coefficients should correspond to the replicates that are identified by the REPWEIGHTS variables. Provide the coefficients as observations in the JKCOEFS= data set and arrange them in the same order in which you list the corresponding replicate weight variables in the REPWEIGHTS statement. The number of observations in the JKCOEFS= data set must not be less than the number of REPWEIGHTS variables.
See the section The Jackknife Method for details about jackknife coefficients.
To specify different coefficients for different replicates, you can also use the JKCOEFS=values option. To specify a single jackknife coefficient for all replicates, use the JKCOEFS=value option.