REPWEIGHTS variables < / options> ;
The REPWEIGHTS statement names variables that provide replicate weights for BRR or jackknife variance estimation, which you
can request by specifying 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 equal the number of REPWEIGHTS variables. For more information,
see the section Degrees of Freedom.
PROC SURVEYFREQ uses the value df to obtain the t-percentile for confidence limits for proportions, totals, and other statistics. For more information, see the section Confidence Limits for Proportions. PROC SURVEYFREQ also uses df to compute the denominator degrees of freedom for the F statistics in the Rao-Scott and Wald chi-square tests. For more information, 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.
-
JKCOEFS=value
JKCOEFS=(values)
JKCOEFS=SAS-data-set
-
specifies the jackknife coefficients for jackknife variance estimation (which you can request by specifying VARMETHOD=JACKKNIFE). You can provide a single jackknife coefficient value to use for all replicates, or you can provide a value for each replicate by specifying a list of values or a SAS-data-set. The jackknife coefficient values must be nonnegative numbers. For more information, see the section The Jackknife Method.
You can provide jackknife coefficients by specifying one of the following forms:
-
value
-
specifies a single jackknife coefficient value to use for all replicates. The coefficient value must be a nonnegative number.
-
(values)
-
specifies a list of jackknife coefficient values, where each value corresponds to a single replicate that is identified by a REPWEIGHTS variable. You can separate the values
with blanks or commas. The coefficient values must be nonnegative numbers. The number of coefficient values should equal the
number of replicate weight variables that you specify in the REPWEIGHTS statement.
You should list the jackknife coefficient values in the same order in which you list the corresponding replicate weight variables
in the REPWEIGHTS statement.
-
SAS-data-set
-
names a SAS-data-set that contains the jackknife coefficients. You should provide the jackknife coefficients in the data set variable named JKCoefficient. Each coefficient value must be a nonnegative number. Each observation in this data set should correspond to a replicate
that is identified by a REPWEIGHTS variable. The number of observations in this data set must not be less than the number
of REPWEIGHTS variables.
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