The SURVEYPHREG Procedure
- Overview
- Getting Started
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Syntax
PROC SURVEYPHREG Statement BY Statement CLASS Statement CLUSTER Statement DOMAIN Statement ESTIMATE Statement FREQ Statement LSMEANS Statement LSMESTIMATE Statement MODEL Statement NLOPTIONS Statement OUTPUT Statement Programming Statements REPWEIGHTS Statement SLICE Statement STORE Statement STRATA Statement TEST Statement WEIGHT Statement -
Details
Notation and Estimation Failure Time Distribution Time and CLASS Variables Usage Partial Likelihood Function for the Cox Model Specifying the Sample Design Missing Values Variance Estimation Domain Analysis Hypothesis Tests, Confidence Intervals, and Residuals Output Data Sets Displayed Output ODS Table Names ODS Graphics
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Examples
- References
| 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 SURVEYPHREG statement. If you do not provide replicate weights for these methods by using a REPWEIGHTS statement, then PROC SURVEYPHREG constructs replicate weights for the analysis. See the sections Balanced Repeated Replication (BRR) Method and Jackknife Method for more information.
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 SURVEYPHREG statement, the procedure uses VARMETHOD=JACKKNIFE by default.
If you specify a REPWEIGHTS statement but do not include a WEIGHT statement, PROC SURVEYPHREG 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. See the section Degrees of Freedom for details.
PROC SURVEYPHREG also use the DF= value in computing the denominator degrees of freedom for the F statistics in Wald type tests and confidence intervals.
- JKCOEFS=jackknife-coefficient-specification
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specifies jackknife coefficients for VARMETHOD=JACKKNIFE. The default value for the jackknife coefficient is
, where 
is the total number of replicates. You can specify an alternative value with one of the following three forms: - JKCOEFS=value
specifies a single jackknife coefficient for all replicates. The coefficient value must be a nonnegative number.
- 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.
- 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 observations in the JKCOEFS= data set should correspond to the replicates that are identified by the REPWEIGHTS variables. Arrange the coefficients or observations in the JKCOEFS= data set 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 Jackknife Method for details about jackknife coefficients.