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
| Output Data Sets |
You can use the Output Delivery System to create a SAS data set from any piece of PROC SURVEYPHREG output. See the section ODS Table Names for more information. PROC SURVEYPHREG also provides an output data set to store observation-level statistics, an output data set to store the replicate weights for BRR or jackknife variance estimation, and an output data set to store the jackknife coefficients for jackknife variance estimation.
OUT= Data Set for the OUTPUT statement
The OUTPUT statement can be used to store observation-level statistics, such as the predicted values and their standard errors, the (weighted) number of observation units at risk, martingale residuals, Schoenfeld residuals, score residuals, and deviance residuals. See the section Residuals for details about how these statistics are calculated.
Replicate Weights Output Data Set
If you specify the OUTWEIGHTS= method-option for VARMETHOD=BRR or JACKKNIFE, PROC SURVEYPHREG stores the replicate weights in an output data set. The OUTWEIGHTS= output data set contains all observations that are used in the analysis or all valid observations in the DATA= input data set. See the section Missing Values for details about valid observations.
The OUTWEIGHTS= data set contains the following variables:
all variables in the DATA= input data set
RepWt_1, RepWt_2,
, RepWt_R, which are the replicate weight variables, where R is the total number of replicates in the analysis
Each replicate weight variable contains the replicate weights for the corresponding replicate. Replicate weights equal zero for those observations not included in the replicate.
After the procedure creates replicate weights for a particular input data set and survey design, you can use the OUTWEIGHTS= method-option to store these replicate weights and then use them again in subsequent analyses, either in PROC SURVEYPHREG or in the other survey procedures. You can use a REPWEIGHTS statement to provide replicate weights for the procedure.
Jackknife Coefficients Output Data Set
If you specify the OUTJKCOEFS= method-option for VARMETHOD=JACKKNIFE, PROC SURVEYPHREG stores the jackknife coefficients in an output data set. The OUTJKCOEFS= output data set contains one observation for each replicate. The OUTJKCOEFS= data set contains the following variables:
Replicate, which is the replicate number for the jackknife coefficient
JKCoefficient, which is the jackknife coefficient for the replicate
DonorStratum, which is the stratum of the PSU that was deleted to construct the replicate, if you specify a STRATA statement
After the procedure creates jackknife coefficients for a particular input data set and survey design, you can use the OUTJKCOEFS= method-option to store these coefficients and then use them again in subsequent analyses, either in PROC SURVEYPHREG or in the other survey procedures. You can use the JKCOEFS= option in the REPWEIGHTS statement to provide jackknife coefficients for the procedure.