The SURVEYPHREG Procedure
- Overview
- Getting Started
-
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
-
Examples
- References
| Specifying the Sample Design |
PROC SURVEYPHREG produces statistics that are based on the sample design used to obtain the survey data. PROC SURVEYPHREG can be used for single-stage or multistage designs, with or without stratification, and with or without unequal weighting. To analyze your survey data with PROC SURVEYPHREG, you need to provide sample design information for the procedure. This information can include design (or variance) strata, clusters, and sampling weights. You provide sample design information with the STRATA, CLUSTER, and WEIGHT statements, and with the RATE= or TOTAL= option in the PROC SURVEYPHREG statement.
If you provide replicate weights for BRR or jackknife variance estimation, you do not need to specify a STRATA or CLUSTER statement. Otherwise, you should specify STRATA and CLUSTER statements whenever your design includes stratification and clustering.
When there are clusters (PSUs) in the sample design, the procedure estimates variance by using the PSUs, as described in the section Variance Estimation. For a multistage sample design, PROC SURVEYPHREG uses only the first stage of the sample design for variance estimation. So, the required input includes only first-stage cluster (PSU) and first-stage stratum identification. You do not need to input design information about any additional stages of sampling.
Stratification
If your sample design is stratified at the first stage of sampling, use the STRATA statement to name the variables that form the strata. The combinations of categories of STRATA variables define the strata in the sample, where strata are nonoverlapping subgroups that were sampled independently. If your sample design has stratification at multiple stages, you should identify only the first-stage strata in the STRATA statement.
If you use a REPWEIGHTS statement to provide replicate weights for BRR or jackknife variance estimation, you do not need to specify a STRATA statement. Otherwise, you should specify a STRATA statement whenever your design includes stratification. If you do not specify a STRATA statement or a REPWEIGHTS statement, then PROC SURVEYPHREG assumes there is no stratification at the first stage. In other words, in this case, the procedure assumes that all observation units are in the same stratum.
Clustering
If your sample design selects clusters at the first stage of sampling, use the CLUSTER statement to name the variables that identify the first-stage clusters, which are also called primary sampling units (PSUs). The combinations of categories of CLUSTER variables define the clusters in the sample. If there is a STRATA statement, clusters are nested within strata. If your sample design has clustering at multiple stages, you should specify only the first-stage clusters (PSUs) in the CLUSTER statement. PROC SURVEYPHREG assumes that each cluster that is defined by the CLUSTER statement variables represents a PSU in the sample.
If you use a REPWEIGHTS statement to provide replicate weights for BRR or jackknife variance estimation, you do not need to specify a CLUSTER statement. Otherwise, you should specify a CLUSTER statement whenever your design includes clustering at the first stage of sampling. If you do not specify a CLUSTER statement, then PROC SURVEYPHREG treats each observation as a PSU.
Weighting
If your sample design includes unequal weighting, use the WEIGHT statement to name the variable that contains the sampling weights. Sampling weights must be positive numbers. If an observation has a weight that is nonpositive or missing, then the procedure omits that observation from the analysis. See the section Missing Values for more information.
If you do not specify a WEIGHT statement but include a REPWEIGHTS statement, PROC SURVEYPHREG uses the average of each observation’s replicate weights as the observation’s weight. If you specify neither a WEIGHT statement nor a REPWEIGHTS statement, PROC SURVEYPHREG assumes all observations have a weight of one.
Population Totals and Sampling Rates
To include a finite population correction (fpc) in Taylor series variance estimation, you can input either the sampling rate or the population total by using the RATE= or TOTAL= option in the PROC SURVEYPHREG statement. You cannot specify both of these options in the same PROC SURVEYPHREG statement. The RATE= and TOTAL= options apply only to Taylor series variance estimation. The procedure does not use a finite population correction for BRR or jackknife variance estimation.
If you do not specify the RATE= or TOTAL= option, the Taylor series variance estimation does not include a finite population correction. For fairly small sampling fractions, this correction is often ignored. See Cochran (1977) and Kish (1965) for more information.
If your design has multiple stages of selection and you are specifying the RATE= option, you should input the first-stage sampling rate, which is the ratio of the number of PSUs in the sample to the total number of PSUs in the study population. If you are specifying the TOTAL= option for a multistage design, you should input the total number of PSUs in the study population.
For a nonstratified sample design, or for a stratified sample design with the same sampling rate or the same population total in all strata, you can use the RATE=value or TOTAL=value option. If your sample design is stratified with different sampling rates or population totals in different strata, use the RATE=SAS-data-set or TOTAL=SAS-data-set option to name a SAS data set that contains the stratum sampling rates or totals. This data set is called a secondary data set, as opposed to the primary data set that you specify with the DATA= option.
The secondary data set must contain all the stratification variables listed in the STRATA statement and all the variables in the BY statement. Furthermore, the BY groups must appear in the same order as in the primary data set. If there are formats associated with the STRATA variables and the BY variables, then the formats must be consistent in the primary and the secondary data sets. If you specify the TOTAL=SAS-data-set option, the secondary data set must have a variable named _TOTAL_ that contains the stratum population totals. If you specify the RATE=SAS-data-set option, the secondary data set must have a variable named _RATE_ that contains the stratum sampling rates. If the secondary data set contains more than one observation for any one stratum, the procedure uses the first value of _TOTAL_ or _RATE_ for that stratum and ignores the rest.
The value in the RATE= option or the values of _RATE_ in the secondary data set must be nonnegative numbers. You can specify value as a number between 0 and 1. Or you can specify value in percentage form as a number between 1 and 100, and PROC SURVEYPHREG converts that number to a proportion. The procedure treats the value 1 as 100% instead of 1%.
If you specify the TOTAL=value option, value must not be less than the sample size. If you provide stratum population totals in a secondary data set, these values must not be less than the corresponding stratum sample sizes.