Try, try again: Replication-based variance estimation methods for survey data analysis

Complex survey samples are constructed with selection schemes that affect the usual random assumptions, so SAS/STAT ® software provides specialized procedures to analyze them: SURVEYMEANS, SURVEYFREQ, SUR-VEYREG, and SURVEYLOGISTIC for means, frequencies, regression, and logistic analysis, respectively. These pro-cedures all use the Taylor series expansion method for variance estimation, which is usually considered to be the "gold standard " when it is practical to compute. However, replication methods are also widely used in practice for variance estimation. Replication methods, such as the jackknife and balanced repeated replication (BRR), replace complex al-gebra with simple repeated analysis. They enable you to analyze the data without the original sample design, protecting survey security, and they ease the task of estimating variances for nonlinear quantities. With the release of SAS 9.2, the SAS/STAT survey analysis procedures now also implement replication methods. These include standard approaches such as jackknife and BRR as well as customized replication methods that employ user-supplied replicate weights. This paper discusses replication methods, comparing them to the Taylor series expansion method with respect to both technical characteristics and practical utility. This paper also discusses other significant enhancements to the survey design and analysis procedures in SAS 9.2