References | | |
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Technology Components | | |
Note: This list may not be complete. No component, listed or unlisted, may be used outside of
the technology in which it is released. The usage decision for a component is found in the Decision
and Decision Constraints.
BBDESIGN |
BBDESIGN implements the weighted finite population Bayesian Bootstrap approach to generate synthetic populations from complex survey data. The primary goal is to incorporate weighting, clustering, and stratification in a nonparametric approach for generating the non-sampled portion of the population from the posterior predictive distribution, conditional on the observed data and the design information. |
COMBINE |
COMBINE is used for collating information from multiple sources through multiple imputation. |
DESCRIBE |
DESCRIBE estimates the population means, proportions, subgroup differences, contrasts and linear combinations of means and proportions. For complex surveys, the Taylor Series approach is used to obtain variance estimates. |
IMPUTE |
IMPUTE uses a multivariate sequential regression approach for imputing missing values in a data set. |
REGRESS |
REGRESS fits linear, logistic, polytomous, Poisson, Tobit and proportional hazard regression models. The Jackknife Repeated Replication (JRR) approach is used to estimate the sampling variances for complex survey data. The missing values may be imputed while performing the regression analysis. |
SASMOD |
SASMOD allows users to analyze data with several SAS procedures. Currently the following SAS PROCS can be called: CALIS, CATMOD, GENMOD, LIFEREG, MIXED, NLIN, PHREG, and PROBIT. The JRR approach is used for complex survey data and the missing values can be multiply imputed while performing these analyses.
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SYNTHESIZE |
SYNTHESIZE uses multivariate sequential regression approach to create full or partial synthetic data sets to limit statistical disclosure. All item missing values will also be imputed when creating synthetic data sets. However, DESCRIBE, REGRESS and SASMOD modules cannot be used to analyze synthetic data sets as they do not implement the appropriate combining rules. |