Survey Data Imputation and Analysis Using SAS® (ADDED FEE) — Professional Development Computer Technology Workshop
ASA, SAS
Survey data commonly contain missing values that result from nonresponse. To provide the same complete data to all the analysts, you impute the missing values by replacing them with reasonable nonmissing values. For example, hot-deck imputation replaces the missing values of a nonrespondent unit with the observed values of a respondent unit. Filling in missing values to reduce nonresponse bias is only part of the imputation task. Analyses of the filled-in data should appropriately account for the imputation. We will show you how to create a set of replicate weights that are adjusted for the imputation. Thus, if you use the imputed data along with the replication variance estimation methods in any of the survey analysis procedures in SAS/STAT, you can be confident that inferences account not only for the survey design but also for the imputation. This workshop will show you how to use the SURVEYIMPUTE procedure to perform traditional cell-based hot-deck imputation as well as modern fully efficient fractional imputation (FEFI), fractional hot-deck imputation (FHDI), and approximate Bayesian bootstrap (ABB) imputation. You will also learn how to analyze data sets that contain imputed values by using the survey analysis procedures.
Instructor(s): Pushpal Mukhopadhyay, SAS Institute Inc.
