Concentrating on the needs of those relatively new to the use of multiple imputation tools in SAS, this course provides a general introduction to using the MI and MIANALYZE procedures for multiple imputation and subsequent analyses with imputed data sets.
Skills Gained
- recognize the type of missing data patterns that exist in your data sets
- analyze imputed data sets using standard SAS procedures
- use PROC MIANALYZE to correctly analyze output from imputed files and subsequent procedure output from standard SAS procedures
- use real-world data sets in the virtual lab to obtain experience running SAS imputation procedures.
Who Can Benefit
- Analysts, data managers, and other data professionals working with data sets with missing data
Prerequisites
- Before attending this course, you should
- have a solid understanding of the SAS DATA step, which can be gained by attending the SAS(R) Programming I: Essentials course or the SAS(R) Programming II: Manipulating Data with the DATA Step course, or have equivalent experience
- have an intermediate knowledge of statistics, which can be gained by attending either the Statistics I: Introduction to ANOVA, Regression, and Logistic Regression course or the Statistics II: ANOVA and Regression course, or have equivalent academic training.