Lab 8:  Missing Data Analysis Using Multiple Imputation

Data are on the Virtual RDC at /space/courses/info747/lab8.

From the 2000 PUMS for Alaska (a small state to save time and space), using the sample data creation programs (01.pums2000.sas) and the data selector example (02.pums2000-missing.sas)

1. Keep the person records for all the in-scope employed individuals.
2. Select wage and salary income and recoded education (from 02.pums2000-missing.sas) and up to five other relevant variables.
3. Replace the allocated wage and salary income and recoded education with multiply-imputed values (build 5 implicates).
4. Assess the effect of missing data on the precision of estimating the mean earnings of high school graduates.