June 2017
Beginner to intermediate
576 pages
15h 22m
English
Now that you have imputed a value for age, you will be able to run models such as linear regression without having to discard missing values.
Let's try a regression with imputation #2.
First, extract impute #2:
impute.2 <- subset(all_imputed_df,.imp=='2')
Next, run the summary() function at the console to insure there are no more NAs:
> summary(impute.2).imp .id Age Gender0: 0 1 : 1 Min. :20.00 M:10001: 0 10 : 1 1st Qu.:23.00 F:10002:2000 100 : 1 Median :28.00 3: 0 1000 : 1 Mean :27.58 4: 0 1001 : 1 3rd Qu.:32.00 5: 0 1002 : 1 Max. :35.00 (Other):1994 EducationRegular High School Diploma :522Bachelor's Degree :323Some College, 1 or More Years, No Degree:2959th Grade to 12th Grade, No Diploma :169 ...