Dealing with Missing Test Scores

If we want to use SAT scores as our outcome, we should examine missingness. Examine the pattern of missingness across all the variables in nyc_scores using miss_var_summary() from the naniar package. naniar integrates with Tidyverse code styling, including the pipe operator (%>%).

There are 60 missing scores in each subject. Though there are many R packages which help with more advanced forms of imputation, such as MICE, Amelia, and mi, we will continue to use simputation and impute_median().

Create a new dataset, nyc_scores_2 by imputing Math score by Borough, but note that impute_median() returns the imputed variable as type "impute". You'll convert the variable to the numeric in a separate step.

simputation and dplyr are loaded.