dimp is a package that builds on the mice library, allowing users to delete imputed values in a specified outcome variable. It contains one primary function:

• dimp() modify and return a passed in mids object to delete imputed outcome values.

# The easiest way to get dimp is to install the whole package via devtools:
install.packages("devtools")
library(devtools)
devtools::install_github("gmasuncion/dimp")
library(dimp)

library(mice)
library(dimp)

# Create a mids object
exampledata <- airquality
mice_obj <- mice(exampledata, m = 5, maxit = 5, seed = 123)

# Deletion
mice_obj_deleted <- dimp(mice_obj, "Ozone") # datasets in this object have missing outcomes

This package was created by Mark Asuncion, Ting Lin, John Fei, Luke Bai and Jason Dang as part of the group project for CHL 8010 F2: Statistical Programming and Computation for Health Data (Instructor: Dr. Aya Mitani) offered by the Dalla Lana School of Public Health at the University of Toronto (Fall 2024).