TippingPoint: Enhanced Tipping Point Displays the Results of Sensitivity Analyses for Missing Data

Using the idea of "tipping point" (proposed in Gregory Campbell, Gene Pennello and Lilly Yue(2011) <DOI:10.1080/10543406.2011.550094>) to visualize the results of sensitivity analysis for missing data, the package provides a set of functions to list out all the possible combinations of the values of missing data in two treatment arms, calculate corresponding estimated treatment effects and p values and draw a colored heat-map to visualize them. It could deal with randomized experiments with a binary outcome or a continuous outcome. In addition, the package provides a visualized method to compare various imputation methods by adding the rectangles or convex hulls on the basic plot.

Getting started

Package details

AuthorShengjie Zhang <zhangshengjie@mrbc-nccd.com>, Xikun Han <hanxikun2014@163.com> and Victoria Liublinska <vliublin@g.harvard.edu>
MaintainerXikun Han <hanxikun2014@163.com>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the TippingPoint package in your browser

Any scripts or data that you put into this service are public.

TippingPoint documentation built on May 2, 2019, 5:56 a.m.