Using the idea of "tipping point" (proposed in Gregory Campbell, Gene Pennello and Lilly Yue(2011) ) 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.

Documentation

Manual: TippingPoint.pdf
Vignette: TippingPoint

Maintainer: Xikun Han <hanxikun2014 at 163.com>

Author(s): Shengjie Zhang <zhangshengjie at mrbc-nccd.com>, Xikun Han <hanxikun2014 at 163.com> and Victoria Liublinska <vliublin at g.harvard.edu>

Install package and any missing dependencies by running this line in your R console:

install.packages("TippingPoint")

Depends R (>= 3.0.0)
Imports ggplot2(>=2.0.0), RColorBrewer, bayesSurv, reshape2
Suggests knitr, rmarkdown
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Package TippingPoint
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Version 1.1.0
Published 2016-05-02
License GPL-2
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NeedsCompilation no
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Package source TippingPoint_1.1.0.tar.gz