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idem (version 2.2)

Inference in Randomized Controlled Trials with Death and Missingness

Description

In randomized studies involving severely ill patients, functional outcomes are often unobserved due to missed clinic visits, premature withdrawal or death. It is well known that if these unobserved functional outcomes are not handled properly, biased treatment comparisons can be produced. In this package, we implement a procedure for comparing treatments that is based on the composite endpoint of both the functional outcome and survival. The procedure was proposed in Wang et al. (2016) . It considers missing data imputation with a sensitivity analysis strategy to handle the unobserved functional outcomes not due to death.

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Version

Install

install.packages('idem')

Monthly Downloads

299

Version

2.2

License

GPL (>= 3)

Maintainer

Chenguang Wang

Last Published

June 30th, 2017

Functions in idem (2.2)

imChkPars

Check parameter specification
imEstimate

Treatment effect estimation
idem-parameters

List of parameters for idem analysis
imBs

Boostrap analysis
abc

Example dataset
idem-package

Inference in Randomized Clinical Trials with Death and Missingness
imFitModel

Model fitting
imImpAll

Impute missing data
imImpSingle

Impute missing data under benchmark assumption
imMisTable

Generate table of missingness pattern frequencies
imPlotSurv

Plot survival curves
imShiny

Run Web-Based idem application
imTest

Hypothesis testing
imPlotImputed

Plot density of imputed values
imPlotMisPattern

Plot missing patterns
imPlotComposite

Cumulative Plot
imPlotContour

Contour plot of the sensitivity analysis results
imNeedImp

Get subjects that need imputation
imPlotCompleters

Plot data of completer