Inference in Randomized Controlled Trials with Death and Missingness

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.


News

idem 3.0

  • Added a NEWS.md file to track changes to the package.
  • Reorganized functions with S3 methods implemented for most of the classes
  • Added SACE analysis

Reference manual

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install.packages("idem")

4.0 by Chenguang Wang, a month ago


Browse source code at https://github.com/cran/idem


Authors: Chenguang Wang [aut, cre] , Andrew Leroux [aut, cre] , Elizabeth Colantuoni [aut] , Daniel O Scharfstein [aut] , Trustees of Columbia University [cph] (tools/make_cpp.R , R/stanmodels.R)


Documentation:   PDF Manual  


Task views: Missing Data


GPL (>= 3) license


Imports rstan, rstantools, sqldf, survival, parallel

Depends on Rcpp, methods

Suggests knitr, shiny, rmarkdown, pander, DT, shinythemes

Linking to StanHeaders, rstan, BH, Rcpp, RcppEigen

System requirements: GNU make


See at CRAN