doi:10.1111/biom.12594> and Wang et al. (2020) <doi:10.18637/jss.v093.i12>. It considers missing data imputation with different sensitivity analysis strategies to handle the unobserved functional outcomes not due to death.">

idem: Inference in Randomized Controlled Trials with Death and Missingness (original) (raw)

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) <doi:10.1111/biom.12594> and Wang et al. (2020) <doi:10.18637/jss.v093.i12>. It considers missing data imputation with different sensitivity analysis strategies to handle the unobserved functional outcomes not due to death.

Version: 5.2
Depends: R (≥ 3.4.0), Rcpp (≥ 0.12.0), methods
Imports: rstan (≥ 2.18.1), RcppParallel (≥ 5.0.1), rstantools (≥ 2.1.1), sqldf (≥ 0.4), survival (≥ 2.38), mice (≥ 3.9.0), parallel (≥ 3.2)
LinkingTo: StanHeaders (≥ 2.18.0), rstan (≥ 2.18.1), BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1)
Suggests: knitr, shiny, rmarkdown, pander, DT, shinythemes
Published: 2023-08-09
DOI: 10.32614/CRAN.package.idem
Author: 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)
Maintainer: Chenguang Wang
License: GPL (≥ 3)
URL: https://github.com/olssol/idem/
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: idem citation info
Materials: NEWS
In views: CausalInference
CRAN checks: idem results

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