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 considers missing data imputation with a sensitivity analysis strategy to handle the unobserved functional outcomes not due to death.
|Depends:||R (≥ 3.2.4)|
|Imports:||sqldf (≥ 0.4), survival (≥ 2.38), parallel (≥ 3.2), coda (≥ 0.18)|
|Suggests:||knitr, shiny, rmarkdown, pander|
|Author:||Chenguang Wang [aut, cre], Andrew Leroux [aut, cre], Elizabeth Colantuoni [aut], Daniel O Scharfstein [aut]|
|Maintainer:||Chenguang Wang <cwang68 at jhmi.edu>|
|License:||GPL (≥ 3)|
|CRAN checks:||idem results|
idem: Inference in Randomized Controlled Trials with Death and Missingness
|Windows binaries:||r-devel: idem_1.0.zip, r-release: idem_1.0.zip, r-oldrel: idem_1.0.zip|
|OS X Mavericks binaries:||r-release: idem_1.0.tgz, r-oldrel: idem_1.0.tgz|
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