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.
|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 <firstname.lastname@example.org>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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