| idem-package {idem} | R Documentation |
Inference in Randomized Clinical Trials with Death and Missingness
Description
This package contains the functions for drawing inference in randomized clinical trials with death and intermittent missingness.
Notation
Consider a two-arm randomized study. Let Y_k denote outcome measured at
time t_k and Z denote a functional endpoint that is a function of
Y. Let L denote the survival time. Let X denote the
baseline covariates and T denote the treatment assignment.
Ranking
If two subject were both alive at the end of the study, they are ranked based
on functional outcome Z. If at least one subject was dead at the end of
the study, they are ranked based on survival time L.
Treatment effect, \theta is defined as the probability that the outcome
for a random individual randomized to treatment T=0 is less than the
outcome of a random individual randomized to treatment T=1 minus the
probability that the outcome for a random individual randomized to treatment
T=0 is greater than the outcome of a random individual randomized to treatment
T=1.
Missingness
In order to estimate \theta in the presence of missing data, we need to
impute Z for subjects alive at the end of the study with Y_k missing
for some k.
The benchmark assumption we consider for the imputation is the complete case missing value (CCMV) restrictions. We then consider exponential tilting models for introducing sensitivity parameters for evaluating the robustness of the findings with regards to different missing data mechanism assumptions. The models are as follows:
f(Y^{(s)}_{mis} | Y^{(s)}_{obs}, Y_0, X, T,S=s) \propto \exp(
\beta_T Z) f(Y^{(s)}_{mis} | Y^{(s)}_{obs}, Y_0, X, T,S=1)
where S denotes the missingness patterns, S=1 denotes the
completers and \beta_T denotes the sensitivity parameter for arm T.
Graphical user interface (GUI)
This package provides a web-based GUI. See imShiny for
details.
References
Wang C, Scharfstein DO, Colantuoni E, Girard T, Yan Y (2016). Inference in Randomized Trials with Death and Missingness. <DOI:10.1111/biom.12594>
Wang C, Colantuoni E, Leroux A, Scharfstein DO (2020). idem: An R Package for Inferences in Clinical Trials with Death and Missingness. <DOI:10.18637/jss.v093.i12>