idem-package: Inference in Randomized Clinical Trials with Death and...

In idem: Inference in Randomized Controlled Trials with Death and Missingness

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>

idem documentation built on Aug. 9, 2023, 5:08 p.m.