Reference Based Multiple Imputation (rbmi) Overviewrbmi is a R package for imputation of missing data in clinical trials with continuous multivariate normal longitudinal outcomes. It supports imputation under a missing at random (MAR) assumption, reference-based imputation methods, and delta ...
Reference based multiple imputation methods have become popular for handling\nmissing data in randomised clinical trials. Rubin's variance estimator is well\nknown to be biased compared to the reference based imputation estimator's true\nrepeated sampling variance. Somewhat surprisingly given the ...
Recent work has shown how such questions can be addressed for trials with continuous outcome data and longitudinal follow┞晄ing reference‐based multiple imputation. For example, patients in the active arm may have their missing data imputed assuming they reverted to the control (ie, reference) ...
MULTIPLE-IMPUTATIONACCESSIBLE ASSUMPTIONSLONGITUDINAL TRIALSSENSITIVITY-ANALYSISReference-based controlled imputations have become a popular tool to assess the sensitivity of primary analysis inference to different post-dropout assumptions and to yield an alternative effectiveness estimand of treatment effect. As ...
33. Because SNPs are the densest type of polymorphism in human genomes, phasing other variants on the basis of these is feasible. Instead of probabilistic imputation, however, Aquila performs straightforward inference by matching the assembly-based SNP calls with those of the Haplotyping module and ...
The Absolute method refers to direct integration of data after preprocessing such as normalization, log2 transformation, missing value filtering and imputation. Ratio Ratio-based scaling refers to converting the quantitative profiles to relative-scale profiles within each batch on a feature-by-feature ba...
Third, MetaNSUE is used to estimate the most likely effect size and its standard error and to create several imputations based on adding noise to these estimations within the bounds. Fourth, each imputed dataset is meta-analyzed and then Rubin's rules are used to combine these imputed meta-...
Reference based multiple imputation (RBMI), which avoids analysts explicitly specifying the parameters of the unobserved data distribution, has proved attractive to researchers. Building on results for longitudinal continuous data, we show that inference using a Tobit regression imputation model for ...
multiple imputationsensitivity analysisRandomized controlled trials provide essential evidence for the evaluation of new and existing medical treatments. Unfortunately, the statistical analysis is often complicated by the occurrence of protocol deviations, which mean we cannot always measure the intended ...
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