A review of the use of controlled multiple imputation in randomised controlled trials with missing outcome data

Sensitivity analysis for clinical trials with missing continuous outcome data using controlled multiple imputation: A practical guide

(2020) Suzie Cro et al.   STATISTICS IN MEDICINE

Missing Data in Clinical Research: A Tutorial on Multiple Imputation

(2020) Peter C. Austin et al.   CANADIAN JOURNAL OF CARDIOLOGY

Oral semaglutide versus subcutaneous liraglutide and placebo in type 2 diabetes (PIONEER 4): a randomised, double-blind, phase 3a trial

(2019) Richard Pratley et al.   LANCET

Reference‐based sensitivity analysis for time‐to‐event data

(2019) Andrew Atkinson et al.   PHARMACEUTICAL STATISTICS

A mean score method for sensitivity analysis to departures from the missing at random assumption in randomised trials

(2018) Ian White et al.   STATISTICA SINICA

Controlled pattern imputation for sensitivity analysis of longitudinal binary and ordinal outcomes with nonignorable dropout

(2018) Yongqiang Tang   STATISTICS IN MEDICINE

Efficacy and safety of semaglutide compared with liraglutide and placebo for weight loss in patients with obesity: a randomised, double-blind, placebo and active controlled, dose-ranging, phase 2 trial

(2018) Patrick M O'Neil et al.   LANCET

Information-anchored sensitivity analysis: theory and application

(2018) Suzie Cro et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY

Control-based imputation for sensitivity analyses in informative censoring for recurrent event data

(2017) Fei Gao et al.   PHARMACEUTICAL STATISTICS

Sensitivity to censored-at-random assumption in the analysis of time-to-event endpoints

(2016) Ilya Lipkovich et al.   PHARMACEUTICAL STATISTICS

Should multiple imputation be the method of choice for handling missing data in randomized trials?

(2016) Thomas R Sullivan et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

The rise of multiple imputation: a review of the reporting and implementation of the method in medical research

(2015) Panteha Hayati Rezvan et al.   BMC Medical Research Methodology

Sensitivity analyses for partially observed recurrent event data

(2015) Mouna Akacha et al.   PHARMACEUTICAL STATISTICS

Comparison Between Two Controlled Multiple Imputation Methods for Sensitivity Analyses of Time-to-Event Data With Possibly Informative Censoring

(2015) Kaifeng Lu et al.   Statistics in Biopharmaceutical Research

Handling missing data in RCTs; a review of the top medical journals

(2014) Melanie L Bell et al.   BMC Medical Research Methodology

Comment on “Analysis of Longitudinal Trials With Protocol Deviations: A Framework for Relevant, Accessible Assumptions, and Inference via Multiple Imputation,” by Carpenter, Roger, and Kenward

(2014) Shaun R. Seaman et al.   Journal of Biopharmaceutical Statistics

A Multiple Imputation Method for Sensitivity Analyses of Time-to-Event Data with Possibly Informative Censoring

(2014) Yue Zhao et al.   Journal of Biopharmaceutical Statistics

Missing data sensitivity analysis for recurrent event data using controlled imputation

(2014) Oliver N. Keene et al.   PHARMACEUTICAL STATISTICS

Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation

(2014) Dan Jackson et al.   STATISTICS IN MEDICINE

Analysis of Longitudinal Trials with Protocol Deviation: A Framework for Relevant, Accessible Assumptions, and Inference via Multiple Imputation

(2013) James R. Carpenter et al.   Journal of Biopharmaceutical Statistics

An analytic method for the placebo-based pattern-mixture model

(2013) Kaifeng Lu   STATISTICS IN MEDICINE

A Bayesian model for time-to-event data with informative censoring

(2012) N. A. Kaciroti et al.   BIOSTATISTICS

Auxiliary variables in multiple imputation in regression with missing X: a warning against including too many in small sample research

(2012) Jochen Hardt et al.   BMC Medical Research Methodology

The Prevention and Treatment of Missing Data in Clinical Trials

(2012) Roderick J. Little et al.   NEW ENGLAND JOURNAL OF MEDICINE

The use and reporting of multiple imputation in medical research - a review

(2010) A. Mackinnon   JOURNAL OF INTERNAL MEDICINE

A Bayesian proportional hazards regression model with non-ignorably missing time-varying covariates

(2010) Patrick T. Bradshaw et al.   STATISTICS IN MEDICINE

Multiple imputation using chained equations: Issues and guidance for practice

(2010) Ian R. White et al.   STATISTICS IN MEDICINE

Guidance for Developers of Health Research Reporting Guidelines

(2010) David Moher et al.   PLOS MEDICINE