Michael G. Kenward

发表

Analyzing Repeated Measurements while Accounting for Derivative Tracking, Varying Within-subject Variance, and Autocorrelation: The Xtmixediou Command

Kate Tilling, Rachael A. Hughes, Michael G. Kenward, 2016 .

Multiple Imputation of Binary and Ordinal Data

Michael G. Kenward, James R. Carpenter, 2012 .

Missing Data in Clinical Trials - A Practical Guide

Michael G. Kenward, Carpenter, M. Kenward, 2007 .

R code and data for: "A penalized framework for distributed lag non-linear models"

Michael G. Kenward, Fabian Scheipl, Ben Armstrong, 2017 .

Fully Conditional Specification

Geert Molenberghs, Michael G. Kenward, Anastasios A. Tsiatis, 2014 .

Fast, closed-form, and efficient estimators for hierarchical models with AR(1) covariance and unequal cluster sizes

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2018, Commun. Stat. Simul. Comput..

Nonrandom Missingness in Categorical Data: Strengt hs and Limitations

Michael G. Kenward, Geert Molenberghs, Stuart R. Lipsitz, 1999 .

The nature of sensitivity in monotone missing not at random models

Geert Molenberghs, Michael G. Kenward, Niel Hens, 2006, Comput. Stat. Data Anal..

MCMC-based estimation methods for continuous longitudinal data with non-random (non)-monotone missingness

Geert Molenberghs, Michael G. Kenward, Caroline Beunckens, 2011, Comput. Stat. Data Anal..

Robust inference using hierarchical likelihood approach for heavy-tailed longitudinal outcomes with missing data: An alternative to inverse probability weighted generalized estimating equations

Michael G. Kenward, Youngjo Lee, Myunghee Cho Paik, 2013, Comput. Stat. Data Anal..

Survival Data, Skips and Large Datasets

Michael G. Kenward, James R. Carpenter, 2012 .

Semi-parametric marginal models for hierarchical data and their corresponding full models

Geert Molenberghs, Michael G. Kenward, M. Kenward, 2010, Comput. Stat. Data Anal..

Sensitivity analysis with multiple imputation

Michael G. Kenward, Carpenter, Carpenter, 2016 .

Information‐anchored sensitivity analysis: theory and application

Michael G. Kenward, James R. Carpenter, Suzie Cro, 2018, Journal of the Royal Statistical Society. Series A,.

Analysis of incomplete data

Geert Verbeke, Michael G. Kenward, Kristel Van Steen, 2005 .

Multiple Imputation and its Application

Michael G. Kenward, James R. Carpenter, M. Kenward, 2013 .

Analysis of Categorical Data

Michael G. Kenward, Byron Jones, 2003 .

Missing not at random models and their missing at random counterparts, in various modelling frameworks

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2008 .

Comments on: Missing data methods in longitudinal studies: a review

Michael G. Kenward, James R. Carpenter, 2009 .

Multiple Imputation of Unordered Categorical Data

Michael G. Kenward, James R. Carpenter, M. Kenward, 2012 .

Performance of parametric survival models under non-random interval censoring: A simulation study

Michael G. Kenward, Nikos Pantazis, Giota Touloumi, 2013, Comput. Stat. Data Anal..

Likelihood and Bayesian Methods: Introduction and Overview

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2014 .

Bayesian models for weighted data with missing values: a bootstrap approach

Harvey Goldstein, Michael G. Kenward, James R. Carpenter, 2018 .

Sensitivity Analysis: Introduction and Overview

Geert Molenberghs, Michael G. Kenward, Geert Verbeke, 2014 .

REALCOM-IMPUTE Software for Multilevel Multiple Imputation with Mixed Response Types

Harvey Goldstein, Michael G. Kenward, James R. Carpenter, 2011 .

Shared-parameter models and missingness at random

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2008 .

The handling of missing data in clinical trials

Michael G. Kenward, M. Kenward, 2013 .

Controlled multiple imputation methods for sensitivity analyses in longitudinal clinical trials with dropout and protocol deviation

Michael G. Kenward, M. Kenward, 2015 .

Multiple-bias modelling for analysis of observational data - Discussion

David J. Spiegelhalter, Donald B. Rubin, Andrew E. Gelman, 2005 .

EVERY MISSING NOT AT RANDOM MODEL HAS GOT A MISSING AT RANDOM COUNTERPART WITH EQUAL FIT

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2008 .

Case study: Conditional power

Michael G. Kenward, Byron Jones, 2014 .

Likelihood‐Based Frequentist Inference

Geert Molenberghs, Michael G. Kenward, M. Kenward, 2007 .

Dataset for: Meta-analysis of quantitative individual patient data: two stage or not two stage?

Wiley Admin, Michael G. Kenward, Tim P. Morris, 2018 .

Sensitivity analysis for modeling incomplete data

Geert Molenberghs, Els Goetghebeur, Michael G. Kenward, 1998 .

Incomplete Data and SAS

Geert Molenberghs, Michael G. Kenward, 2007 .

Missing data methodology: Introduction and preliminaries

Geert Verbeke, Michael G. Kenward, Anastasios A. Tsiatis, 2015 .

Sensitivity Analysis: MI Unleashed

Michael G. Kenward, James R. Carpenter, 2012 .

PSEUDO-LIKELIHOOD ESTIMATION FOR INCOMPLETE DATA

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2011 .

Handling missing values in cost effectiveness analyses that use data from cluster randomized trials

Michael G. Kenward, Karla Diaz-Ordaz, Richard Grieve, 2012, 1206.6070.

Clusters with random size: maximum likelihood versus weighted estimation

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2018 .

SAS code for assessing ABE, IBE and PBE in replicate cross-over trials

Michael G. Kenward, Byron Jones, 2003 .

Sensitivity analysis: A likelihood-based perspective

Geert Molenberghs, Michael G. Kenward, Geert Verbeke, 2015 .

Missing data mechanisms and pattern-mixture models

Peter J. Diggle, Geert Molenberghs, Michael G. Kenward, 1998 .

Informative dropout in longitudinal data analysis.

Peter J. Diggle, Michael G. Kenward, M. Kenward, 1994 .

Doubly robust pseudo-likelihood for incomplete hierarchical binary data

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2020 .

Sense and sensitivity when intended data are missing.

Geert Molenberghs, Els Goetghebeur, Michael G. Kenward, 1999 .

An improved approximation to the precision of fixed effects from restricted maximum likelihood

Michael G. Kenward, James H. Roger, M. Kenward, 2009, Comput. Stat. Data Anal..

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

Michael G. Kenward, Andrew Atkinson, James R. Carpenter, 2019, Pharmaceutical statistics.

The Vorozole Study

Geert Molenberghs, Michael G. Kenward, 2007 .

A sensitivity analysis for informative dropout: a local influence approach

Geert Verbeke, Michael G. Kenward, Herbert Thijs, 1998 .

Discussion of two important missing data issues

Michael G. Kenward, Raymond J. Carroll, Jason Roy, 2004 .

R code for: "Distributed lag non-linear models"

Michael G. Kenward, Antonio Gasparrini, Ben Armstrong, 2017 .

A method for increasing the robustness of multiple imputation

Michael G. Kenward, Rhian M. Daniel, M. Kenward, 2012, Comput. Stat. Data Anal..

Statistical Modelling of Partially Observed Data Using Multiple Imputation: Principles and Practice

Harvey Goldstein, Michael G. Kenward, James R. Carpenter, 2012 .

How meaningful and sensitive are selection models and pattern-mixtures models?

Geert Verbeke, Michael G. Kenward, Herbert Thijs, 2002 .

Design and Analysis of Cross-Over Trials, Second Edition

Michael G. Kenward, Byron Jones, M. Kenward, 2003 .

Sensitivity analysis for incomplete data

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2008 .

Faculty Opinions recommendation of Comment: Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data.

Michael G. Kenward, Rhian Daniel, M. Kenward, 2008 .

Analysis of Continuous Data

Michael G. Kenward, Byron Jones, 2003 .

Sensitivity Analysis of Continuous Incomplete Longitudinal Outcomes

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2003 .

Clusters with unequal size: maximum likelihood versus weighted estimation in large samples

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2018 .

The Effective Sample Size and an Alternative Small-Sample Degrees-of-Freedom Method

Geert Molenberghs, Geert Verbeke, Christel Faes, 2009 .

Pseudo-Likelihood for Combined Selection and Pattern-Mixture Models for Incomplete Data

Geert Molenberghs, Michael G. Kenward, Bart Michiels, 1998 .

Multiple Imputation and its Application: Carpenter/Multiple Imputation and its Application

Michael G. Kenward, James R. Carpenter, M. Kenward, 2013 .

Validation of surrogate markers in multiple randomized clinical trials with repeated measurements: canonical correlation approach.

Geert Molenberghs, Michael G. Kenward, Helena Geys, 2004 .

Missing data in randomised controlled trials: a practical guide

Michael G. Kenward, M. Kenward, J. Carpenter, 2007 .

Ignorance and uncertainty regions as inferential tools in a sensitivity analysis

Geert Molenberghs, Els Goetghebeur, Michael G. Kenward, 2006 .

Likelihood Based Frequentist Inference When Data Are Missing at Random

Geert Molenberghs, Michael G. Kenward, M. Kenward, 1998 .

Influence analysis to assess sensitivity of the dropout process

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2001 .

Generalized shared-parameter models and missingness at random

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2011 .

Mastitis in diary cattle: local influence to assess sensitivity of the dropout process

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2001 .

Conceptual Considerations regarding Endpoints, Hypotheses, and Analyses for Incomplete Longitudinal Clinical Trial Data

Michael G. Kenward, Craig H. Mallinckrodt, M. Kenward, 2009 .

Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation by Ming T. Tan, Guo‐Liang Tian, Kai Wang Ng

Michael G. Kenward, 2010 .

Discussion of Likelihood Inference for Models with Unobservables: Another View

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2009 .

Flexible modelling of the covariance matrix in a linear random effects model

Geert Verbeke, Michael G. Kenward, Emmanuel Lesaffre, 2000 .

Monotone missing data and pattern‐mixture models

Geert Molenberghs, Peter J. Diggle, Michael G. Kenward, 1998 .

Sensitivity analysis for incomplete categorical data

Geert Molenberghs, Els Goetghebeur, Michael G. Kenward, 2001 .

A Log‐Linear Model for Binary Cross‐Over Data

Michael G. Kenward, Byron Jones, M. Kenward, 1987 .

Design and Analysis of Cross-Over Trails.

Michael G. Kenward, Byron Jones, Byron William Brown, 1991 .

Missing Data in Clinical Studies

Geert Molenberghs, Michael G. Kenward, M. Kenward, 2007 .

A Method for Comparing Profiles of Repeated Measurements

Michael G. Kenward, M. Kenward, 1987 .

Pattern‐mixture models with proper time dependence

Geert Molenberghs, Michael G. Kenward, M. Kenward, 2003 .

Using Hierarchical Likelihood for Missing Data Problems

Michael G. Kenward, Youngjo Lee, M. Kenward, 2007 .

Sensitivity analysis for incomplete contingency tables: the Slovenian plebiscite case

Geert Molenberghs, Els Goetghebeur, Michael G. Kenward, 2001 .

Shared‐Parameter Models

Geert Molenberghs, Michael G. Kenward, M. Kenward, 2007 .

A Tutorial on the Practical Use and Implication of Complete Sufficient Statistics

Geert Molenberghs, Geert Verbeke, Michael G. Kenward, 2018 .

The Direct Likelihood Method

Geert Molenberghs, Michael G. Kenward, 2007 .