Related references
Note: Only part of the references are listed.How to report E-values for meta-analyses: Recommended improvements and additions to the new GRADE approach
Maya B. Mathur et al.
ENVIRONMENT INTERNATIONAL (2022)
Are Greenland, Ioannidis and Poole opposed to the Cornfield conditions? A defence of the E-value
Tyler J. VanderWeele
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2022)
Are E-values too optimistic or too pessimistic? Both and neither
Arvid Sjolander et al.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2022)
E-values for effect heterogeneity and approximations for causal interaction
Maya B. Mathur et al.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2022)
Graphical Models for Processing Missing Data
Karthika Mohan et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2021)
Missing data: A statistical framework for practice
James R. Carpenter et al.
BIOMETRICAL JOURNAL (2021)
Conducting sensitivity analysis for unmeasured confounding in observational studies using E-values: The evalue package
Ariel Linden et al.
STATA JOURNAL (2020)
Commentary: Developing best-practice guidelines for the reporting of E-values
Tyler J. VanderWeele et al.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2020)
Commentary: An argument against E-values for assessing the plausibility that an association could be explained away by residual confounding
Sander Greenland
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2020)
Commentary: Continuing the E-value's post-publication peer review
Charles Poole
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2020)
Assessing the impact of unmeasured confounders for credible and reliable real-world evidence
Xiang Zhang et al.
PHARMACOEPIDEMIOLOGY AND DRUG SAFETY (2020)
Selection Mechanisms and Their Consequences: Understanding and Addressing Selection Bias
Louisa H. Smith
CURRENT EPIDEMIOLOGY REPORTS (2020)
Accounting for missing data in statistical analyses: multiple imputation is not always the answer
Rachael A. Hughes et al.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2019)
Bounding Bias Due to Selection
Louisa H. Smith et al.
EPIDEMIOLOGY (2019)
Mediational E-values Approximate Sensitivity Analysis for Unmeasured Mediator-Outcome Confounding
Louisa H. Smith et al.
EPIDEMIOLOGY (2019)
Limitations and Misinterpretations of E-Values for Sensitivity Analyses of Observational Studies
John P. A. Ioannidis et al.
ANNALS OF INTERNAL MEDICINE (2019)
Correcting Misinterpretations of the E-Value
Tyler J. VanderWeele et al.
ANNALS OF INTERNAL MEDICINE (2019)
Web Site and R Package for Computing E-values
Maya B. Mathur et al.
EPIDEMIOLOGY (2018)
Sensitivity Analysis in Observational Research: Introducing the E-Value
Tyler J. VanderWeele et al.
ANNALS OF INTERNAL MEDICINE (2017)
Sensitivity Analysis Without Assumptions
Peng Ding et al.
EPIDEMIOLOGY (2016)
Handling missing data in RCTs; a review of the top medical journals
Melanie L. Bell et al.
BMC MEDICAL RESEARCH METHODOLOGY (2014)
Missing Data A Systematic Review of How They Are Reported and Handled
Iris Eekhout et al.
EPIDEMIOLOGY (2012)
Using causal diagrams to guide analysis in missing data problems
Rhian M. Daniel et al.
STATISTICAL METHODS IN MEDICAL RESEARCH (2012)
Strategy for intention to treat analysis in randomised trials with missing outcome data
Ian R. White et al.
BMJ-BRITISH MEDICAL JOURNAL (2011)
Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values
Ian R. White et al.
STATISTICS IN MEDICINE (2010)
A Randomized, Controlled Trial of Financial Incentives for Smoking Cessation
Kevin G. Volpp et al.
NEW ENGLAND JOURNAL OF MEDICINE (2009)
Inverse probability weighted estimation for general missing data problems
Jeffrey M. Wooldridge
JOURNAL OF ECONOMETRICS (2007)
A structural approach to selection bias
MA Hernán et al.
EPIDEMIOLOGY (2004)