Sensitivity analysis for the interactive effects of internal bias and publication bias in meta‐analyses

Big little lies: a compendium and simulation of p -hacking strategies

(2023) Angelika M. Stefan et al.   Royal Society Open Science

Are E-values too optimistic or too pessimistic? Both and neither!

(2022) Arvid Sjölander et al.   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

E-values for effect heterogeneity and approximations for causal interaction

(2022) Maya B Mathur et al.   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

Interventions to reduce meat consumption by appealing to animal welfare: Meta-analysis and evidence-based recommendations

(2021) Maya B. Mathur et al.   APPETITE

Methods to Address Confounding and Other Biases in Meta-Analyses: Review and Recommendations

(2021) Maya B. Mathur et al.   Annual Review of Public Health

Multiple-bias Sensitivity Analysis Using Bounds

(2021) Louisa H. Smith et al.   EPIDEMIOLOGY

Assessing treatment effects and publication bias across different specialties in medicine: a meta-epidemiological study

(2021) Simon Schwab et al.   BMJ Open

Meta‐regression methods to characterize evidence strength using meaningful‐effect percentages conditional on study characteristics

(2021) Maya B. Mathur et al.   Research Synthesis Methods

Detecting publication selection bias through excess statistical significance

(2021) T. D. Stanley et al.   Research Synthesis Methods

Are Greenland, Ioannidis and Poole opposed to the Cornfield conditions? A defence of the E-value

(2021) Tyler J VanderWeele   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

Robust Metrics and Sensitivity Analyses for Meta-analyses of Heterogeneous Effects

(2020) Maya B. Mathur et al.   EPIDEMIOLOGY

Association of Type 2 Diabetes With Cancer: A Meta-analysis With Bias Analysis for Unmeasured Confounding in 151 Cohorts Comprising 32 Million People

(2020) Suping Ling et al.   DIABETES CARE

Commentary: An argument against E-values for assessing the plausibility that an association could be explained away by residual confounding

(2020) Sander Greenland   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

Commentary: Continuing the E-value’s post-publication peer review

(2020) Charles Poole   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

Sensitivity analysis for publication bias in meta‐analyses

(2020) Maya B. Mathur et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS

A historical review of publication bias

(2020) Arielle Marks‐Anglin et al.   Research Synthesis Methods

Using Monte Carlo experiments to select meta‐analytic estimators

(2020) Sanghyun Hong et al.   Research Synthesis Methods

Limitations and Misinterpretations of E-Values for Sensitivity Analyses of Observational Studies

(2019) John P.A. Ioannidis et al.   ANNALS OF INTERNAL MEDICINE

Correcting Misinterpretations of the E-Value

(2019) Tyler J. VanderWeele et al.   ANNALS OF INTERNAL MEDICINE

Sensitivity Analysis for Unmeasured Confounding in Meta-Analyses

(2019) Maya B. Mathur et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Bounding bias due to selection

(2019) Louisa H. Smith et al.   EPIDEMIOLOGY

Simple Sensitivity Analysis for Differential Measurement Error

(2019) Tyler J VanderWeele et al.   AMERICAN JOURNAL OF EPIDEMIOLOGY

Physical activity and the risk of liver cancer: a systematic review and meta-analysis of prospective studies and a bias analysis

(2019) Sebastian E Baumeister et al.   JNCI-Journal of the National Cancer Institute

Psychology's Renaissance

(2018) Leif D. Nelson et al.   Annual Review of Psychology

The metawars

(2018) Jop de Vrieze   SCIENCE

New metrics for meta-analyses of heterogeneous effects

(2018) Maya B. Mathur et al.   STATISTICS IN MEDICINE

Screening for Obesity in Children and Adolescents

(2017) et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Statistical Significance and the Dichotomization of Evidence

(2017) Blakeley B. McShane et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Sensitivity Analysis Without Assumptions

(2016) Peng Ding et al.   EPIDEMIOLOGY

ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

(2016) Jonathan AC Sterne et al.   BMJ-British Medical Journal

ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

(2016) Jonathan AC Sterne et al.   BMJ-British Medical Journal

p-Curve and p-Hacking in Observational Research

(2016) Stephan B. Bruns et al.   PLoS One

The Extent and Consequences of P-Hacking in Science

(2015) Megan L. Head et al.   PLOS BIOLOGY

Conducting Meta-Analyses inRwith themetaforPackage

(2015) Wolfgang Viechtbauer   Journal of Statistical Software

Meta-Analysis of Observational Studies with Unmeasured Confounders

(2014) Lawrence C. McCandless  

Publication bias in the social sciences: Unlocking the file drawer

(2014) A. Franco et al.   SCIENCE

Statistical methods for dealing with publication bias in meta-analysis

(2014) Zhi-Chao Jin et al.   STATISTICS IN MEDICINE

Cognitive Impairment Associated With Atrial Fibrillation

(2013) Shadi Kalantarian et al.   ANNALS OF INTERNAL MEDICINE

An estimate of the science-wise false discovery rate and application to the top medical literature

(2013) L. R. Jager et al.   BIOSTATISTICS

Power failure: why small sample size undermines the reliability of neuroscience

(2013) Katherine S. Button et al.   NATURE REVIEWS NEUROSCIENCE

Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias — An Updated Review

(2013) Kerry Dwan et al.   PLoS One

Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data

(2013) Matthieu Resche-Rigon et al.   STATISTICS IN MEDICINE

Severe hypoglycaemia and cardiovascular disease: systematic review and meta-analysis with bias analysis

(2013) A. Goto et al.   BMJ-British Medical Journal

A peculiar prevalence of p values just below .05

(2012) E.J. Masicampo et al.   QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY

Robust variance estimation in meta-regression with dependent effect size estimates

(2010) Larry V. Hedges et al.   Research Synthesis Methods

Assessment of regression-based methods to adjust for publication bias through a comprehensive simulation study

(2009) Santiago G Moreno et al.   BMC Medical Research Methodology

Sensitivity Analysis: Distributional Assumptions and Confounding Assumptions

(2008) Tyler J. VanderWeele   BIOMETRICS

Bias modelling in evidence synthesis

(2008) Rebecca M. Turner et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY