4.6 Article

The Importance of Making Assumptions in Bias Analysis

Related references

Note: Only part of the references are listed.
Article Statistics & Probability

Flexible Sensitivity Analysis for Observational Studies Without Observable Implications

Alexander M. Franks et al.

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2020)

Article Public, Environmental & Occupational Health

Use of E-values for addressing confounding in observational studies-an empirical assessment of the literature

Manuel R. Blum et al.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2020)

Editorial Material Public, Environmental & Occupational Health

Commentary: Cynical epidemiology

Jay S. Kaufman

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2020)

Editorial Material Public, Environmental & Occupational Health

Commentary: The value of E-values and why they are not enough

Matthew P. Fox et al.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2020)

Editorial Material Public, Environmental & Occupational Health

Commentary: Developing best-practice guidelines for the reporting of E-values

Tyler J. VanderWeele et al.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2020)

Editorial Material Public, Environmental & Occupational Health

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)

Editorial Material Public, Environmental & Occupational Health

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

Charles Poole

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2020)

Letter Public, Environmental & Occupational Health

RE: APPLYING THE E VALUE TO ASSESS THE ROBUSTNESS OF EPIDEMIOLOGIC FIELDS OF INQUIRY TO UNMEASURED CONFOUNDING

Ghassan B. Hamra

AMERICAN JOURNAL OF EPIDEMIOLOGY (2019)

Article Medicine, General & Internal

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

John P. A. Ioannidis et al.

ANNALS OF INTERNAL MEDICINE (2019)

Editorial Material Medicine, General & Internal

Correcting Misinterpretations of the E-Value

Tyler J. VanderWeele et al.

ANNALS OF INTERNAL MEDICINE (2019)

Article Public, Environmental & Occupational Health

Applying the E Value to Assess the Robustness of Epidemiologic Fields of Inquiry to Unmeasured Confounding

Ludovic Trinquart et al.

AMERICAN JOURNAL OF EPIDEMIOLOGY (2019)

Article Mathematics, Interdisciplinary Applications

Technical Considerations in the Use of the E-Value

Tyler J. VanderWeele et al.

JOURNAL OF CAUSAL INFERENCE (2019)

Article Public, Environmental & Occupational Health

The Harm Done to Reproducibility by the Culture of Null Hypothesis Significance Testing

Timothy L. Lash

AMERICAN JOURNAL OF EPIDEMIOLOGY (2017)

Article Medicine, General & Internal

Sensitivity Analysis in Observational Research: Introducing the E-Value

Tyler J. VanderWeele et al.

ANNALS OF INTERNAL MEDICINE (2017)

Article Public, Environmental & Occupational Health

Sensitivity Analysis Without Assumptions

Peng Ding et al.

EPIDEMIOLOGY (2016)

Article Public, Environmental & Occupational Health

Good practices for quantitative bias analysis

Timothy L. Lash et al.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2014)

Article Statistics & Probability

Relaxation Penalties and Priors for Plausible Modeling of Nonidentified Bias Sources

Sander Greenland

STATISTICAL SCIENCE (2009)

Article Public, Environmental & Occupational Health

Bias formulas for external adjustment and sensitivity analysis of unmeasured confounders

Onyebuchi A. Arah et al.

ANNALS OF EPIDEMIOLOGY (2008)

Article Public, Environmental & Occupational Health

Monte Carlo sensitivity analysis and Bayesian analysis of smoking as an unmeasured confounder in a study of silica and lung cancer

K Steenland et al.

AMERICAN JOURNAL OF EPIDEMIOLOGY (2004)

Article Public, Environmental & Occupational Health

Sensitivity analysis, Monte Carlo risk analysis, and Bayesian uncertainty assessment

S Greenland

RISK ANALYSIS (2001)