ArticleBiometrical journal. Biometrische Zeitschrift2011
Sensitivity analysis for causal inference using inverse probability weighting.
Article in Biometrical journal. Biometrische Zeitschrift, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- The Inflammatory Potential of the Diet at Midlife Is Associated with Later Healthy Aging in French Adults.The Journal of nutrition · 2018Trial
- Best practices for moving from correlation to causation in ecological research.Nature communications · 2026Review
- Getting to Know Worst-Case Confounders.Observational studies · 2026Article
- Investigating the role of chronic stress and perceived discrimination in racial disparities in incident dementia among U.S. older adults.Social science & medicine (1982) · 2025Article
- Long-Duration Vocational Education's Effects on Individuals' Vocational Identity, Self-Efficacy, and Job Satisfaction.Behavioral sciences (Basel, Switzerland) · 2025Article
- Opinion on "Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare".Frontiers in immunology · 2025Article
- Informative censoring in externally controlled clinical trials: a potential source of bias.ESMO open · 2025Article
- Sensitivity analysis for causality in observational studies for regulatory science.Journal of clinical and translational science · 2023Article
- Intravenous edaravone treatment in ALS and survival: An exploratory, retrospective, administrative claims analysis.EClinicalMedicine · 2022Article
- BOUNDS ON THE CONDITIONAL AND AVERAGE TREATMENT EFFECT WITH UNOBSERVED CONFOUNDING FACTORS.Annals of statistics · 2022Article
- Rationale and Design of the SAFE-PAD Study.Circulation. Cardiovascular quality and outcomes · 2021Observational
- Association of the use of hearing aids with the conversion from mild cognitive impairment to dementia and progression of dementia: A longitudinal retrospective study.Alzheimer's & dementia (New York, N. Y.) · 2021Article
- Statistical sensitivity analysis for the estimation of fetal alcohol spectrum disorders prevalence.Reproductive toxicology (Elmsford, N.Y.) · 2019Article
- Prospective association between adherence to the Mediterranean diet and risk of depressive symptoms in the French SU.VI.MAX cohort.European journal of nutrition · 2018Observational
- The Inflammatory Potential of the Diet Is Associated with Depressive Symptoms in Different Subgroups of the General Population.The Journal of nutrition · 2017Article
- Practice of causal inference with the propensity of being zero or one: assessing the effect of arbitrary cutoffs of propensity scores.Communications for statistical applications and methods · 2016Article
- A comparison of confounding adjustment methods with an application to early life determinants of childhood obesity.Journal of developmental origins of health and disease · 2014Observational
- Dietary quality and 6-year anthropometric changes in a sample of French middle-aged overweight and obese adults.PloS one · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Evaluation of impact of potential uncontrolled confounding is an important component for causal inference based on observational studies. In this article, we introduce a general framework of sensitivity analysis that is based on inverse probability weighting. We propose a general methodology that allows both non-parametric and parametric analyses, which are driven by two parameters that govern the magnitude of the variation of the multiplicative errors of the propensity score and their correlations with the potential outcomes. We also introduce a specific parametric model that offers a mechanistic view on how the uncontrolled confounding may bias the inference through these parameters. Our method can be readily applied to both binary and continuous outcomes and depends on the covariates only through the propensity score that can be estimated by any parametric or non-parametric method. We illustrate our method with two medical data sets.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.