ArticleAmerican journal of epidemiology2011
Propensity score-based sensitivity analysis method for uncontrolled confounding.
Article in American journal of epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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Who cites it
24 citing papers in PubMed.
- Estimated Impact of Pressure to Conceive on Maternal Depression in Lesotho: A Quasi-experimental Propensity Score Matching using DHS Data.Archives of women's mental health · 2026Article
- Depression may not be an independent risk factor for mortality in patients with cardiovascular disease: data from NHANES 2011-2018.Open heart · 2026Article
- Bayesian Sensitivity Analysis for Causal Estimation With Time-Varying Unmeasured Confounding.Statistics in medicine · 2026Article
- Estimating the impact of maternal anemia on low-birth-weight in Sub-Saharan African countries: propensity score matching analysis.BMC pregnancy and childbirth · 2025Article
- Estimated effect of teenage pregnancy on adverse birth outcome in Sub-Saharan African countries: propensity score matching analysis of recent demographic and health survey data.BMC pregnancy and childbirth · 2025Article
- The effect of khat chewing on sexual desire among adults in North East Ethiopia: a propensity score-match analysis.Frontiers in public health · 2025Article
- Enhancing birth weight outcomes through improved antenatal care in West African countries: Evidence from propensity score matching analysis.PLOS global public health · 2025Article
- Associations between oxygenation status and prognosis in sepsis.Critical care (London, England) · 2024Article
- Impact of partner alcohol use on intimate partner violence among reproductive-age women in East Africa Demographic and Health Survey: propensity score matching.BMC public health · 2024Article
- Estimating generalized propensity scores with survey and attrition weighted data.Statistics in medicine · 2024Article
- Estimating the impact of birth interval on under-five mortality in east african countries: a propensity score matching analysis.Archives of public health = Archives belges de sante publique · 2023Article
- Observational
- Early intubation and patient-centered outcomes in septic shock.Critical care (London, England) · 2022Article
- A FLEXIBLE SENSITIVITY ANALYSIS APPROACH FOR UNMEASURED CONFOUNDING WITH MULTIPLE TREATMENTS AND A BINARY OUTCOME WITH APPLICATION TO SEER-MEDICARE LUNG CANCER DATA.The annals of applied statistics · 2022Article
- Training in ERCP: a multifaceted enterprise now more than ever.Endoscopy international open · 2018Article
- Do preoperative depressive symptoms predict quality of life after laparoscopic cholecystectomy: A longitudinal prospective study.PloS one · 2018Article
- Propensity Scores in Pharmacoepidemiology: Beyond the Horizon.Current epidemiology reports · 2017Article
- Can you party your way to better health? A propensity score analysis of block parties and health.Social science & medicine (1982) · 2015Article
- Article
- 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
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The authors developed a sensitivity analysis method to address the issue of uncontrolled confounding in observational studies. In this method, the authors use a 1-dimensional function of the propensity score, which they refer to as the sensitivity function (SF), to quantify the hidden bias due to unmeasured confounders. The propensity score is defined as the conditional probability of being treated given the measured covariates. Then the authors construct SF-corrected inverse-probability-weighted estimators to draw inference on the causal treatment effect. This approach allows analysts to conduct a comprehensive sensitivity analysis in a straightforward manner by varying sensitivity assumptions on both the functional form and the coefficients in the 1-dimensional SF. Furthermore, 1-dimensional continuous functions can be well approximated by low-order polynomial structures (e.g., linear, quadratic). Therefore, even if the imposed SF is practically certain to be incorrect, one can still hope to obtain valuable information on treatment effects by conducting a comprehensive sensitivity analysis using polynomial SFs with varying orders and coefficients. The authors demonstrate the new method by implementing it in an asthma study which evaluates the effect of clinician prescription patterns regarding inhaled corticosteroids for children with persistent asthma on selected clinical outcomes.
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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.