ReviewEpidemiologic reviews2022
Monte Carlo Simulation Approaches for Quantitative Bias Analysis: A Tutorial.
Review in Epidemiologic reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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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
23 citing papers in PubMed.
- Statistical Behavior of the Rank-order and Tiering Metric of the 2020 Centers for Medicare and Medicaid Services Organ Procurement Organization Rule.Transplantation direct · 2026Article
- Exploring the association between higher education and steeper cognitive decline in a nationally representative longitudinal study in India.American journal of epidemiology · 2026Article
- Substituting blood-based biomarkers for imaging measures in Alzheimer's disease studies: implications for sample size and bias.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- Seasonal changes in health risks due to exposure to MTBE among workers of a refinery.Scientific reports · 2026Article
- Transcriptional Heterogeneity Reveals a Synaptic Gene Program in Developing and Adult Human Oligodendrocyte Precursor Cells.bioRxiv : the preprint server for biology · 2026Article
- Foster Care and Child Maltreatment Mortality Rates in the US.JAMA network open · 2025Article
- Substituting Blood-Based Biomarkers for Imaging Measures in Alzheimer's Disease Studies: Implications for Sample Size and Bias.medRxiv : the preprint server for health sciences · 2025Article
- Transportability of nonlocal real-world evidence and its relevance to health technology assessment: a primer.Journal of comparative effectiveness research · 2025Review
- Evidence triangulation in health research.European journal of epidemiology · 2025Article
- Early age-related changes to articular cartilage TOsteoarthritis and cartilage open · 2025Article
- Collider stratification bias II: magnitude of bias.American journal of epidemiology · 2025Article
- Could differential underreporting of loneliness between men and women bias the gender-specific association between loneliness duration and rate of memory decline? A probabilistic bias analysis of effect modification.American journal of epidemiology · 2025Article
- Data-driven simulations to assess the impact of study imperfections in time-to-event analyses.American journal of epidemiology · 2025Article
- Using Quantitative Bias Analysis to Adjust for Misclassification of COVID-19 Outcomes: An Applied Example of Inhaled Corticosteroids and COVID-19 Outcomes.Pharmacoepidemiology and drug safety · 2025Article
- A Comparison of Green, Delta, and Monte Carlo Methods to Select an Optimal Approach for Calculating the 95% Confidence Interval of the Population-attributable Fraction: Guidance for Epidemiological Research.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2024Article
- Guidance of development, validation, and evaluation of algorithms for populating health status in observational studies of routinely collected data (DEVELOP-RCD).Military Medical Research · 2024Article
- Article
- Association between Empirical Anti-Pseudomonal Antibiotics and Progression to Thoracic Surgery and Death in Empyema: Database Research.Antibiotics (Basel, Switzerland) · 2024Article
- INSCYD physiological performance software is valid to determine the maximal lactate steady state in male and female cyclists.Frontiers in sports and active living · 2024Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Quantitative bias analysis can be used to empirically assess how far study estimates are from the truth (i.e., an estimate that is free of bias). These methods can be used to explore the potential impact of confounding bias, selection bias (collider stratification bias), and information bias. Quantitative bias analysis includes methods that can be used to check the robustness of study findings to multiple types of bias and methods that use simulation studies to generate data and understand the hypothetical impact of specific types of bias in a simulated data set. In this article, we review 2 strategies for quantitative bias analysis: 1) traditional probabilistic quantitative bias analysis and 2) quantitative bias analysis with generated data. An important difference between the 2 strategies relates to the type of data (real vs. generated data) used in the analysis. Monte Carlo simulations are used in both approaches, but the simulation process is used for different purposes in each. For both approaches, we outline and describe the steps required to carry out the quantitative bias analysis and also present a bias-analysis tutorial demonstrating how both approaches can be applied in the context of an analysis for selection bias. Our goal is to highlight the utility of quantitative bias analysis for practicing epidemiologists and increase the use of these methods in the epidemiologic literature.
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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.