ArticleAmerican journal of epidemiology2020
The Epidemiologic Toolbox: Identifying, Honing, and Using the Right Tools for the Job.
Article in American journal of epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- A Framework for Thinking About the Potential Public Health Impact of Epidemiologic Research.Epidemiology (Cambridge, Mass.) · 2026Article
- Unmet needs among long-term breast cancer survivors.Cancer causes & control : CCC · 2025Article
- Using machine learning to identify subgroups with the highest expected benefit in a population-based water, sanitation, handwashing, and nutrition intervention.medRxiv : the preprint server for health sciences · 2025Article
- Variable selection for causal inference, prediction, and descriptive research: a narrative review of recommendations.European heart journal open · 2025Review
- Scientific Committee guidance on appraising and integrating evidence from epidemiological studies for use in EFSA's scientific assessments.EFSA journal. European Food Safety Authority · 2024Article
- Clinical Multiteam System Composition and Complexity Among Newly Diagnosed Early-Stage Breast, Colorectal, and Lung Cancer Patients With Multiple Chronic Conditions: A SEER-Medicare Analysis.JCO oncology practice · 2023Article
- On the Need to Revitalize Descriptive Epidemiology.American journal of epidemiology · 2022Article
- Is the Way Forward to Step Back? Documenting the Frequency With Which Study Goals Are Misaligned With Study Methods and Interpretations in the Epidemiologic Literature.Epidemiologic reviews · 2022Observational
- The Global Emergence of Human Babesiosis.Pathogens (Basel, Switzerland) · 2021Review
- Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example.Infectious Disease Modelling · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
There has been much debate about the relative emphasis of the field of epidemiology on causal inference. We believe this debate does short shrift to the breadth of the field. Epidemiologists answer myriad questions that are not causal and hypothesize about and investigate causal relationships without estimating causal effects. Descriptive studies face significant and often overlooked inferential and interpretational challenges; we briefly articulate some of them and argue that a more detailed treatment of biases that affect single-sample estimation problems would benefit all types of epidemiologic studies. Lumping all questions about causality creates ambiguity about the utility of different conceptual models and causal frameworks; 2 distinct types of causal questions include 1) hypothesis generation and theorization about causal structures and 2) hypothesis-driven causal effect estimation. The potential outcomes framework and causal graph theory help efficiently and reliably guide epidemiologic studies designed to estimate a causal effect to best leverage prior data, avoid cognitive fallacies, minimize biases, and understand heterogeneity in treatment effects. Appropriate matching of theoretical frameworks to research questions can increase the rigor of epidemiologic research and increase the utility of such research to improve public health.
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.