ArticleAmerican journal of epidemiology2019
Target Validity and the Hierarchy of Study Designs.
Article in American journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 3 of them syntheses that pooled it.
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
93 citing papers in PubMed, 3 syntheses or guidelines pooled it.
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- Trial
- Baseline Characteristics Explain Differences in Effectiveness of Randomization to Daily Oral TDF/FTC PrEP Between Transgender Women and Cisgender Men Who Have Sex With Men in the iPrEx Trial.Journal of acquired immune deficiency syndromes (1999) · 2019Trial
- Associated-Factor Studies in Biomedical Research: Foundations, Limitations, and Criteria for Appropriate Use.Epidemiologia (Basel, Switzerland) · 2026Review
- Effect of antihypertensive medication reduction on short-term blood pressure control in older adults: calibration of OPTiMISE trial results to real-world primary care data.Age and ageing · 2026Article
- Midlife hypertension and late-life cognition: weighting the LifeAfter90 study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Effect Modification and Its Impact on Preventable and Attributable Fractions in the Potential Outcomes Framework.Journal of epidemiology · 2026Article
- A Framework for Thinking About the Potential Public Health Impact of Epidemiologic Research.Epidemiology (Cambridge, Mass.) · 2026Article
- The Ideal Trial: Defining Causal Estimands that Balance Relevance and Feasibility in Target Trial Emulations and Actual Randomized Trials.Epidemiology (Cambridge, Mass.) · 2026Review
- Using large biobanks for psychiatric genomic research: Consistency of clinical and genetic aspects of recorded depression across US states in the All of Us Research Program.Psychological medicine · 2026Article
- Association between obesity and neurodevelopmental delay risk in children under five years: A study from Tumbes, Peru.PloS one · 2026Article
- Moving From Representativeness Toward Transportability in an Era of Digital and Big Data.International journal of public health · 2026Review
- Machine learning to examine adequate awareness and positive perception of HIV pre-exposure prophylaxis among women in sub-Saharan Africa: evidence from 2021-2024 surveys.BMC infectious diseases · 2025Article
- Revisiting representativeness.International journal of epidemiology · 2025Article
- An evolved interpretation of Austin Bradford Hill's causal viewpoints and their influence on epidemiologic methods.American journal of epidemiology · 2025Article
- When the parts are greater than the whole: how understanding mechanisms can advance implementation research.Implementation science : IS · 2025Article
- Estimating dementia incidence in insured older Asian Americans and Pacific Islanders in California: an application of inverse odds of selection weights.American journal of epidemiology · 2025Article
33 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
In recent years, increasing attention has been paid to problems of external validity, specifically to methodological approaches for both quantitative generalizability and transportability of study results. However, most approaches to these issues have considered external validity separately from internal validity. Here we argue that considering either internal or external validity in isolation may be problematic. Further, we argue that a joint measure of the validity of an effect estimate with respect to a specific population of interest may be more useful: We call this proposed measure target validity. In this work, we introduce and formally define target bias as the total difference between the true causal effect in the target population and the estimated causal effect in the study sample, and target validity as target bias = 0. We illustrate this measure with a series of examples and show how this measure may help us to think more clearly about comparisons between experimental and nonexperimental research results. Specifically, we show that even perfect internal validity does not ensure that a causal effect will be unbiased in a specific target population.
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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.