ArticleEpidemiology (Cambridge, Mass.)2021
Incremental Propensity Score Effects for Time-fixed Exposures.
Article in Epidemiology (Cambridge, Mass.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Assessing the causal effects of a stochastic intervention in time series data: are heat alerts effective in preventing deaths and hospitalizations?Biostatistics (Oxford, England) · 2023Pooled it
- Contributions of preeclampsia to preterm delivery: a hypothetical interventional cohort study using incremental propensity scores.International journal of epidemiology · 2026Article
- Rethinking causal inference for recurring exposures: The incremental propensity score approach with lavaan.Behavior research methods · 2025Article
- Modeling Versus Balancing Approaches to Addressing Instrumental Variables in Weighting: A Comparison of the Outcome-Adaptive Lasso, Stable Balancing Weighting, and Stable Confounder Selection.Pharmacoepidemiology and drug safety · 2025Article
- Synthesis estimators for transportability with positivity violations by a continuous covariate.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2025Article
- The impact of aggressive and conservative propensity for initiation of neuromuscular blockade in mechanically ventilated patients with hypoxemic respiratory failure.Journal of critical care · 2024Article
- Causal Effects of Stochastic PrEP Interventions on HIV Incidence Among Men Who Have Sex With Men.American journal of epidemiology · 2024Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
When causal inference is of primary interest, a range of target parameters can be chosen to define the causal effect, such as average treatment effects (ATEs). However, ATEs may not always align with the research question at hand. Furthermore, the assumptions needed to interpret estimates as ATEs, such as exchangeability, consistency, and positivity, are often not met. Here, we present the incremental propensity score (PS) approach to quantify the effect of shifting each person's exposure propensity by some predetermined amount. Compared with the ATE, incremental PS may better reflect the impact of certain policy interventions and do not require that positivity hold. Using the Nulliparous Pregnancy Outcomes Study: monitoring mothers-to-be (nuMoM2b), we quantified the relationship between total vegetable intake and the risk of preeclampsia and compared it to average treatment effect estimates. The ATE estimates suggested a reduction of between two and three preeclampsia cases per 100 pregnancies for consuming at least half a cup of vegetables per 1,000 kcal. However, positivity violations obfuscate the interpretation of these results. In contrast, shifting each woman's exposure propensity by odds ratios ranging from 0.20 to 5.0 yielded no difference in the risk of preeclampsia. Our analyses show the utility of the incremental PS effects in addressing public health questions with fewer assumptions.
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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.