Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Relative Risk01:12

Relative Risk

1.2K
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
1.2K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

266
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
266
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

223
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
223
Hazard Ratio01:12

Hazard Ratio

378
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
378
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

380
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
380
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

978
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
978

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Racial Differences in Adverse Pregnancy Outcomes and Incident Hypertension: A Mediation Analysis.

Journal of the American Heart Association·2026
Same author

Large-scale proteomics in early pregnancy and timing of onset of hypertensive disorders of pregnancy.

medRxiv : the preprint server for health sciences·2026
Same author

Endothelial Susceptibility-Related Genetic Variants and Hypertensive Disorders of Pregnancy-Brief Report.

Arteriosclerosis, thrombosis, and vascular biology·2026
Same author

Harmonizing Maternal and Infant Biospecimen Collection and Processing for Research.

Biopreservation and biobanking·2026
Same author

Fetal brain volumes and brain gyrification index associated with opioid exposure.

Brain communications·2026
Same author

From single conventional regression to ensemble modelling: relative importance of the Healthy Eating Index-2015 components in relation to adverse pregnancy outcomes.

The British journal of nutrition·2026
Same journal

Application of the E-value under non-proportional hazards.

Epidemiology (Cambridge, Mass.)·2026
Same journal

Can the All of Us sample be reweighted to mirror a nationally representative sample? A comparison of mortality predictors.

Epidemiology (Cambridge, Mass.)·2026
Same journal

Gut health, systemic inflammation, and linear growth among Indonesian infants: findings from the Action Against Stunting Hub observation cohort: Erratum.

Epidemiology (Cambridge, Mass.)·2026
Same journal

Evaluating Estimators in Partially Identified Models.

Epidemiology (Cambridge, Mass.)·2026
Same journal

Stratification and accumulation? Explaining changing mortality inequities between business owners and non-owners in the U.S. (1984-2022).

Epidemiology (Cambridge, Mass.)·2026
Same journal

Be wary of age-stratum aging in early-onset cancer trends.

Epidemiology (Cambridge, Mass.)·2026
See all related articles

Related Experiment Video

Updated: Nov 20, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.9K

Incremental Propensity Score Effects for Time-fixed Exposures.

Ashley I Naimi1, Jacqueline E Rudolph1, Edward H Kennedy2

  • 1From the Department of Epidemiology, Emory University, Atlanta, GA.

Epidemiology (Cambridge, Mass.)
|January 20, 2021
PubMed
Summary
This summary is machine-generated.

The incremental propensity score (PS) method offers a robust alternative to average treatment effects (ATEs) for causal inference in public health research. This approach better reflects policy impacts and relaxes restrictive assumptions like positivity.

More Related Videos

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
09:50

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke

Published on: February 12, 2015

11.4K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K

Related Experiment Videos

Last Updated: Nov 20, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.9K
Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
09:50

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke

Published on: February 12, 2015

11.4K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K

Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Average treatment effects (ATEs) are commonly used for causal inference but may not align with research questions or policy goals.
  • Key assumptions for ATE interpretation, including exchangeability, consistency, and positivity, are often violated in real-world observational studies.
  • Positivity violations, in particular, can obscure the interpretation of ATE estimates, limiting their utility for public health decision-making.

Purpose of the Study:

  • To introduce and evaluate the incremental propensity score (PS) approach as an alternative to ATEs for quantifying causal effects.
  • To assess the relationship between total vegetable intake and preeclampsia risk using the incremental PS method, addressing limitations of ATEs.
  • To demonstrate the utility of incremental PS effects in public health research by relaxing stringent assumptions.

Main Methods:

  • The study employed the incremental propensity score (PS) approach to quantify the effect of shifting an individual's exposure propensity by a defined amount.
  • The Nulliparous Pregnancy Outcomes Study: monitoring mothers-to-be (nuMoM2b) dataset was utilized to analyze the association between vegetable intake and preeclampsia.
  • ATEs were calculated for comparison, highlighting the impact of positivity violations on interpretation.

Main Results:

  • ATE estimates suggested a modest reduction in preeclampsia risk with increased vegetable intake, but interpretation was hindered by positivity violations.
  • The incremental PS analysis, with odds ratios ranging from 0.20 to 5.0, indicated no significant difference in preeclampsia risk when shifting exposure propensity.
  • The findings underscore the challenges in interpreting ATEs under positivity violations and highlight the advantages of the incremental PS approach.

Conclusions:

  • The incremental propensity score (PS) method provides a valuable tool for causal inference in public health, offering a more flexible alternative to ATEs.
  • This approach can better reflect the impact of policy interventions and is less sensitive to positivity violations, enhancing the reliability of findings.
  • The study demonstrates the practical application and benefits of incremental PS effects for addressing complex public health questions with fewer restrictive assumptions.