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

Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

100
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...
100
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

169
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...
169
Controls in Experiments01:13

Controls in Experiments

7.7K
When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...
7.7K
Crossover Experiments01:16

Crossover Experiments

2.8K
Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
2.8K
Group Design02:01

Group Design

8.9K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
8.9K
Drug Concentration Versus Time Correlation01:15

Drug Concentration Versus Time Correlation

768
The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
768

You might also read

Related Articles

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

Sort by
Same author

A Metabolomics Approach To Identify Metabolites Associated with Uremic Symptoms in Patients Receiving Maintenance Hemodialysis.

Kidney360·2025
Same author

Incidence and Risk Factors for Pruritus in Patients with Nondialysis CKD.

Clinical journal of the American Society of Nephrology : CJASN·2022
See all related articles

Related Experiment Video

Updated: Jul 2, 2025

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

5.9K

Controlling time-varying confounding in difference-in-differences studies using the time-varying treatments

Leslie Myint1

  • 1Department of Mathematics, Statistics, and Computer Science, Macalester College, Saint Paul, MN USA.

Health Services & Outcomes Research Methodology
|February 26, 2024
PubMed
Summary

This study shows how time-varying treatments (TVT) methods can improve difference-in-differences (DiD) analysis by reducing bias from time-varying confounders. Hybrid approaches combining TVT and DiD offer better estimation when standard assumptions fail.

Keywords:
Difference-in-differencesInverse probability weightingTime-varying confoundingTime-varying treatmentsTreatment strategies

More Related Videos

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

9.9K
Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

15.4K

Related Experiment Videos

Last Updated: Jul 2, 2025

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

5.9K
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

9.9K
Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

15.4K

Area of Science:

  • Biostatistics
  • Epidemiology
  • Health Economics

Background:

  • Difference-in-differences (DiD) studies often face challenges with time-varying confounding.
  • Standard DiD methods may yield biased estimates when confounders change over time due to treatment exposure.

Purpose of the Study:

  • To explore how time-varying treatment (TVT) biostatistical methods can address time-varying confounding in DiD studies.
  • To compare the performance of TVT, DiD, and hybrid estimators using simulations.

Main Methods:

  • A simulation study was conducted using longitudinal data with treatment effect heterogeneity.
  • Linear and logistic models were used to simulate data, considering time-invariant and time-varying confounders.
  • Inverse probability weighting estimators from TVT, DiD, and hybrid frameworks were compared for bias and standard error.

Main Results:

  • Hybrid estimators combining TVT and DiD concepts demonstrated lower bias compared to standard TVT and DiD estimators under unmet assumptions.
  • The simulation highlighted the impact of time-varying confounders affected by prior treatment on estimator performance.

Conclusions:

  • The time-varying treatment (TVT) framework offers valuable tools to enhance difference-in-differences (DiD) analyses, particularly in the presence of time-varying confounding.
  • Hybrid approaches provide more robust estimation, and TVT offers alternative estimands relevant for policy evaluation.