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

Controls in Experiments01:13

Controls in Experiments

14.2K
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...
14.2K
Censoring Survival Data01:09

Censoring Survival Data

299
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
299
Contingency Table01:29

Contingency Table

2.9K
A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
2.9K
Randomized Experiments01:13

Randomized Experiments

8.5K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
8.5K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

214
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,...
214
Study Design in Statistics01:15

Study Design in Statistics

9.7K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
9.7K

You might also read

Related Articles

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

Sort by
Same author

AI-assisted teams outperform AI-led teams but not human-only teams in assessing research reproducibility in quantitative social science.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

A Bayesian bivariate spatial modeling framework for stage-specific cancer incidence and targeting of screening efforts.

American journal of epidemiology·2026
Same author

Publisher Correction: Reproducibility and robustness of economics and political science research.

Nature·2026
Same author

Cardiovascular and mortality risks following COVID-19-related vs. non-COVID-19 COPD exacerbations.

Annals of the American Thoracic Society·2026
Same author

Reproducibility and robustness of economics and political science research.

Nature·2026
Same author

Estimating the cost of establishing and maintaining a trauma registry at a tertiary health institution in a low and middle-income country.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention·2026

Related Experiment Video

Updated: Oct 31, 2025

Operant Procedures for Assessing Behavioral Flexibility in Rats
08:30

Operant Procedures for Assessing Behavioral Flexibility in Rats

Published on: February 15, 2015

21.2K

A (Flexible) Synthetic Control Method for Count Data and Other Nonnegative Outcomes.

Carl Bonander1

  • 1From the Health Economics & Policy, School of Public Health & Community Medicine, University of Gothenburg, Gothenburg, Sweden.

Epidemiology (Cambridge, Mass.)
|June 29, 2021
PubMed
Summary

The synthetic control method, used in epidemiology, can be improved for better covariate balance. This new approach ensures non-negative counterfactuals, addressing limitations of existing methods for population-level intervention evaluation.

More Related Videos

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

14.8K
The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan
11:58

The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan

Published on: June 29, 2018

9.7K

Related Experiment Videos

Last Updated: Oct 31, 2025

Operant Procedures for Assessing Behavioral Flexibility in Rats
08:30

Operant Procedures for Assessing Behavioral Flexibility in Rats

Published on: February 15, 2015

21.2K
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

14.8K
The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan
11:58

The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan

Published on: June 29, 2018

9.7K

Area of Science:

  • Epidemiology
  • Causal Inference
  • Econometrics

Background:

  • The synthetic control method (SCM) is widely used for evaluating population-level interventions.
  • Original SCM imposes strict interpolation constraints, potentially leading to poor covariate balance and bias.
  • Existing SCM extensions allowing extrapolation may yield unrealistic negative counterfactuals, unsuitable for count data.

Purpose of the Study:

  • To propose an enhanced synthetic control method that allows for extrapolation to improve covariate balance.
  • To ensure that estimated counterfactual outcomes remain non-negative, making the method suitable for count data.
  • To provide a flexible alternative to existing SCM approaches that may produce poor or unrealistic counterfactuals.

Main Methods:

  • Developed a modified synthetic control procedure incorporating a penalty term.
  • The penalty favors interpolation over extrapolation where possible, balancing flexibility with stability.
  • The method was theoretically analyzed and demonstrated using empirical examples.

Main Results:

  • The proposed method successfully allows for extrapolation while ensuring non-negative counterfactual estimates.
  • Demonstrated improved covariate balance compared to methods restricted to interpolation.
  • Empirical examples showed the method's utility when standard approaches yield poor or unrealistic counterfactuals.

Conclusions:

  • The enhanced synthetic control method offers a valuable alternative for epidemiological studies, particularly with bounded or count outcome data.
  • This approach improves covariate balance and generates more realistic counterfactual estimates.
  • Implementation functions are provided in R for practical application.