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

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

510
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,...
510
Study Design in Statistics01:15

Study Design in Statistics

10.2K
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...
10.2K
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

1.3K
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
1.3K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

504
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...
504
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

1.1K
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
1.1K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.8K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.8K

You might also read

Related Articles

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

Sort by
Same author

Environmental and family correlates of daily TV-watching time in children with autism spectrum disorder and typically developing children.

Frontiers in pediatrics·2026
Same author

Molecular bridge engineering in covalent organic frameworks for enhanced electronic transport.

Nature communications·2026
Same author

Comparative evaluation of interrupted time series analytical methods for healthcare quality improvement research: a Monte Carlo simulation study.

BMC medical research methodology·2026
Same author

Near-Theoretical-Limit Doping of Poly(benzodifurandione) through Carbonyl-Driven Aminoalkylsilane Attachment.

Journal of the American Chemical Society·2026
Same author

Corrigendum to "Improvement of calcified tendonitis following human placenta extract injection: A retrospective, single-arm, multicenter observational study" [J Orthopaed 71 (2026) 120-123].

Journal of orthopaedics·2026
Same author

Genome-wide CG hypomethylation of the <i>Arabidopsis</i> ecotype Cvi linked to structural variation and RNAi at the <i>VIM4</i>-<i>VIM2</i> locus.

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

Related Experiment Video

Updated: Mar 8, 2026

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

15.4K

A practical guide to propensity score analysis for applied clinical research.

Jaehoon Lee1, Todd D Little1

  • 1Department of Educational Psychology and Leadership, College of Education, Texas Tech University, United States.

Behaviour Research and Therapy
|February 4, 2017
PubMed
Summary

Propensity score (PS) analysis helps address bias in observational studies. This guide offers practical steps for researchers to conduct and evaluate PS analysis effectively.

Keywords:
MatchingPropensity scoreRSubclassificationWeighting

More Related Videos

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.2K
Influence of Emotional Factors on the Efficacy of Acupuncture Treatment for Overweight Complicated with Hyperlipidemia: A Retrospective Cohort Study
03:05

Influence of Emotional Factors on the Efficacy of Acupuncture Treatment for Overweight Complicated with Hyperlipidemia: A Retrospective Cohort Study

Published on: November 21, 2025

693

Related Experiment Videos

Last Updated: Mar 8, 2026

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

15.4K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.2K
Influence of Emotional Factors on the Efficacy of Acupuncture Treatment for Overweight Complicated with Hyperlipidemia: A Retrospective Cohort Study
03:05

Influence of Emotional Factors on the Efficacy of Acupuncture Treatment for Overweight Complicated with Hyperlipidemia: A Retrospective Cohort Study

Published on: November 21, 2025

693

Area of Science:

  • Clinical Research
  • Biostatistics
  • Epidemiology

Background:

  • Observational studies are crucial when randomized trials are unethical or infeasible.
  • Selection bias is a significant challenge in observational research.
  • Propensity score (PS) analysis is a key method for causal inference in these settings.

Purpose of the Study:

  • To provide a comprehensive overview of propensity score (PS) analysis techniques.
  • To offer practical guidance for applied clinical researchers on conducting PS analysis.
  • To demystify PS analysis and make it accessible to practitioners.

Main Methods:

  • Overview of PS estimation and application methods.
  • Explanation of balance diagnostics for assessing covariate balance.
  • Description of treatment effect estimation and sensitivity analysis techniques.

Main Results:

  • Recent advances in PS analysis are presented.
  • A tutorial is included to guide users through PS analysis steps.
  • The article synthesizes various PS methodologies for practical use.

Conclusions:

  • Propensity score (PS) analysis is a valuable tool for causal inference in observational studies.
  • Clear guidelines and practical tutorials can empower researchers to utilize PS methods.
  • This resource aims to enhance the application of PS analysis in clinical practice.