Related Experiment Video

Updated: Sep 25, 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

[Use of the major components methods in epidemiological studies]

Iu N Kurunov, O V Reviakina, V M Efimov

    Problemy Tuberkuleza
    |June 7, 2003
    PubMed

    More Related Videos

    Real-World M3-BREATHE: Toward Multimodal Mobile Monitoring of Behaviour, Respiration, and Exposures for Treatment and Health Evaluation09:50

    Real-World M3-BREATHE: Toward Multimodal Mobile Monitoring of Behaviour, Respiration, and Exposures for Treatment and Health Evaluation

    Published on: June 5, 2026

    Quantification of the Potential Impact of Glyphosate-Based Products on Microbiomes07:42

    Quantification of the Potential Impact of Glyphosate-Based Products on Microbiomes

    Published on: January 10, 2022

    Related Concept Videos

    Statistical Methods for Analyzing Epidemiological Data01:25

    Statistical Methods for Analyzing Epidemiological Data

    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:
    Introduction to Epidemiology01:26

    Introduction to Epidemiology

    Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
    Study Designs in Epidemiology01:20

    Study Designs in Epidemiology

    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 case-control studies.
    Confounding in Epidemiological Studies01:27

    Confounding in Epidemiological Studies

    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 phenomenon...
    Causality in Epidemiology01:21

    Causality in Epidemiology

    Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
    Strategies for Assessing and Addressing Confounding01:25

    Strategies for Assessing and Addressing Confounding

    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...