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

Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

933
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
933
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

249
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,...
249
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

602
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...
602
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

243
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
243
Comparing Experimental Results: Student's t-Test01:09

Comparing Experimental Results: Student's t-Test

3.9K
The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
3.9K
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

2.6K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.6K

You might also read

Related Articles

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

Sort by
Same author

Correction: Somatic morbidity in bipolar disorders.

International journal of bipolar disorders·2026
Same author

Long-Term Opioid Therapy Tapering and Risk of Substance Use Disorder and Overdose: Differences by Opioid Dose and Duration.

Journal of general internal medicine·2026
Same author

Measured and Estimated Glomerular Filtration Rates and Risk of Adverse Health Outcomes.

JAMA·2026
Same author

Somatic morbidity in bipolar disorders.

International journal of bipolar disorders·2026
Same author

Evaluation of clinical utility in emulated clinical trials.

European journal of epidemiology·2026
Same author

Bacterial dysbiosis, cervicovaginal human papillomaviruses and inflammation persist in women living with HIV-1 after a year of antiretroviral treatment.

The Journal of infectious diseases·2026

Related Experiment Video

Updated: Nov 12, 2025

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

641

Adjustment for Disease Severity in the Test-Negative Study Design.

Iuliana Ciocănea-Teodorescu, Martha Nason, Arvid Sjölander

    American Journal of Epidemiology
    |March 17, 2021
    PubMed
    Summary

    The test-negative study design, used for vaccine effectiveness, may produce biased results. Adjusting for disease severity can help provide unbiased estimates, especially for infectious diseases like cholera.

    Keywords:
    biascollapsibilitytest-negative designvaccine effectiveness

    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

    14.9K
    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
    07:15

    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

    Published on: January 16, 2019

    11.2K

    Related Experiment Videos

    Last Updated: Nov 12, 2025

    Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
    06:16

    Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

    Published on: August 9, 2024

    641
    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
    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
    07:15

    Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

    Published on: January 16, 2019

    11.2K

    Area of Science:

    • Epidemiology
    • Biostatistics

    Background:

    • The test-negative study design is a popular variation of the case-control design, frequently used for estimating influenza vaccine effectiveness.
    • It aims to mitigate confounding bias related to healthcare-seeking behavior and offers logistic advantages.

    Purpose of the Study:

    • To investigate the validity of the test-negative design for estimating vaccine effectiveness in infectious diseases beyond influenza.
    • To identify methods for reducing bias and enabling generalization of findings to the broader population.

    Main Methods:

    • Analysis of directed acyclic graphs to understand the assumptions and limitations of the test-negative design.
    • Development and simulation of methods to address bias, specifically through adjustment for disease severity.
    • Application of findings to real-world scenarios, such as cholera vaccine effectiveness studies.

    Main Results:

    • The standard test-negative design can yield biased odds ratio estimates that are not generalizable to the entire population without strong assumptions.
    • Adjusting for disease severity can significantly reduce this bias.
    • Under specific assumptions, adjusting for severity allows for unbiased estimation of a causal odds ratio.

    Conclusions:

    • The test-negative design requires careful consideration of potential biases, particularly when applied to diseases like cholera.
    • Adjustment for disease severity is a crucial strategy for improving the accuracy and generalizability of vaccine effectiveness estimates from test-negative studies.
    • Further research and validation are needed for applying this adjusted design to various infectious disease contexts.