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

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

16.7K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
16.7K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

1.2K
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:
1.2K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

556
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,...
556
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

711
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
711
Cancer Survival Analysis01:21

Cancer Survival Analysis

838
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
838
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

1.4K
Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
1.4K

You might also read

Related Articles

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

Sort by
Same author

Preparation of Polyvinyl Alcohol/Chitosan/<i>Antrodia cinnamomea</i> Polysaccharide Composite Film Incorporated with Tea Tree Essential Oil: Structure, Antioxidant, Antibacterial Activities, and Application in Postharvest 'Yuluxiang' Pear Preservation.

Foods (Basel, Switzerland)·2026
Same author

Early response to ivarmacitinib and its impact on long-term efficacy in patients with moderate-to-severe atopic dermatitis: a <i>post hoc</i> analysis of a phase-III trial.

The Journal of dermatological treatment·2026
Same author

[Catalytic synthesis of dihydroavenanthramide D by lipase RWL].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology·2026
Same author

Early Pregnancy Blood Pressure Trajectory Groups Predict Hypertensive Disorders of Pregnancy.

JACC. Advances·2026
Same author

Case Report: A rare co-occurrence of IgA pemphigus and pyoderma gangrenosum associated with IgA-κ type monoclonal gammopathy of undetermined significance: a 19-year diagnostic and therapeutic journey.

Frontiers in immunology·2026
Same author

Association of sarcopenia with the long-term risk of overall infections and infectious diseases: a prospective cohort study of 458 332 participants.

MedScience·2026

Related Experiment Video

Updated: Apr 7, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.8K

Retrospective likelihood-based methods for analyzing case-cohort genetic association studies.

Yuanyuan Shen1, Tianxi Cai1, Yu Chen2

  • 1Department of Biostatistics, Harvard University, Boston, MA 02115.

Biometrics
|July 16, 2015
PubMed
Summary

This study introduces a novel pseudo-score test for case-cohort (CCH) designs, enhancing the assessment of genetic susceptibility (SNP) and event time associations, particularly for low event rates. The method offers flexibility and improved efficiency compared to existing approaches.

Keywords:
Case-cohort designCox proportional hazards modelGenetic associationInverse probability weightingPolytomous regressionPseudo-likelihood

More Related Videos

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

35.0K
gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair
08:15

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

Published on: October 6, 2014

12.8K

Related Experiment Videos

Last Updated: Apr 7, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.8K
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

35.0K
gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair
08:15

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

Published on: October 6, 2014

12.8K

Area of Science:

  • Biostatistics
  • Genetic Epidemiology
  • Statistical Genetics

Background:

  • The case-cohort (CCH) design is a cost-effective approach for studying genetic susceptibility and time-to-event data, especially when event rates are low.
  • Existing methods for analyzing genetic associations in CCH designs may have limitations regarding covariate handling and efficiency.

Purpose of the Study:

  • To propose a powerful pseudo-score test for assessing the association between single nucleotide polymorphisms (SNPs) and event time within the CCH design.
  • To develop a method that allows the censoring distribution to depend on covariates measured only in the CCH sample, without needing full cohort data.

Main Methods:

  • A pseudo-score test is derived from a pseudo-likelihood, treating SNP genotype as the dependent variable and time-to-event outcomes/covariates as independent.
  • The method estimates hazard ratio parameters by maximizing the pseudo-likelihood, leveraging the independence or low-dimensional relationship of genetic variables with covariates.
  • Large sample properties are studied, and finite sample performance is assessed using simulated and real data.

Main Results:

  • The proposed pseudo-score test demonstrates high relative efficiency compared to commonly used alternative approaches.
  • The method effectively handles censoring distributions dependent on CCH-specific covariates without requiring extensive follow-up data from the entire cohort.
  • Validation through simulated and real data confirms the method's performance.

Conclusions:

  • The developed pseudo-score test provides a flexible, efficient, and powerful tool for genetic association studies using the case-cohort design.
  • This approach offers significant advantages in handling complex censoring patterns and covariate information, improving the analysis of time-to-event genetic data.