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

Randomized Experiments01:13

Randomized Experiments

6.7K
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...
6.7K
Chi-square Analysis02:46

Chi-square Analysis

37.2K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
37.2K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

26
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
26
Censoring Survival Data01:09

Censoring Survival Data

56
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...
56
Epistasis Analysis01:09

Epistasis Analysis

4.9K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
4.9K
Dihybrid Crosses01:18

Dihybrid Crosses

73.5K
Overview
73.5K

You might also read

Related Articles

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

Sort by
Same author

Mapping the genetic architecture of human cortical expansion and its links to neuropsychiatric disorders.

bioRxiv : the preprint server for biology·2026
Same author

Precision Functional Parcellation of the Human Cortex via Rest-Task fMRI Fusion.

bioRxiv : the preprint server for biology·2026
Same author

Association of Genetic Liability to Psychiatric Disorders with Peripheral Metabolic Dysregulation.

medRxiv : the preprint server for health sciences·2026
Same author

Rare Coding Variants Reveal Distinct Genetic Architectures Across Multidimensional Sleep Phenotypes.

medRxiv : the preprint server for health sciences·2026
Same author

Targeted maximum likelihood estimation for mediation analysis with multiple time-varying mediators.

Biometrics·2026
Same author

Characterizing the Uncertainty, Misclassification and Inconsistency of Polygenic Prediction.

medRxiv : the preprint server for health sciences·2026
Same journal

Interpretable Bayesian Modeling for Multireader Multicase Studies: Addressing Overdispersion and Limited Sample Size in Diagnostic Enhancement Evaluation.

Statistics in medicine·2026
Same journal

Adaptive Sequential Multiple Hypotheses Testing for Concomitant Vaccine Safety Surveillance.

Statistics in medicine·2026
Same journal

Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta-Diversity.

Statistics in medicine·2026
Same journal

Optimal Weighted Tests for Replication Studies and the 'Two-Trials Rule' With Multiple Hypotheses.

Statistics in medicine·2026
Same journal

Identifiable Copula-Double-Cox Models: A Fully Parametric Framework for Dependent Right-Censored Survival Data.

Statistics in medicine·2026
Same journal

Moving From Individualized Risk-Based Prevention to Benefit-Based Prevention: Estimating Individualized Life-Years Gained From Prevention Services as a Basis for Eligibility.

Statistics in medicine·2026
See all related articles

Related Experiment Video

Updated: May 29, 2025

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

14.4K

Causal Mediation Analysis: A Summary-Data Mendelian Randomization Approach.

Shu-Chin Lin1,2, Sheng-Hsuan Lin3, Tian Ge4,5,6

  • 1Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan.

Statistics in Medicine
|February 6, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces improved Mendelian randomization (MR) methods for causal mediation analysis, enhancing accuracy and efficiency. The novel Diff-IVW, Prod-IVW, and Prod-Median approaches offer more robust and reliable causal inference in complex biological systems.

Keywords:
causal inferenceindirect effectmediation analysismediation proportionsummary‐data Mendelian randomization

More Related Videos

In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

20.6K
Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

3.9K

Related Experiment Videos

Last Updated: May 29, 2025

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

14.4K
In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

20.6K
Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

3.9K

Area of Science:

  • Genetics and Biostatistics
  • Causal Inference Methodologies
  • Epidemiological Research

Background:

  • Mendelian randomization (MR) is crucial for causal inference in genetic epidemiology.
  • Existing MR methods for mediation analysis, like difference and product methods using MR-Inverse Variance Weighted (MR-IVW), require enhancement for rigor and precision.
  • There is a need for advanced MR-based mediation frameworks to address limitations in current methodologies.

Purpose of the Study:

  • To develop novel summary-data Mendelian randomization (MR) frameworks for causal mediation analysis.
  • To improve the accuracy, statistical efficiency, and robustness of existing MR-based mediation methods.
  • To propose pleiotropy-robust methods for more reliable causal effect estimation.

Main Methods:

  • Developed novel variance estimators for mediation effects in MR analysis.
  • Derived rigorous statistical inference procedures for MR-based mediation.
  • Proposed Diff-IVW and Prod-IVW methods, enhancing existing MR-IVW approaches.
  • Adapted MR-Egger and MR-Median principles to create pleiotropy-robust Diff-Egger, Diff-Median, Prod-Egger, and Prod-Median methods.

Main Results:

  • The proposed Diff-IVW and Prod-IVW methods demonstrated improved statistical efficiency and type I error control compared to existing approaches.
  • While MR-IVW methods are susceptible to directional pleiotropy bias, Diff-Median and Prod-Median effectively mitigate these biases.
  • Simulation studies confirmed the performance of the proposed methods, highlighting their complementary nature.

Conclusions:

  • The developed MR-based causal mediation analysis frameworks offer significant improvements in statistical properties.
  • The proposed methods, particularly Diff-IVW, Prod-IVW, and Prod-Median, are recommended for practical application due to their enhanced accuracy, efficiency, and robustness.
  • These advanced methodologies provide more reliable tools for dissecting complex causal pathways in genetic studies.