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

Censoring Survival Data01:09

Censoring Survival Data

256
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...
256
Longitudinal Studies01:26

Longitudinal Studies

256
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
256
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

308
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
308
Causality in Epidemiology01:21

Causality in Epidemiology

912
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...
912
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

89
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...
89
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

200
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.
200

You might also read

Related Articles

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

Sort by
Same author

From vision to action: a theory of change for introductory biology education reform.

Journal of microbiology & biology education·2026
Same author

Activity budgets, social behavior, and fitness outcomes associated with a baboon group fusion.

bioRxiv : the preprint server for biology·2026
Same author

Lifetime fitness and annual survival are heritable and highly genetically correlated in a wild primate population.

Evolution; international journal of organic evolution·2026
Same author

Social microbiome transmission predicts microbial specialization and host lifespan in a wild primate.

bioRxiv : the preprint server for biology·2026
Same author

Real-time heart rate in the wild: remote collection of cardiac data in baboons using a low-power Bluetooth and LoRaWAN system.

bioRxiv : the preprint server for biology·2026
Same author

Disparate social structures are underpinned by distinct social rules across a primate radiation.

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

Inference on summaries of a model-agnostic longitudinal variable importance trajectory with application to suicide prevention.

The annals of applied statistics·2026
Same journal

A NOVEL BAYESIAN FRAMEWORK UNCOVERING BRAIN CONNECTIVITY-TO-SHAPE RELATIONSHIP IN PRECLINICAL ALZHEIMER'S DISEASE.

The annals of applied statistics·2026
Same journal

EVALUATING MULTIPLEX DIAGNOSTIC TEST USING PARTIALLY ORDERED BAYES CLASSIFIER.

The annals of applied statistics·2026
Same journal

BRIDGING THE GAP: ENHANCING THE GENERALIZABILITY OF EPIGENETIC CLOCKS THROUGH TRANSFER LEARNING.

The annals of applied statistics·2026
Same journal

TREATMENT EFFECT HETEROGENEITY AND IMPORTANCE MEASURES FOR MULTIVARIATE CONTINUOUS TREATMENTS.

The annals of applied statistics·2026
Same journal

FEDERATED LEARNING OF ROBUST INDIVIDUALIZED DECISION RULES WITH APPLICATION TO HETEROGENEOUS MULTIHOSPITAL SEPSIS POPULATION.

The annals of applied statistics·2026
See all related articles

Related Experiment Video

Updated: Sep 18, 2025

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

4.1K

CAUSAL MEDIATION ANALYSIS FOR SPARSE AND IRREGULAR LONGITUDINAL DATA.

Shuxi Zeng1, Stacy Rosenbaum2,3, Susan C Alberts4

  • 1Department of Statistical Science, Duke University.

The Annals of Applied Statistics
|June 24, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new causal mediation analysis for sparse longitudinal data. Early adversity directly increased female baboons' glucocorticoid levels, with no evidence of mediation by social bonds.

Keywords:
Causal inferencefunctional principal component analysislongitudinal datamediationsparse and irregular data

More Related Videos

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K
Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.4K

Related Experiment Videos

Last Updated: Sep 18, 2025

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

4.1K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K
Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.4K

Area of Science:

  • Biostatistics
  • Longitudinal Data Analysis
  • Causal Inference

Background:

  • Causal mediation analysis is crucial for understanding treatment effects via intermediate variables.
  • Existing methods struggle with sparse, irregularly timed longitudinal data for mediators and outcomes.

Purpose of the Study:

  • To extend causal mediation analysis to handle sparse, irregular longitudinal data.
  • To investigate the direct and indirect effects of early adversity on adult glucocorticoid levels in female baboons.

Main Methods:

  • Functional data analysis framework treating data as stochastic processes.
  • Functional principal component analysis for dimension reduction in structural equation models.
  • Bayesian inference for uncertainty quantification.

Main Results:

  • Early adversity significantly increased adult female glucocorticoid concentrations (9-14%).
  • Little evidence was found for mediation of these effects through social bond strength.

Conclusions:

  • The developed functional causal mediation analysis is applicable to sparse longitudinal data.
  • Early adversity has a direct impact on female baboon stress hormone levels, independent of social bonds.