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

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

Mechanistic Models: Compartment Models in Individual and Population Analysis

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 squares (OLS)...
Longitudinal Studies01:26

Longitudinal Studies

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...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...

You might also read

Related Articles

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

Sort by
Same author

Diabetes, impaired fasting glucose, and cognitive trajectories: a multi-cohort study.

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

Suicide mortality in United States urban career firefighters and emergency medical service providers.

Preventive medicine·2026
Same author

Residential green space, walkability, and cardiometabolic biomarkers in midlife women: a longitudinal cohort study.

Environmental research, health : ERH·2026
Same author

Impact of adopting race-neutral lung function reference equations on firefighter hiring.

American journal of respiratory and critical care medicine·2026
Same author

Posttraumatic Stress Disorder and Handgrip Strength Among World Trade Center Firefighters and Emergency Medical Responders.

International journal of environmental research and public health·2026
Same author

Generalizability of blood-based biomarkers of Alzheimer's disease and related dementias in a multicultural cohort of older adults: The effect of adjustment for kidney function.

Journal of Alzheimer's disease : JAD·2026
Same journal

Ensuring Quality in Preclinical Research: The Importance of Being Human.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Addressing Cluster-Level Treatment Effect Heterogeneity in Sample Size Determination for Hierarchical 2 × 2 Factorial Designs.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

A Multiple Imputation Approach to Distinguish Curative From Life-Prolonging Effects in the Presence of Missing Covariates.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Tests for Categorical Data Beyond Pearson: A Distance Covariance and Energy Distance Approach.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Nonparametric Estimation of the Patient-Weighted While-Alive Estimand.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Two-Stage Multiple Test Procedures Controlling False Discovery Rate With Auxiliary Variable and Their Application to Set4 <math><semantics><mi>Δ</mi> <annotation>$\Delta$</annotation></semantics></math> Mutant Data.

Biometrical journal. Biometrische Zeitschrift·2026
See all related articles

Related Experiment Video

Updated: May 28, 2026

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
09:38

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Multi-stage transitional models with random effects and their application to the Einstein aging study.

Changhong Song1, Lynn Kuo, Carol A Derby

  • 1Department of Statistics, University of Connecticut, Storrs, CT 06269, USA.

Biometrical Journal. Biometrische Zeitschrift
|October 25, 2011
PubMed
Summary
This summary is machine-generated.

This study models cognitive decline in aging, analyzing transitions between normal cognition, memory impairment, and dementia. It identifies risk factors influencing these stages and informative missingness due to death.

More Related Videos

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Related Experiment Videos

Last Updated: May 28, 2026

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
09:38

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Area of Science:

  • Gerontology
  • Biostatistics
  • Cognitive Neuroscience

Background:

  • Longitudinal aging studies track cognitive status to understand dementia development and risk factors.
  • Dementia progression is often modeled as a multi-stage process with time-varying effects.
  • Understanding transitions between cognitive states is crucial for aging research.

Purpose of the Study:

  • To assess how risk factors influence transitions between cognitive stability, memory impairment, and clinical dementia.
  • To develop and evaluate a statistical model linking transition probabilities, informative missingness (death), and subject heterogeneity.
  • To compare generalized logit and proportional odds models for analyzing cognitive status transitions.

Main Methods:

  • Developed a shared random effects model to analyze transitions among cognitive states.
  • Incorporated time-varying effects and informative missingness due to death.
  • Evaluated generalized logit and proportional odds models using first-order Markov transition probabilities.
  • Utilized the Akaike information criterion for model goodness-of-fit assessment on Einstein Aging Study data.

Main Results:

  • Compared eight distinct modeling approaches (four generalized logit, four proportional odds).
  • Identified the best-fitting generalized logit and proportional odds models for cognitive transition analysis.
  • Demonstrated the utility of shared random effects models in capturing complex aging trajectories.

Conclusions:

  • The developed shared random effects model effectively captures transitions in cognitive status during aging.
  • The best-fitting models provide insights into risk factor influences on dementia progression.
  • These findings contribute to a more nuanced understanding of cognitive aging and dementia development.