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

Longitudinal Research02:20

Longitudinal Research

13.7K
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...
13.7K
Longitudinal Studies01:26

Longitudinal Studies

698
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...
698
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

719
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
719
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

342
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...
342
Quadratic Models01:23

Quadratic Models

357
Quadratic models are mathematical representations used to describe relationships in which the rate of change changes at a constant rate. These models appear in a wide variety of natural and engineered systems, especially those involving motion, forces, and optimization. One common application is analyzing the vertical motion of objects influenced by gravity, such as a ball thrown into the air.In such scenarios, the object's height changes over time in a curved pattern, rising to a maximum point...
357
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

414
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...
414

You might also read

Related Articles

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

Sort by
Same author

A scalable, multi-resolution consensus clustering approach for prioritizing robust signals from high-throughput screens.

Briefings in bioinformatics·2026
Same author

Identifying therapeutic targets in low-grade serous ovarian carcinomas with no specific molecular profile.

The Journal of pathology·2026
Same author

Investigating the contribution of rare non-coding variants in BRCA1, BRCA2 and PALB2 to hereditary breast cancer.

NPJ breast cancer·2026
Same author

Historical change in the health of Ghanaian middle-aged and older adults.

The journals of gerontology. Series B, Psychological sciences and social sciences·2026
Same author

Associations of family policy and income inequality with loneliness in midlife: Cross-national evidence from the United States and Europe.

Social science & medicine (1982)·2026
Same author

Historical Change in Midlife Development from a Cross-National Perspective.

Current directions in psychological science·2026
Same journal

Proficiency order invariance of MLE, MAP, EAP, and WLE in item response theory.

The British journal of mathematical and statistical psychology·2026
Same journal

Bias and precision in true-score estimation.

The British journal of mathematical and statistical psychology·2026
Same journal

Polychoric correlations under the assumption of elliptical latent traits.

The British journal of mathematical and statistical psychology·2026
Same journal

Regularized reduced rank regression for mixed predictor and response variables.

The British journal of mathematical and statistical psychology·2026
Same journal

A multiple-choice SDT model for cognitive diagnosis models.

The British journal of mathematical and statistical psychology·2026
Same journal

Modular item response and structural equation modelling via measurement and uncertainty preserving parametric modelling.

The British journal of mathematical and statistical psychology·2026
See all related articles

Related Experiment Video

Updated: Apr 18, 2026

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

6.9K

Blending substantive and methodological expertise into statistical models: Longitudinal model development.

Kevin J Grimm1, Russell Houpt1, Maggie Cleaver1

  • 1Department of Psychology, Arizona State University, Tempe, Arizona, USA.

The British Journal of Mathematical and Statistical Psychology
|April 17, 2026
PubMed
Summary
This summary is machine-generated.

Collaboration between applied researchers and statistical experts is crucial for effective study design and data analysis, especially for complex research on change processes. This partnership ensures optimal methods are used, even with secondary or limited longitudinal data.

Keywords:
growth curve modellinglinear multilevel modelslongitudinal data analysissurvival analysis

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

3.8K
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

11.2K

Related Experiment Videos

Last Updated: Apr 18, 2026

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

6.9K
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

3.8K
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

11.2K

Area of Science:

  • Methodology
  • Data Science
  • Applied Research

Background:

  • Effective study design and data analysis ideally involve collaboration between applied researchers and statistical experts.
  • Research questions about change processes present unique challenges in study design and data analysis.
  • Longitudinal data analysis often requires compromises between ideal models and data feasibility, particularly when using secondary data.

Purpose of the Study:

  • To highlight the importance of collaboration between applied researchers and statistical experts in study design and data analysis.
  • To discuss the challenges in analyzing change processes, especially with secondary or limited longitudinal data.
  • To illustrate how collaborative efforts can inform the development of appropriate analytic models.

Main Methods:

  • The paper discusses two empirical projects.
  • It focuses on the collaborative process between applied researchers and developmental methodologists.
  • The discussion centers on how this collaboration informed the analytic models used.

Main Results:

  • Collaboration between applied researchers and statistical experts is essential for robust study design and analysis.
  • Developmental methodologists can help bridge the gap between research questions and data limitations.
  • Empirical examples demonstrate the successful application of collaborative model development.

Conclusions:

  • Close collaboration between applied researchers and statistical experts is vital for addressing complex research questions, particularly those involving change processes.
  • Adapting analytic models to fit feasible longitudinal data, often secondary, requires a joint effort.
  • The discussed projects exemplify how methodological expertise can guide applied researchers in developing effective analytic strategies.