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 Studies01:26

Longitudinal Studies

612
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...
612
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

687
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...
687
Longitudinal Research02:20

Longitudinal Research

13.6K
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...
13.6K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

535
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...
535
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

316
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...
316
Two-Way ANOVA01:17

Two-Way ANOVA

3.5K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
3.5K

You might also read

Related Articles

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

Sort by
Same author

How to apply Bayesian stochastic search variable selection with multiply imputed data.

Psychological methods·2026
Same author

Construct Diversity in Measures of Helicopter Parenting in Emerging Adulthood.

Emerging adulthood (Print)·2026
Same author

Testing the robustness of daily associations of affect with alcohol and cannabis use.

Journal of psychopathology and clinical science·2026
Same author

Identifying and characterizing shared and ethnic background site-specific dietary patterns in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

Nutrition journal·2025
Same author

Depressive symptoms and goal pursuit: Between-person and reciprocal within-person effects in a multi-wave longitudinal study.

Journal of clinical psychology·2024
Same author

A systematic comparison of additive and interaction approaches to modeling the effects of syndemic problems on HIV outcomes in South Africa.

Journal of behavioral medicine·2024
Same journal

The frequency of childhood gender-nonconforming behavior in a nationally representative sample.

Developmental psychology·2026
Same journal

Linking childhood adversity and daily hassles to adolescent sleep behaviors: Diurnal cortisol as a mediating pathway.

Developmental psychology·2026
Same journal

Infants' expectations about caregivers' comforting behavior and associations with maternal depressive symptoms at 6, 9, and 12 months.

Developmental psychology·2026
Same journal

Nonsymbolic ratio and fraction magnitude processing predict fraction knowledge in early grades.

Developmental psychology·2026
Same journal

The growing influence of the parental monitoring-peer affiliation pathway in early adolescence.

Developmental psychology·2026
Same journal

Employing a cohort-sequential design spanning 30 years to understand trajectories of maturity fears.

Developmental psychology·2026
See all related articles

Related Experiment Video

Updated: Mar 13, 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

6.8K

Comparing within-person effects from multivariate longitudinal models.

Sierra A Bainter1, Andrea L Howard2

  • 1Department of Psychology, University of Miami.

Developmental Psychology
|October 21, 2016
PubMed
Summary
This summary is machine-generated.

Different statistical models reveal distinct insights into within-person developmental effects. This study clarifies these intraindividual relationships, showing how model choice impacts conclusions about developmental processes.

More Related Videos

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.4K
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

Related Experiment Videos

Last Updated: Mar 13, 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

6.8K
The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.4K
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

Area of Science:

  • Developmental Psychology
  • Quantitative Psychology
  • Longitudinal Data Analysis

Background:

  • Researchers often use multivariate models to study intraindividual changes in constructs over time.
  • Existing models test distinct types of within-person effects, leading to varied developmental inferences.
  • Previous work focused on the existence of these effects, not their nature.

Purpose of the Study:

  • To clarify the specific within-person inferences derivable from different multivariate models.
  • To compare how distinct modeling approaches characterize concurrent developmental processes.
  • To provide a framework for interpreting seemingly contradictory findings in developmental research.

Main Methods:

  • Comparative analysis of distinct multivariate statistical models.
  • Application of models to an empirical example of mother-child relationship development.
  • Investigation of concurrent changes in mother-child closeness and conflict.

Main Results:

  • Different models yield fundamentally different conclusions about intraindividual developmental processes.
  • The choice of model significantly influences the interpretation of developmental relationships.
  • A framework is presented to reconcile divergent findings across models.

Conclusions:

  • Understanding the specific within-person effects each model assesses is crucial for accurate developmental interpretation.
  • Researchers must carefully select models to align with their specific developmental questions.
  • The study offers a method for making sense of varied results in longitudinal developmental research.