Jove
Visualize
Contact Us

Related Concept Videos

Longitudinal Studies01:26

Longitudinal Studies

428
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...
428
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

213
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...
213
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

459
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...
459
Longitudinal Research02:20

Longitudinal Research

13.0K
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...
13.0K
Two-Way ANOVA01:17

Two-Way ANOVA

3.3K
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...
3.3K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

245
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...
245

You might also read

Related Articles

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

Sort by
Same author

Early Screening for Decoding- and Language-Related Reading Difficulties in First and Third Grades.

Assessment for effective intervention : official journal of the Council for Educational Diagnostic Services·2026
Same author

Adolescent Sexting in Romantic Relationships and Daily Positive and Negative Affect Dynamics: A Dyadic Intensive Longitudinal Study.

Computers in human behavior·2026
Same author

A primer on intensive longitudinal psychometrics.

Behavior research methods·2026
Same author

Dynamic measurement invariance cutoffs for longitudinal and dyadic data.

Behavior research methods·2026
Same author

Evidence-based practice attitude scale for Latinx mental health professionals: a novel application of confirmatory factor analysis.

Implementation science communications·2026
Same author

Practical Implications of Sum Scores Being Psychometrics' Greatest Accomplishment.

Psychometrika·2026
Same journal

Addressing selective reporting bias in meta-analysis of dependent effect sizes: A tutorial in R.

Psychological methods·2026
Same journal

Heterogeneous variance models with Gaussian processes.

Psychological methods·2026
Same journal

Bayesian evaluation for latent variable models: A tutorial on computing information criteria and bayes factors with the r package bleval.

Psychological methods·2026
Same journal

A stochastic block prior for clustering in graphical models.

Psychological methods·2026
Same journal

Three-level vector autoregressive models.

Psychological methods·2026
Same journal

Scaling cognitive modeling to big data: A deep learning approach to studying individual differences in evidence accumulation model parameters.

Psychological methods·2026
See all related articles
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 Experiment Video

Updated: Jan 1, 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

6.7K

A primer on two-level dynamic structural equation models for intensive longitudinal data in Mplus.

Daniel McNeish1, Ellen L Hamaker2

  • 1Department of Psychology, Arizona State University.

Psychological Methods
|December 20, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces time-series analysis for psychological research, covering single-subject (N=1) to complex multi-person models. It aims to equip researchers with foundational knowledge for advanced statistical modeling in psychology.

More Related Videos

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.2K
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

3.6K

Related Experiment Videos

Last Updated: Jan 1, 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

6.7K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.2K
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

3.6K

Area of Science:

  • Psychology
  • Statistics
  • Data Science

Background:

  • Intensive longitudinal data collection is increasing due to technological advances.
  • Statistical methods for modeling such data are rapidly evolving.
  • Time-series analysis, crucial for longitudinal data, is underrepresented in psychology resources.

Purpose of the Study:

  • To introduce fundamental concepts of time-series analysis for psychological researchers.
  • To bridge the gap in psychology-specific resources for analyzing intensive longitudinal data.
  • To facilitate understanding and application of advanced dynamic structural equation models.

Main Methods:

  • Starts with basic N=1 time-series analysis.
  • Progresses to complex dynamic structural equation models (e.g., in Mplus Version 8).
  • Provides conceptual understanding, template code, and guidance on result interpretation.

Main Results:

  • Offers a foundational knowledge base for time-series analysis in psychology.
  • Aims to make advanced statistical literature more accessible to a broader research audience.
  • Enhances researchers' ability to model intensive longitudinal data.

Conclusions:

  • There is a need for accessible resources on time-series analysis in psychology.
  • This work provides a stepping stone for researchers to engage with complex longitudinal data modeling.
  • Improved understanding of time-series analysis can advance psychological research methodologies.