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

64
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...
64
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

293
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
293
Group Design02:01

Group Design

9.0K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
9.0K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

119
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
119
Randomized Experiments01:13

Randomized Experiments

7.0K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
7.0K
Longitudinal Research02:20

Longitudinal Research

12.0K
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...
12.0K

You might also read

Related Articles

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

Sort by
Same author

Clustering Individuals Based on Similarity in Idiographic Factor Loading Patterns.

Multivariate behavioral research·2024
Same author

Homogeneity Assumptions in the Analysis of Dynamic Processes.

Multivariate behavioral research·2023
Same author

Estimating both directed and undirected contemporaneous relations in time series data using hybrid-group iterative multiple model estimation.

Psychological methods·2022
Same author

Latent variable GIMME using model implied instrumental variables (MIIVs).

Psychological methods·2019
Same author

Assessing the robustness of cluster solutions obtained from sparse count matrices.

Psychological methods·2019

Related Experiment Video

Updated: Jul 18, 2025

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

5.9K

From the Individual to the Group: Using Idiographic Analyses and Two-Stage Random Effects Meta-Analysis to Obtain

Sandra A W Lee1, Kathleen M Gates1

  • 1University of North Carolina Chapel Hill.

Multivariate Behavioral Research
|August 23, 2023
PubMed
Summary

This study introduces a two-stage random effects meta-analysis (2SRE-MA) for analyzing real-time psychological data. This method effectively generates population inferences from idiographic, within-person observational time series data.

Keywords:
GIMMESVARVARaggregating idiographic resultsintensive longitudinal dataperson-specific analysespsychological networkstime series meta-analysistwo-stage random effects meta-analysis (2SRE-MA)

More Related Videos

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
06:26

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

Published on: November 27, 2019

71.3K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

585

Related Experiment Videos

Last Updated: Jul 18, 2025

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

5.9K
Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
06:26

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

Published on: November 27, 2019

71.3K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

585

Area of Science:

  • Psychology
  • Data Science
  • Behavioral Science

Background:

  • Increasing use of portable technology and wearable devices for psychological data collection.
  • Generation of large volumes of real-time, observational time series data.
  • Need for analytical approaches that address heterogeneity and non-ergodicity in within-person processes.

Purpose of the Study:

  • To present meta-analysis techniques for idiographic analyses of within-person processes.
  • To advocate for and demonstrate a two-stage random effects meta-analysis (2SRE-MA) for observational time series data.
  • To align novel implementations with calls for idiographic approaches in population-level inferences.

Main Methods:

  • Application of one-stage and two-stage random effects meta-analysis.
  • Focus on single-subject observational time series data.
  • Demonstration using an empirical example, contrasting with prior implementations on short time series.

Main Results:

  • The two-stage random effects meta-analysis (2SRE-MA) is presented as a preferred method for observational time series data.
  • The study provides a novel implementation of 2SRE-MA for longer time series.
  • The methodology effectively generates population inferences from idiographic data.

Conclusions:

  • Two-stage random effects meta-analysis (2SRE-MA) is a valuable tool for psychological research utilizing real-time data.
  • This approach supports understanding within-person processes by integrating idiographic findings.
  • The study contributes a practical implementation for analyzing complex psychological time series data.