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

Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

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 Cox...

You might also read

Related Articles

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

Sort by
Same author

Causal mediation analysis with one or multiple mediators: A comparative study.

Psychological methods·2026
Same author

NeuroConText: Contrastive learning for neuroscience meta-analysis with rich text representation.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

Individual Brain Charting: fifth release of high-resolution fMRI data for cognitive mapping.

Scientific data·2026
Same author

Subject fingerprinting and task classification rely on distinct functional connectivity features.

Brain structure & function·2026
Same author

An Interactive Brain Atlas of Knowledge.

bioRxiv : the preprint server for biology·2025
Same author

A non-monotonic code for event probability in the human brain.

Nature communications·2025

Related Experiment Video

Updated: Jul 11, 2026

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels
08:19

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

Published on: October 20, 2023

Mixed-effect statistics for group analysis in fMRI: a nonparametric maximum likelihood approach.

Alexis Roche1, Sébastien Mériaux, Merlin Keller

  • 1CEA, Neurospin, Gif-sur-Yvette, France. alexis.roche@cea.fr

Neuroimage
|September 25, 2007
PubMed
Summary

New statistical tests address estimation uncertainties in population mean effect analyses. These tests offer alternatives to the standard t statistic, enhancing accuracy in random-effect models.

More Related Videos

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

Related Experiment Videos

Last Updated: Jul 11, 2026

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels
08:19

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

Published on: October 20, 2023

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

Area of Science:

  • Statistics
  • Biostatistics
  • Neuroimaging Analysis

Background:

  • Standard t statistics in one-sample random-effect analyses may not fully account for within-subject estimation uncertainties.
  • Accurate population mean effect estimation is crucial in various scientific fields.

Purpose of the Study:

  • To introduce novel test statistics that incorporate within-subject estimation uncertainties.
  • To provide alternatives to the standard t statistic for one-sample random-effect analyses.
  • To implement these new tests in a user-friendly toolbox.

Main Methods:

  • Developed test statistics by estimating across-subject effect distributions using maximum likelihood under a nonparametric mixed-effect model.
  • Calibrated statistics using permutation tests for precise false positive control.
  • Assumed symmetry in the across-subject distribution for inference.

Main Results:

  • The proposed test statistics provide a more robust analysis by accounting for estimation uncertainties.
  • Permutation tests ensure exact false positive control under the stated symmetry assumption.
  • The Distance toolbox for SPM facilitates the application of these new methods.

Conclusions:

  • The new test statistics offer improved accuracy for population mean effect testing in random-effect models.
  • The Distance toolbox makes these advanced statistical methods accessible for researchers.
  • This work enhances statistical rigor in analyses involving complex data structures.