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 Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

438
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...
438
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

359
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...
359
Law of Independent Assortment02:03

Law of Independent Assortment

46.6K
While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.
46.6K
Binomial Probability Distribution01:15

Binomial Probability Distribution

13.1K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
13.1K
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

729
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
729
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

2.9K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
2.9K

You might also read

Related Articles

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

Sort by
Same author

Regional, functional and transcriptomic decoding of multidimensional brain structure alterations in obsessive-compulsive disorder.

Nature communications·2026
Same author

Brain age prediction in generalized anxiety disorder using a convolutional neural network.

Translational psychiatry·2026
Same author

The methodological foundations of lesion network mapping remain sound.

bioRxiv : the preprint server for biology·2026
Same author

ADHD symptom trajectories and brain morphometry: A longitudinal analysis.

medRxiv : the preprint server for health sciences·2026
Same author

Diffusion Magnetic Resonance Imaging of Cortical Microstructure Differs in Nonmanifest and Manifest Genetic Parkinson's Disease.

Movement disorders : official journal of the Movement Disorder Society·2026
Same author

Periductal iron-corrected T1 is a predictor of adverse outcomes in large-duct primary sclerosing cholangitis.

BMC medical imaging·2026
Same journal

Segmentation of the parasagittal dura mater on multi-center 3D-FLAIR MRI.

NeuroImage·2026
Same journal

Spatial frequency channels implement a mental ruler in spatial vision.

NeuroImage·2026
Same journal

Exploring the Link Between Intravoxel Incoherent Motion Measured Brain Diffusivity During Wakefulness and Sleep Macrostructure in the Elderly.

NeuroImage·2026
Same journal

Closed-loop adaptation of transcranial magnetic stimulation intensity with electroencephalography feedback.

NeuroImage·2026
Same journal

Volumetric postmortem MRI of the medial temporal lobe in Alzheimer's disease and related disorders: methodological advances and implications for in vivo biomarker development.

NeuroImage·2026
Same journal

Neural responses to equity and inequity when receiving vicarious rewards for self and charity during adolescence.

NeuroImage·2026
See all related articles

Related Experiment Video

Updated: May 3, 2026

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

2.9K

Permutation inference for the general linear model.

Anderson M Winkler1, Gerard R Ridgway2, Matthew A Webster3

  • 1Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, UK; Global Imaging Unit, GlaxoSmithKline, London, UK; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.

Neuroimage
|February 18, 2014
PubMed
Summary
This summary is machine-generated.

Approximate permutation methods offer flexible control of false positives in neuroimaging research. These advanced techniques provide powerful and reliable statistical inference for complex experimental designs, even with nuisance variables.

Keywords:
General linear modelMultiple regressionPermutation inferenceRandomise

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

6.1K
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

5.8K

Related Experiment Videos

Last Updated: May 3, 2026

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

2.9K
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

6.1K
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

5.8K

Area of Science:

  • Neuroimaging research
  • Statistical inference
  • Computational neuroscience

Background:

  • Permutation methods offer precise control of false positives and flexible statistical analysis.
  • Traditional permutation methods can lack flexibility for complex experimental designs and nuisance variables.

Purpose of the Study:

  • To investigate approximate permutation methods for enhanced flexibility in neuroimaging.
  • To identify optimal permutation strategies for typical imaging research scenarios.
  • To present a general framework for permutation inference in complex general linear models (GLMs).

Main Methods:

  • Detailed simulations were conducted to evaluate various approximate permutation methods.
  • A generic framework for permutation inference in GLMs with exchangeable or symmetric error distributions was developed.
  • The 'randomise' algorithm was implemented for permutation inference with GLMs.

Main Results:

  • Approximate permutation methods demonstrate flexibility with experimental designs and nuisance variables.
  • Permutation inferences provide powerful results with excellent false positive control in common neuroimaging scenarios.
  • The methods are effective even when data independence assumptions are violated in specific cases.

Conclusions:

  • Approximate permutation methods are a powerful and flexible tool for neuroimaging statistical inference.
  • The proposed framework and 'randomise' algorithm offer robust control of false positives in complex GLMs.
  • These methods enhance the reliability of findings in neuroimaging research by accommodating complex designs.