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Related Concept Videos

Multiple Comparison Tests01:13

Multiple Comparison Tests

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Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
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McNemar's Test is a nonparametric statistical test used to determine if there is a significant difference in proportions between two related groups when the outcome is binary (e.g., yes/no, success/failure). It is beneficial when we have paired data, such as pre-test/post-test designs, where the same subjects are measured under two different conditions. The test is named after the statistician Quinn McNemar, who introduced it in 1947. It is commonly used in situations where subjects are...
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The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can...
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The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
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MATLAB stands for Matrix Laboratory. MathWorks developed MATLAB as a multi-paradigm numerical computing environment and proprietary programming language. It has evolved significantly over the years to become a tool utilized by engineers, scientists, and mathematicians for various tasks, including matrix calculations, developing algorithms, data analysis, and visualization. MATLAB's applications span various industries and disciplines. It's used in image and signal processing,...
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Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
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PERMUTOOLS: A MATLAB PACKAGE FOR MULTIVARIATE PERMUTATION TESTING.

Michael J Crosse1,2,3, John J Foxe3,4, Sophie Molholm3,4

  • 1Segotia, Galway, Ireland.

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Summary
This summary is machine-generated.

This study introduces PERMUTOOLS, a MATLAB package for advanced statistical analysis. It offers distribution-free permutation testing and effect size measurement, improving accuracy in quantitative research.

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Area of Science:

  • Statistics
  • Computational Statistics
  • Data Science

Background:

  • Traditional parametric statistical methods rely on population assumptions that may not hold true.
  • This can lead to inaccurate results and misinterpretations in quantitative research.
  • Resampling methods offer an alternative but often lack efficient software implementations.

Conclusions:

  • PERMUTOOLS offers a valuable tool for researchers seeking accurate and reliable statistical inference.
  • The package enhances quantitative research by providing efficient, empirically-based analytical methods.
  • Promotes the adoption of advanced resampling techniques in statistical practice.