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

Multiple Comparison Tests01:13

Multiple Comparison Tests

4.3K
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.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
4.3K
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

454
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
454
Bonferroni Test01:10

Bonferroni Test

3.1K
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.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
3.1K
Reliability and Validity01:29

Reliability and Validity

13.5K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
13.5K
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

3.7K
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...
3.7K
Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test01:09

Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test

4.3K
In parametric statistics, two fundamental tests stand out for their utility and wide application: the Student's t-test and goodness-of-fit tests. These tests provide researchers with a robust method for drawing insights from data, testing hypotheses, and making informed decisions based on their findings.
The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with...
4.3K

You might also read

Related Articles

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

Sort by
Same author

Biochemical profiling and symptomatology of androgen deficiency in males with cluster headache: A prospective case-control study.

Headacheยท2026
Same authorSame journal

Long-term Cancer Risk in Acromegaly: A Population-Based Cohort Study with 44 Years of Follow-up.

European journal of endocrinologyยท2026
Same author

Methodological innovations to advance substance use disorder research: Proceedings of a NIDA workshop on target trial emulation and translational testing of digital health tools.

Journal of substance use and addiction treatmentยท2026
Same author

Early Prediction Model for Retinopathy of Prematurity Using Placental and Neonatal Risk Factors.

Investigative ophthalmology & visual scienceยท2026
Same author

The effect of selective decontamination on antimicrobial resistance in intensive care patients: a systematic review and meta-analysis.

Scientific reportsยท2026
Same author

An observational diagnostic accuracy study comparing the urine dipstick with a consensus-based reference standard for the diagnosis of urinary tract infections in older adults.

BMC geriatricsยท2026

Related Experiment Video

Updated: Nov 26, 2025

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
16:23

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

14.7K

Multiple testing: when is many too much?

Rolf H H Groenwold1,2, Jelle J Goeman2, Saskia Le Cessie1,2

  • 1Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

European Journal of Endocrinology
|December 10, 2020
PubMed
Summary
This summary is machine-generated.

Medical research often involves testing multiple hypotheses, increasing the risk of false-positive results. This overview discusses multiple testing and methods to reduce these errors in scientific studies.

More Related Videos

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats
09:12

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats

Published on: March 17, 2019

9.7K
A Protocol of Manual Tests to Measure Sensation and Pain in Humans
07:28

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Published on: December 19, 2016

21.4K

Related Experiment Videos

Last Updated: Nov 26, 2025

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
16:23

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

14.7K
Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats
09:12

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats

Published on: March 17, 2019

9.7K
A Protocol of Manual Tests to Measure Sensation and Pain in Humans
07:28

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Published on: December 19, 2016

21.4K

Area of Science:

  • Medical research
  • Biostatistics
  • Clinical trials

Background:

  • Most medical research involves testing multiple hypotheses or estimating multiple relationships simultaneously.
  • This practice, known as multiple testing, significantly elevates the probability of obtaining false-positive conclusions.

Discussion:

  • The phenomenon of multiple testing is a critical consideration in statistical analysis.
  • Understanding and addressing multiple testing is essential for the validity of research findings.

Key Insights:

  • Increased hypothesis testing directly correlates with a higher risk of false positives.
  • Methods exist to mitigate the risks associated with multiple testing in research.

Outlook:

  • Future research should emphasize robust statistical approaches to manage multiple testing.
  • Implementing strategies to control false-positive rates will enhance the reliability of medical evidence.