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

Errors In Hypothesis Tests01:14

Errors In Hypothesis Tests

4.4K
When performing a hypothesis test, there are four possible outcomes depending on the actual truth (or falseness) of the null hypothesis and the decision to reject or not.
4.4K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

153
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
153
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

242
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%...
242
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

237
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...
237
Guidelines for Writing Outcome01:11

Guidelines for Writing Outcome

2.8K
When developing expected outcomes for a patient care plan, the nurse should adhere to the following recommendations:
Patient outcomes reflect the patient's response to the goal rather than what the nurse aims to achieve. Terminology should be observable and measurable to avoid the reader's interpretation. The desired outcome should be realistic and achievable in the designated care timeframe. Expected outcomes should align with adjunctive therapies. The outcome should enhance care...
2.8K
Crossover Experiments01:16

Crossover Experiments

2.9K
Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
2.9K

You might also read

Related Articles

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

Sort by
Same author

Gaming the peer review system: Evidence for a review mill in medicine highlights the need to ensure reviewer integrity.

Accountability in research·2026
Same author

A Delphi survey on attitudes to serious research misconduct: Exploring convergence vs. polarization of views of research "sleuths" and research integrity experts.

Accountability in research·2026
Same author

What does lack of language lateralization signify? Evidence of fluctuating asymmetry rather than hemispheric equipoise on non-lateralized tasks.

Royal Society open science·2024
Same author

Approaches to Measuring Language Lateralisation: An Exploratory Study Comparing Two fMRI Methods and Functional Transcranial Doppler Ultrasound.

Neurobiology of language (Cambridge, Mass.)·2024
Same author

Comment on Le Floch & Ropars (2017) 'Left-right asymmetry of the Maxwell spot centroids in adults without and with dyslexia'.

Proceedings. Biological sciences·2024
Same author

Laterality indices consensus initiative (LICI): A Delphi expert survey report on recommendations to record, assess, and report asymmetry in human behavioural and brain research.

Laterality·2023
Same journal

Sentiment Analysis of Acceptance TVET Online Courses on the Skill Academy App from Google Play: Leveraging Text Mining with Comparison Machine Learning Model.

F1000Research·2026
Same journal

Emotional intelligence: An important skill to learn now more than ever.

F1000Research·2026
Same journal

East Mediterranean Lineage of <i>Brucella melitensis</i> in Human Isolates and Milk Samples in Oman Using MLVA-14.

F1000Research·2026
Same journal

Application of K-Means Clustering for Job Applicant Analysis in Construction Firms Using R.

F1000Research·2026
Same journal

The influence of self-esteem and emotional intelligence on addiction to social networks in Peruvian university students.

F1000Research·2026
Same journal

A Bibliometric Analysis of Music's Role in Promoting Well-Being in Health Science Research.

F1000Research·2026
See all related articles

Related Experiment Video

Updated: Aug 6, 2025

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

4.0K

Using multiple outcomes in intervention studies: improving power while controlling type I errors.

Dorothy V M Bishop1

  • 1Department of Experimental Psychology, University of Oxford, Oxford, Oxon, OX2 6GG, UK.

F1000Research
|November 9, 2023
PubMed
Summary
This summary is machine-generated.

Using multiple outcomes in clinical trials can improve efficiency. The Adjust NVar approach controls error rates, offering a better balance of power and type I error than single outcomes for studies with several correlated measures.

Keywords:
correlated outcomesfamilywise error rateinterventionmethodologymultiple comparisonspowerstatistics

More Related Videos

Author Spotlight: Repetitive Transcranial Magnetic Stimulation Combined with Movement Observation in Cerebral Palsy
07:20

Author Spotlight: Repetitive Transcranial Magnetic Stimulation Combined with Movement Observation in Cerebral Palsy

Published on: August 9, 2024

1.3K
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

632

Related Experiment Videos

Last Updated: Aug 6, 2025

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

4.0K
Author Spotlight: Repetitive Transcranial Magnetic Stimulation Combined with Movement Observation in Cerebral Palsy
07:20

Author Spotlight: Repetitive Transcranial Magnetic Stimulation Combined with Movement Observation in Cerebral Palsy

Published on: August 9, 2024

1.3K
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

632

Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Significance

Background:

  • CONSORT guidelines recommend a single primary outcome to minimize false positives.
  • Multiple outcomes can be used if the familywise error rate is controlled.
  • Controlling error involves specifying a threshold (N) for significant outcomes based on their number and correlation.

Purpose of the Study:

  • To explore an alternative to single primary outcomes in intervention studies.
  • To develop a method for controlling familywise error rate with multiple outcomes.
  • To assess the efficiency of using multiple correlated outcomes versus a single outcome.

Main Methods:

  • Simulations used null-hypothesis significance testing with alpha = .05.
  • Examined 2-12 outcome measures, correlations from 0 to .8, and effect sizes from 0 to .7.
  • Developed the Adjust NVar approach, calculating minimum significant outcomes (MinNSig) to control the familywise error rate at 5%.

Main Results:

  • The Adjust NVar approach demonstrated a more efficient trade-off between statistical power and type I error rate.
  • This efficiency was observed when using three or more moderately intercorrelated outcome variables.
  • Compared to single-outcome studies, Adjust NVar showed improved performance under specific conditions.

Conclusions:

  • Employing a suite of moderately correlated outcome measures can be more efficient than a single primary outcome in intervention studies.
  • This approach provides internal replication within a study.
  • The Adjust NVar method can also be applied to evaluate existing intervention studies.