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

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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, controlled...
Multiple Comparison Tests01:13

Multiple Comparison Tests

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...
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...
Group Design02:01

Group Design

The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to...
Cochran's Q Test01:17

Cochran's Q Test

Cochran's Q Test is a nonparametric statistical test used to determine if there are potential differences in the outcomes of three or more related groups on a binary (yes/no) or dichotomous outcome. It is essentially an extension of the McNemar Test, which is limited to two related samples - Cochran's Q test can handle three or more related samples, making it more versatile in scenarios where subjects are measured under multiple conditions. The test statistic follows a Chi-Square distribution,...

You might also read

Related Articles

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

Sort by
Same author

Fine particulate matter exposure and long-term lung-function trajectory in adults with cystic fibrosis.

Annals of the American Thoracic Society·2026
Same author

Approach to prevention and management of chronic lung allograft dysfunction in North American lung transplant centers.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation·2026
Same author

Comparative analysis of selective fungal culture media and incubation conditions for <i>Aspergillus fumigatus</i> in cystic fibrosis sputum.

Microbiology spectrum·2026
Same author

Assessing the Need for Reproductive Genetic Counseling Among Adults with Cystic Fibrosis.

Research square·2026
Same author

Clinical effectiveness of elexacaftor/tezacaftor/ivacaftor (ETI) in People with Cystic Fibrosis in the United States.

Annals of the American Thoracic Society·2026
Same author

Representation of Minoritized People with Cystic Fibrosis in CF Therapeutics Development Network Clinical Trials.

Annals of the American Thoracic Society·2026

Related Experiment Video

Updated: May 9, 2026

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

Comparative effectiveness research - what is it and how does one do it?

Christopher H Goss1, Nathan Tefft

  • 1Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Washington, Seattle, WA, USA. goss@u.washington.edu

Paediatric Respiratory Reviews
|July 30, 2013
PubMed
Summary

Comparative Effectiveness Research (CER) is gaining focus through federal initiatives. This review outlines CER definitions, cost roles, and essential study components for robust clinical approach comparisons.

Keywords:
Comparative effectiveness researchCost benefit analysisCost effectiveness analysisDefinitionsPaediatricsRare diseases

More Related Videos

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
08:24

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

Published on: August 25, 2023

Using a Comparative Species Approach to Investigate the Neurobiology of Paternal Responses
07:59

Using a Comparative Species Approach to Investigate the Neurobiology of Paternal Responses

Published on: September 19, 2011

Related Experiment Videos

Last Updated: May 9, 2026

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

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
08:24

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

Published on: August 25, 2023

Using a Comparative Species Approach to Investigate the Neurobiology of Paternal Responses
07:59

Using a Comparative Species Approach to Investigate the Neurobiology of Paternal Responses

Published on: September 19, 2011

Area of Science:

  • Health Services Research
  • Clinical Research Methodology

Background:

  • Growing emphasis on Comparative Effectiveness Research (CER) driven by recent initiatives.
  • Federal mandates are shaping the definition, priorities, and coordination of CER.

Purpose of the Study:

  • To review various definitions of CER.
  • To explore the role of cost assessment in CER.
  • To summarize key components of CER studies.

Main Methods:

  • Literature review summarizing definitions and components of CER.
  • Analysis of study populations, design, data sources, comparators, and outcomes.
  • Examination of CER dissemination strategies.

Main Results:

  • CER definitions are varied but focus on comparing clinical approaches.
  • Cost assessment plays a significant role in evaluating healthcare interventions.
  • Key components include appropriate populations, designs, data, comparators, and outcomes.

Conclusions:

  • Understanding CER definitions and components is crucial for effective research.
  • Dissemination of CER findings is vital for informing clinical practice and policy.