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

Cluster Sampling Method01:20

Cluster Sampling Method

14.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
14.9K
Vesicular Tubular Clusters01:45

Vesicular Tubular Clusters

3.3K
After budding out from the ER membrane, some COPII vesicles lose their coat and fuse with one another to form larger vesicles and interconnected tubules called vesicular tubular clusters or VTCs. These clusters constitute a compartment at the ER-Golgi interface known as ERGIC (Endoplasmic Reticulum Golgi Intermediate Compartment). The ERGIC is a mobile membrane-bound cargo transport system that sorts proteins secreted from ER and delivers them to the Golgi.
With the help of motor proteins such...
3.3K
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

256
Body:Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to...
256
Random Sampling Method01:09

Random Sampling Method

15.1K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
15.1K
Design Example: Maintaining Level of an Embankment01:19

Design Example: Maintaining Level of an Embankment

448
Constructing a roadway embankment over uneven terrain requires precise leveling to ensure stability and proper drainage. Surveyors use a leveling instrument and staff to calculate ground elevations and determine the required fill material at each point along the embankment alignment.The process begins by positioning a leveling instrument near a benchmark with a known elevation. A backsight reading establishes the instrument height, which serves as a reference for subsequent measurements. A...
448
Group Design02:01

Group Design

10.8K
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...
10.8K

You might also read

Related Articles

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

Sort by
Same author

Navigating evidence-informed decision making for arboviral disease control in Pacific Island countries.

BMC global and public health·2026
Same author

Pilot Study: Vancomycin Calcium Sulfate Beads in the Prevention of Recurrent Capsular Contracture of Breast Implants.

Plastic and reconstructive surgery. Global open·2026
Same author

Test-Negative Designs With Multiple Testing Sources.

Statistics in medicine·2026
Same author

The association between adherence to elective nodal volume guidelines and reduced distant metastasis in esophageal and gastroesophageal junction cancer: a retrospective analysis of elective nodal irradiation.

Journal of gastrointestinal oncology·2026
Same author

Integrated validation of internally controlled one-step multiplex real-time RT-PCR for dengue virus serotyping and monoplex assay for quantification.

Journal of virological methods·2026
Same author

The impact of large-scale release of <i>Wolbachia</i> mosquitoes on dengue incidence in Campo Grande, Brazil: an ecological study.

Lancet regional health. Americas·2025

Related Experiment Video

Updated: Feb 14, 2026

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.9K

Analysis of cluster-randomized test-negative designs: cluster-level methods.

Nicholas P Jewell1, Suzanne Dufault1, Zoe Cutcher2

  • 1Division of Biostatistics, School of Public Health, University of California, Berkeley, CA 94720, USA.

Biostatistics (Oxford, England)
|February 16, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a cluster-randomized test-negative design for evaluating vector control interventions at a community level. This method helps reduce bias from healthcare-seeking behavior when assessing disease reduction, such as dengue.

Keywords:
Case-controlCluster-randomized trialsOdds ratioTest-negative design

More Related Videos

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.7K
Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore
06:01

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore

Published on: December 12, 2019

9.0K

Related Experiment Videos

Last Updated: Feb 14, 2026

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.9K
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.7K
Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore
06:01

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore

Published on: December 12, 2019

9.0K

Area of Science:

  • Epidemiology
  • Biostatistics
  • Vector-borne disease control

Background:

  • Community-level randomization is crucial for vector control trials.
  • Healthcare-seeking behavior can confound disease ascertainment in intervention studies.
  • The test-negative design mitigates confounding in individual-level efficacy assessments.

Purpose of the Study:

  • To introduce a cluster-randomized test-negative design for group-level intervention randomization.
  • To propose and evaluate methods for estimating relative risk (RR) in this design.
  • To address confounding in vector control trials using a novel design.

Main Methods:

  • Development of a cluster-randomized test-negative design.
  • Proposal of estimation and inference methods based on randomization distributions.
  • Permutation of intervention assignment across randomly selected clusters.
  • Simulation study to assess the performance of proposed techniques.

Main Results:

  • The proposed methods provide a framework for analyzing cluster-randomized trials with a test-negative design.
  • The simulation study evaluates the accuracy and efficiency of the estimation and inference techniques.
  • The design is applicable to interventions like Wolbachia-infected mosquito releases for dengue control.

Conclusions:

  • The cluster-randomized test-negative design is a valuable tool for robust evaluation of community-level public health interventions.
  • This approach effectively addresses confounding from healthcare-seeking behavior in vector control studies.
  • The proposed inferential methods offer reliable estimation of intervention efficacy in complex trial settings.