Jove
Visualize
Contact Us

Related Concept Videos

Cluster Sampling Method01:20

Cluster Sampling Method

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...
Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...

You might also read

Related Articles

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

Sort by
Same author

Sociodemographic and political factors associated with COVID-19 mortality in Brazilian municipalities across three years: An approach supported by Gaussian Mixture clustering.

Spatial and spatio-temporal epidemiology·2025
Same author

Lessons from the historical dynamics of environmental law enforcement in the Brazilian Amazon.

Scientific reports·2024
Same author

A Data-Driven Framework for Small Hydroelectric Plant Prognosis Using Tsfresh and Machine Learning Survival Models.

Sensors (Basel, Switzerland)·2023
Same author

Spatial distribution of sedentary behavior and unhealthy eating habits in Belo Horizonte, Brazil: the role of the neighborhood environment.

Ciencia & saude coletiva·2022
Same author

Spatial analysis of leisure-time physical activity in an urban area.

Revista brasileira de epidemiologia = Brazilian journal of epidemiology·2021
Same author

Full scale composting of food waste and tree pruning: How large is the variation on the compost nutrients over time?

The Science of the total environment·2020
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 Experiment Video

Updated: May 21, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Optimal selection of the spatial scan parameters for cluster detection: a simulation study.

Sérgio Henrique Rodrigues Ribeiro1, Marcelo Azevedo Costa

  • 1Department of Statistics, Universidade Federal de Minas Gerais, Belo Horizonte, MG 31270-901, Brazil.

Spatial and Spatio-Temporal Epidemiology
|June 12, 2012
PubMed
Summary

Analyzing spatial scan statistics, this study found that secondary cluster analysis does not improve hot-spot detection on average. However, a variable maximum cluster size, as used in the double scan statistic, enhances performance and positive predictive values.

More Related Videos

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

Related Experiment Videos

Last Updated: May 21, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

Area of Science:

  • Spatial statistics
  • Epidemiology
  • Geographic information systems

Background:

  • Spatial scan statistics are crucial for identifying disease clusters.
  • Selecting an appropriate maximum cluster size is a key parameter.
  • The utility of secondary cluster analysis for irregular or missed primary clusters is debated.

Purpose of the Study:

  • To evaluate the performance of circular, elliptic, and double spatial scan statistics.
  • To assess the impact of maximum cluster size and secondary cluster analysis on detection accuracy.
  • To determine if secondary cluster analysis improves the identification of true unknown clusters.

Main Methods:

  • Comparison of circular, elliptic, and double scan statistics.
  • Systematic variation of maximum cluster size parameter.
  • Evaluation of different approaches for analyzing significant secondary clusters.
  • Empirical performance assessment for hot-spot clusters.

Main Results:

  • Secondary cluster analysis did not significantly improve the average detection of true hot-spot clusters.
  • A variable maximum cluster size demonstrated improved performance.
  • The double scan statistic, utilizing an early-stopping procedure, enhanced positive predictive values.

Conclusions:

  • For hot-spot clusters, secondary cluster analysis offers limited average improvement in detecting the primary cluster.
  • Variable maximum cluster size strategies, like the double scan statistic, enhance detection performance.
  • The double scan statistic's early-stopping mechanism positively impacts predictive accuracy.