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

Ranks01:02

Ranks

318
Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
318
Ordinal Level of Measurement00:55

Ordinal Level of Measurement

28.2K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
28.2K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

341
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
341
Wilcoxon Signed-Ranks Test for Median of Single Population01:14

Wilcoxon Signed-Ranks Test for Median of Single Population

278
The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
278
Wilcoxon Rank-Sum Test01:21

Wilcoxon Rank-Sum Test

418
The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a nonparametric test used to determine if there is a significant difference between the distributions of two independent samples. This test is designed specifically for two independent populations and has the following key requirements:
418
Stratified Sampling Method01:16

Stratified Sampling Method

13.6K
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. 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.
To choose a stratified sample, divide the population into groups called strata and then take a...
13.6K

You might also read

Related Articles

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

Sort by
Same author

Leveraging injection networks to prevent HIV and other blood borne infections among people who inject drugs in Kenya: design and rationale.

BMC infectious diseases·2025
Same author

Leveraging Injection Networks to Prevent HIV and Other Blood Borne Infections Among People Who Inject Drugs in Kenya: Design and Rationale.

Research square·2025
Same author

Unsupervised Liu-type shrinkage estimators for mixture of regression models.

Statistical methods in medical research·2024
Same author

Bayesian mixture modelling with ranked set samples.

Statistics in medicine·2024
Same author

Efficient estimators with categorical ranked set samples: estimation procedures for osteoporosis.

Journal of applied statistics·2022
Same author

Wnt Site Signaling Inhibitor Secreted Frizzled-Related Protein 3 Protects Mitral Valve Endothelium From Myocardial Infarction-Induced Endothelial-to-Mesenchymal Transition.

Journal of the American Heart Association·2022

Related Experiment Video

Updated: Oct 30, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.7K

Estimation of ordinal population with multi-observer ranked set samples using ties information.

Amirhossein Alvandi1, Armin Hatefi2

  • 1Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA, USA.

Statistical Methods in Medical Research
|July 5, 2021
PubMed
Summary

This study introduces a new ranked set sampling method that effectively combines ranking information from multiple sources. This approach improves data collection and estimation for ordinal categorical data, outperforming traditional methods.

Keywords:
Ordinal categorical variablebone mineral densitymaximum likelihoodmulti-observernon-parametric estimationordinal logistic regressionosteoporosisranked set sampling

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.7K

Related Experiment Videos

Last Updated: Oct 30, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.7K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.7K

Area of Science:

  • Statistics
  • Survey Methodology
  • Data Analysis

Background:

  • Measuring study variables can be costly, necessitating efficient sampling techniques.
  • Ranked set sampling (RSS) offers an alternative to simple random sampling for obtaining representative samples.
  • Ordinal logistic regression is commonly used for RSS data but doesn't utilize ranking information during estimation.

Purpose of the Study:

  • To propose a novel ranked set sampling scheme that integrates multi-source ranking information.
  • To enhance both data collection and parameter estimation processes in surveys.
  • To develop methods for non-parametric and maximum likelihood estimation using RSS data for ordinal categorical populations.

Main Methods:

  • A new ranked set sampling scheme is proposed, incorporating combined ranking information.
  • Non-parametric and maximum likelihood estimation techniques are applied to the ranked set sampling data.
  • Extensive simulation studies are conducted to evaluate the performance of the proposed estimators.

Main Results:

  • The proposed ranked set sampling scheme effectively utilizes multi-source ranking information.
  • The new methods demonstrate improved performance in estimating parameters for ordinal categorical populations.
  • Simulation results validate the efficiency of the developed estimators.

Conclusions:

  • The novel ranked set sampling approach offers a significant advancement for surveys with costly measurements and ordinal categorical data.
  • This method enhances the utilization of available ranking information in statistical estimation.
  • The approach is applicable to real-world datasets, as demonstrated by analyses of bone disorder and obesity data.