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

Stratified Sampling Method01:16

Stratified Sampling Method

15.7K
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...
15.7K
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

6.8K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
6.8K
Sampling Plans01:23

Sampling Plans

1.1K
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...
1.1K
Bootstrapping01:24

Bootstrapping

857
The term "bootstrap" originated in the 19th century as a metaphor for self-improvement or achieving something independently, without external assistance. This concept extends to statistical bootstrapping, a self-contained method for estimating population parameters through resampling, even though it can be computationally intensive. Developed by the American statistician Dr. Bradley Efron in 1979, bootstrapping provides a robust way to perform inference when the original sample size is...
857
Systematic Sampling Method01:17

Systematic Sampling Method

13.5K
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.
Systematic sampling is one of the simplest methods...
13.5K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

4.2K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
4.2K

You might also read

Related Articles

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

Sort by
Same author

Nonparametric estimation of a biometric function using neoteric ranked set sampling with application to breast cancer data.

Journal of biopharmaceutical statistics·2026
Same author

Nonparametric Estimation of a Biometric Function Using Ranked Set Sampling With Ties Information.

Biometrical journal. Biometrische Zeitschrift·2025
Same author

Nonparametric estimation of mean residual lifetime in ranked set sampling with a concomitant variable.

Journal of applied statistics·2024
Same author

Estimation of a decreasing mean residual life based on ranked set sampling with an application to survival analysis.

The international journal of biostatistics·2024
Same author

On estimating the area under the ROC curve in ranked set sampling.

Statistical methods in medical research·2022
Same author

Estimating the area under a receiver operating characteristic curve using partially ordered sets.

The international journal of biostatistics·2020

Related Experiment Video

Updated: Feb 26, 2026

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
06:48

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Published on: June 7, 2024

2.1K

Efficient body fat estimation using multistage pair ranked set sampling.

M Mahdizadeh1, Ehsan Zamanzade2

  • 11 Department of Statistics, Hakim Sabzevari University, Sabzevar, Iran.

Statistical Methods in Medical Research
|July 19, 2017
PubMed
Summary

Multistage pair ranked set sampling offers an efficient alternative for costly measurements by reducing ranking burden. This unbiased method provides a competitive mean estimator, especially when considering costs.

Keywords:
Auxiliary informationconcomitant variablejudgment ranking

More Related Videos

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos
13:35

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos

Published on: March 21, 2021

11.9K
Biochemical and High Throughput Microscopic Assessment of Fat Mass in Caenorhabditis Elegans
16:07

Biochemical and High Throughput Microscopic Assessment of Fat Mass in Caenorhabditis Elegans

Published on: March 30, 2013

21.3K

Related Experiment Videos

Last Updated: Feb 26, 2026

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
06:48

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Published on: June 7, 2024

2.1K
Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos
13:35

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos

Published on: March 21, 2021

11.9K
Biochemical and High Throughput Microscopic Assessment of Fat Mass in Caenorhabditis Elegans
16:07

Biochemical and High Throughput Microscopic Assessment of Fat Mass in Caenorhabditis Elegans

Published on: March 30, 2013

21.3K

Area of Science:

  • Statistics
  • Survey Methodology

Background:

  • Precise measurements can be expensive.
  • Rank-based sampling is useful when ranking is cheap and measurements are costly.
  • Existing multistage ranked set sampling (MSRS) can involve significant ranking burden.

Purpose of the Study:

  • Introduce multistage pair ranked set sampling (MPRS) as a novel rank-based sampling design.
  • Mitigate the ranking burden associated with MSRS.
  • Evaluate the performance of the MPRS mean estimator.

Main Methods:

  • Developed the MPRS sampling design.
  • Derived the mean estimator for MPRS.
  • Analyzed the bias and variance properties of the MPRS mean estimator.
  • Compared MPRS with simple random sampling (SRS) and MSRS under ideal ranking conditions.

Main Results:

  • The MPRS mean estimator is unbiased.
  • Under perfect rankings, MPRS has variance no larger than SRS.
  • MPRS may outperform MSRS in precision when cost is factored in, despite MSRS being more precise under perfect rankings.
  • Demonstrated the methodology with a medical dataset.

Conclusions:

  • MPRS is a viable rank-based sampling technique that reduces ranking burden compared to MSRS.
  • MPRS offers a cost-effective approach for situations with expensive measurements.
  • The choice between MPRS and MSRS depends on the balance between ranking burden, measurement cost, and desired precision.