Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Statistical Analysis: Overview

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...

Uncertainty in Measurement: Reading Instruments

Uncertainty in Measurement: Reading Instruments

Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...

Variability: Analysis

Variability: Analysis

Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...

Ratio Level of Measurement

Ratio Level of Measurement

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.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated. For...

Interval Level of Measurement

Interval Level of Measurement

For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between the...

Accuracy and Precision

Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. Highly accurate measurements...

You might also read

Related Articles

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

Sort by

Same author

Clinical and HLA Associations of Fluoroquinolone-Induced Liver Injury: Results From the Drug-Induced Liver Injury Network.

The American journal of gastroenterology·2025

Same author

Liver Injury due to Intravenous Methylprednisolone in the Drug-Induced Liver Injury Network.

Liver international : official journal of the International Association for the Study of the Liver·2025

Same author

Comparison of Measures of Pain Intensity During Sickle Cell Disease Vaso-Occlusive Episodes.

The journal of pain·2024

Same author

A comparison of the effect of patient-specific versus weight-based protocols to treat vaso-occlusive episodes in the emergency department.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine·2023

Same author

Identification of Reduced ERAP2 Expression and a Novel HLA Allele as Components of a Risk Score for Susceptibility to Liver Injury Due to Amoxicillin-Clavulanate.

Gastroenterology·2022

Same author

Multiparametric Quantitative Imaging Biomarker as a Multivariate Descriptor of Health: A Roadmap.

Academic radiology·2022

Search research articles

Related Experiment Video

Updated: Jul 13, 2026

Doppler Ultrasound-Based Leg Blood Flow Assessment During Single-Leg Knee-Extensor Exercise in an Uncontrolled Setting

Doppler Ultrasound-Based Leg Blood Flow Assessment During Single-Leg Knee-Extensor Exercise in an Uncontrolled Setting

Published on: December 15, 2023

An overview on assessing agreement with continuous measurements.

Huiman X Barnhart¹, Michael J Haber, Lawrence I Lin

¹Department of Biostatistics and Bioinformatics and Duke Clinical Research Institute, Duke University, Durham, North Carolina 27715, USA. huiman.barnhart@duke.edu

Journal of Biopharmaceutical Statistics

|July 7, 2007

Summary

This study unifies concepts for assessing measurement agreement across disciplines. It classifies statistical methods for continuous data, aiding in understanding measurement reliability and accuracy.

More Related Videos

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

Published on: February 21, 2025

Related Experiment Videos

Last Updated: Jul 13, 2026

Doppler Ultrasound-Based Leg Blood Flow Assessment During Single-Leg Knee-Extensor Exercise in an Uncontrolled Setting

Doppler Ultrasound-Based Leg Blood Flow Assessment During Single-Leg Knee-Extensor Exercise in an Uncontrolled Setting

Published on: December 15, 2023

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

Published on: February 21, 2025

Area of Science:

Measurement science
Statistical analysis
Interdisciplinary research

Background:

Accurate measurements are foundational across scientific disciplines.
Historical work by Galton, Pearson, and Fisher established early measurement principles.
Practical measurement often involves acceptable error or unavailable true values.

Purpose of the Study:

To elucidate and contrast fundamental concepts of measurement agreement from various disciplines.
To unite these concepts under the theme of assessing closeness of observations.
To focus on continuous measurements and statistical approaches for agreement assessment.

Main Methods:

Classification of statistical approaches for assessing agreement.
Categorization into descriptive tools, unscaled summary indices, and scaled summary indices.
Consideration of various data structures and presence/absence of a reference standard.

Main Results:

Identification of three main categories of statistical methods for agreement assessment.
Development of a framework for understanding measurement agreement across different fields.
Highlighting of scaled summary indices ranging from -1 to 1.

Conclusions:

A unified approach to assessing measurement agreement is presented.
The study identifies research gaps and suggests future directions in the field.
The findings facilitate a broader understanding and application of measurement agreement techniques.