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

Random and Systematic Errors01:20

Random and Systematic Errors

11.1K
Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
11.1K
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

1.5K
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
1.5K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

74.0K
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. 
74.0K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

1.7K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
1.7K
Errors and Mistakes in Surveying01:19

Errors and Mistakes in Surveying

123
Errors and mistakes in surveying refer to inaccuracies in measurements and data recording. The errors are deviations from the actual value caused by human sensory limitations, equipment flaws, or environmental effects. These errors are typically unintentional and can result from the inherent imperfections in the instruments used, atmospheric conditions, or the observer’s inability to perceive exact measurements. On the other hand, mistakes are caused by the surveyor's lack of...
123
Random Error01:04

Random Error

932
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
932

You might also read

Related Articles

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

Sort by
Same author

The Role of Intention, Behavioral Regulation, and Physical Activity Behavior in the Prediction of Physical Activity Identity across Time.

Behavioral sciences (Basel, Switzerland)·2024
Same author

The case for the curve: Parametric regression with second- and third-order polynomial functions of predictors should be routine.

Psychological methods·2023
Same author

Theoretical considerations when simulating data from the g-and-h family of distributions.

The British journal of mathematical and statistical psychology·2022
Same author

The Importance of Thinking Multivariately When Setting Subscale Cutoff Scores.

Educational and psychological measurement·2022
Same author

How to think clearly about the central limit theorem.

Psychological methods·2022
Same author

Measurement protocols, random-variable-valued measurements, and response process error: Estimation and inference when sample data are not deterministic.

PloS one·2020

Related Experiment Video

Updated: Jul 25, 2025

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

6.9K

Generalized measurement error: Intrinsic and incidental measurement error.

Edward Kroc1

  • 1Measurement, Evaluation, and Research Methodology, University of British Columbia, Vancouver, British Columbia, Canada.

Plos One
|June 29, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces two new types of measurement error (intrinsic and incidental) for random-valued data. It generalizes classical error models and statistical theories to this broader measurement domain.

More Related Videos

Assessment of Child Anthropometry in a Large Epidemiologic Study
09:36

Assessment of Child Anthropometry in a Large Epidemiologic Study

Published on: February 2, 2017

27.1K
Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

4.5K

Related Experiment Videos

Last Updated: Jul 25, 2025

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

6.9K
Assessment of Child Anthropometry in a Large Epidemiologic Study
09:36

Assessment of Child Anthropometry in a Large Epidemiologic Study

Published on: February 2, 2017

27.1K
Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

4.5K

Area of Science:

  • Statistics
  • Measurement Theory
  • Data Science

Background:

  • Traditional measurement error models apply to deterministic data.
  • Handling random-variable-valued data requires new approaches to measurement error.

Purpose of the Study:

  • To generalize measurement error concepts for random-variable-valued data.
  • To introduce intrinsic and incidental measurement error.
  • To extend classical statistical methods to this new data domain.

Main Methods:

  • Formulation of intrinsic and incidental measurement error.
  • Definition of calibrating conditions for generalized error models.
  • Exploration of generalized point estimation, inference, and likelihood theory.

Main Results:

  • Distinction between intrinsic and incidental measurement error.
  • Generalization of classical measurement error models, including Berkson error.
  • Adaptation of statistical inference for random-variable-valued measurements.

Conclusions:

  • The proposed framework accommodates a broader range of measurement data.
  • Generalized statistical theories provide tools for analyzing complex measurement processes.
  • This work advances the understanding and modeling of measurement error in diverse applications.