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

Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

3.2K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
3.2K
Testing a Claim about Mean: Known Population SD01:11

Testing a Claim about Mean: Known Population SD

3.4K
A complete procedure of testing the hypothesis about a population mean is explained here.
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
3.4K
Ratio Level of Measurement00:54

Ratio Level of Measurement

22.5K
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....
22.5K
Testing a Claim about Mean: Unknown Population SD01:21

Testing a Claim about Mean: Unknown Population SD

6.5K
A complete procedure of testing a hypothesis about a population mean when the population standard deviation is unknown is explained here.
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...
6.5K
Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

55.9K
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...
55.9K
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

9.1K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
9.1K

You might also read

Related Articles

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

Sort by
Same author

Digital cognitive behavioral therapy and peer support for adolescents and young adults with sickle cell disease and chronic pain: study protocol of a parallel, three-arm, randomized controlled trial (PRESENCE).

Trials·2026
Same author

Benefits of Electronic Symptom Monitoring During Cancer Treatment by Age, Sex, Race, and Education (Alliance AFT-39).

JCO oncology practice·2026
Same author

What patients would have liked to have known in advance about physical function due to cancer treatment.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer·2026
Same author

Evaluating different scoring algorithms to assess communication ability for individuals living with Angelman syndrome: the Observer-Reported Communication Ability (ORCA) measure.

Journal of patient-reported outcomes·2026
Same author

Correction: Identifying High-Priority Ecological-Level Indicators of Structural Racism in Black and Hispanic/Latino Communities.

Journal of racial and ethnic health disparities·2026
Same author

Frailty phenotype in adults with sickle cell disease.

The journals of gerontology. Series A, Biological sciences and medical sciences·2026

Related Experiment Video

Updated: Apr 8, 2026

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

5.1K

Estimating minimally important difference (MID) in PROMIS pediatric measures using the scale-judgment method.

David Thissen1, Yang Liu2, Brooke Magnus3

  • 1Department of Psychology, University of North Carolina at Chapel Hill, 358 Davie Hall, CB #3270, Chapel Hill, NC, 27599, USA. dthissen@email.unc.edu.

Quality of Life Research : an International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation
|June 30, 2015
PubMed
Summary

Minimally important differences (MIDs) for Patient-Reported Outcomes Measurement Information System (PROMIS) pediatric measures were assessed. Clinician data suggested a 2-point MID, while adolescent and parent data indicated a 3-point MID on the PROMIS T-score scale.

Keywords:
Item response theoryMinimally important differencePROMISPatient-reported outcomesPediatricsSelf-report

More Related Videos

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

3.1K
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

28.1K

Related Experiment Videos

Last Updated: Apr 8, 2026

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

5.1K
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

3.1K
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

28.1K

Area of Science:

  • Health Outcomes Research
  • Pediatric Health Measurement
  • Psychometrics

Background:

  • The Patient-Reported Outcomes Measurement Information System (PROMIS) provides item banks for pediatric self-report measures.
  • Establishing minimally important differences (MIDs) is crucial for interpreting changes in health status using PROMIS measures.

Purpose of the Study:

  • To determine the minimally important differences (MIDs) for pediatric self-report item banks within the PROMIS framework.
  • To provide benchmarks for detecting meaningful changes in health for children using PROMIS measures.

Main Methods:

  • Judges (adolescents, parents, clinicians) evaluated vignettes with paired PROMIS questionnaires.
  • Judges indicated whether an important change in health status was observed.
  • Item response theory was used to estimate MIDs based on 50% agreement among judges.

Main Results:

  • A total of 246 judges participated, including adolescents, parents, and clinicians.
  • The estimated MID was approximately 2 points on the PROMIS T-score scale when using clinician data.
  • The estimated MID was approximately 3 points on the PROMIS T-score scale when using adolescent and parent data.

Conclusions:

  • The established MIDs enhance the interpretability of PROMIS pediatric measures in clinical research.
  • These MIDs facilitate the identification of clinically meaningful changes in health status over time for pediatric populations.
  • The findings support the use of PROMIS measures for tracking health changes in children and adolescents.