Related Experiment Video

Updated: Oct 23, 2025

Validation of a Psychosocial Intervention on Body Image in Older People: An Experimental Design
07:40

Validation of a Psychosocial Intervention on Body Image in Older People: An Experimental Design

Published on: May 31, 2021

3.5K

Belgian population norms for the EQ-5D-5L, 2018

Lisa Van Wilder1, Rana Charafeddine2, Philippe Beutels3,4

  • 1Department of Public Health and Primary Care, Ghent University, Ghent, Belgium.

Quality of Life Research : an International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation
|August 18, 2021
PubMed
Abstract

Keywords:
EQ-5DHealth inequalitiesHealth interview surveyHealth statusHealth-related quality of lifeMulti-attribute utility instrumentPopulation normsVisual analogue scale

More Related Videos

Oral Health Assessment by Lay Personnel for Older Adults08:47

Oral Health Assessment by Lay Personnel for Older Adults

Published on: February 2, 2020

13.1K
Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis06:03

Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis

Published on: February 6, 2020

6.8K

Related Concept Videos

The Bell Curve01:21

The Bell Curve

The normal probability distribution, often depicted as a symmetrical, bell-shaped curve, is fundamental in statistics and the study of natural phenomena. This pattern, famously described by mathematician Carl Friedrich Gauss, shows how data points are distributed around a central mean, with most values near the average and fewer observations occurring as they deviate further from it.
This pattern applies to many human characteristics beyond intelligence, such as height. For example, if you...
452
Quartile01:15

Quartile

Quartiles are numbers that separate the data into quarters. Quartiles may or may not be part of the data. To find the quartiles, first, find the median or second quartile. The first quartile, Q1, is the middle value of the lower half of the data, and the third quartile, Q3, is the middle value, or median, of the upper half of the data. To get the idea, consider the same data set:
1; 1; 2; 2; 4; 6; 6.8; 7.2; 8; 8.3; 9; 10; 10; 11.5
The median or second quartile is seven. The lower half of the...
7.1K
Bioequivalence Data: Statistical Interpretation01:16

Bioequivalence Data: Statistical Interpretation

Body:The statistical interpretation of bioequivalence data is a significant aspect of pharmaceutical research. Bioequivalence refers to the absence of any significant difference in the rate and extent to which the active ingredient in pharmaceutical products becomes available at the site of drug action when administered at the same molar dose under similar conditions. This helps determine if different drug products have similar absorption rates, ensuring their interchangeability.Statistical...
22
5-Number Summary01:04

5-Number Summary

In a dataset, the 5-number summary includes the minimum data value, the data value of the first quartile, the median data value or data value of the second quartile, the data value of the third quartile, and the maximum data value. These 5 data values can be visualized as a box and whisker plot.
In a box plot, the minimum and maximum data values represent the lower and upper whiskers in the graph, and the median is designated as the center of the box in the chart. The first quartile and third...
5.2K
Estimating Population Mean with Known Standard Deviation01:16

Estimating Population Mean with Known Standard Deviation

To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
9.0K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
4.2K