Related Experiment Video
Updated: Jan 13, 2026

10:39
Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
Published on: August 29, 2025
1.1K
Do EQ-5D-Y-3L value sets have common properties, and how do they compare to EQ-5D-5L value sets?
Bram Roudijk1,2, Tianxin Pan3, Jan Abel Olsen4
1EuroQol Research Foundation, Marten Meesweg 107, Rotterdam, 3068 AV, The Netherlands. Roudijk@euroqol.org.
Summary
This study compares EQ-5D-Y-3L value sets across 11 countries, finding both differences and similarities in health valuation. Children
Area of Science:
- Health Economics
- Psychometrics
- Patient-Reported Outcomes
Background:
- Numerous EQ-5D-Y-3L value sets are available globally.
- This presents an opportunity to compare international differences and similarities.
Purpose of the Study:
- To compare EQ-5D-Y-3L value sets across 11 countries.
- To assess similarities between EQ-5D-Y-3L and EQ-5D-5L value sets.
Main Methods:
- Reviewed 11 EQ-5D-Y-3L value set publications.
- Assessed similarities using kernel density plots and other characteristics.
- Compared EQ-5D-Y-3L and EQ-5D-5L value sets from the same countries.
Main Results:
- All studies used the same discrete choice experiment (DCE) design.
- Analytical strategies varied; values for state 33333 ranged from -0.691 to 0.289.
- Pain/discomfort consistently received the largest weight; self-care the smallest in most studies.
- European and Asian value sets showed similarities, as did Australian and Brazilian sets to Asian sets.
Conclusions:
- Substantial differences exist in EQ-5D-Y-3L value set scales, but striking similarities in weighting (e.g., pain/discomfort).
- EQ-5D-Y-3L values suggest lower willingness to trade life years for quality of life in children compared to adults (EQ-5D-5L).
Related Concept Videos
Ordinal Level of Measurement
31.9K
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.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
31.9K
Bioequivalence Data: Statistical Interpretation
190
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...
190
Ratio Level of Measurement
20.5K
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....
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....
20.5K
Estimation of the Physical Quantities
7.2K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
7.2K
5-Number Summary
5.5K
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...
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...
5.5K
Interval Level of Measurement
17.9K
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...
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...
17.9K

