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5-Number Summary01:04

5-Number Summary

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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.
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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...
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Estimating an EQ-5D-Y-3L Value Set for China.

Zhihao Yang1,2, Jie Jiang3, Pei Wang4

  • 1Health Services Management Department, Guizhou Medical University, Gui'an, China. Zhihao_yang_cn@126.com.

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This study developed China's first EQ-5D-Y-3L value set using a hybrid model. A larger time trade-off (TTO) design improved the estimation of health state values for the Chinese population.

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Area of Science:

  • Health Economics
  • Psychometrics
  • Patient-Reported Outcomes

Background:

  • The EQ-5D-Y-3L is a widely used instrument for measuring health status in youth.
  • Estimating country-specific value sets is crucial for accurate health economic evaluations.
  • Previous EQ-5D-Y-3L valuations primarily used discrete choice experiment (DCE) data, with conventional time trade-off (cTTO) data for anchoring.

Purpose of the Study:

  • To develop an EQ-5D-Y-3L value set for China using the standard protocol.
  • To investigate the impact of an expanded cTTO design on value set estimation.
  • To compare different modeling strategies for integrating DCE and TTO data.

Main Methods:

  • Valuation of 28 EQ-5D-Y-3L health states using DCE and cTTO methods with independent samples.
  • Recruitment of a representative general public sample (n=1476) across 14 Chinese regions.
  • Comparison of two modeling strategies: DCE with mapping versus a joint hybrid model.

Main Results:

  • The hybrid model integrating DCE and TTO data demonstrated superior performance.
  • The selected hybrid model with an A3 term yielded significant coefficients and good prediction accuracy.
  • The developed EQ-5D-Y-3L value set for China ranged from -0.088 to 0.924.

Conclusions:

  • A robust EQ-5D-Y-3L value set for China was successfully established using a hybrid model.
  • A larger cTTO design is recommended for future EQ-5D-Y-3L valuation studies.
  • This value set will facilitate more accurate health economic evaluations in China.