Related Experiment Video
Updated: Jun 12, 2026

13:04
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Published on: September 19, 2012
Deriving a Korean SF-6Dv2 Value Set Using a Discrete Choice Experiment with Duration
Eun-Young Bae1, Jahyun Cho2, Jooho Moon3
1College of Pharmacy, Gyeongsang National University, Jinju, South Korea. eybae@gnu.ac.kr.
Pharmacoeconomics
|June 11, 2026
Summary
This study derived the first Korean SF-6Dv2 value set using a discrete choice experiment. This new tool supports health economic evaluations in Korea by enabling quality-adjusted life-year calculations.
Area of Science:
- Health Economics
- Psychometrics
- Biostatistics
Background:
- The SF-6Dv2 is a valuable tool for health state valuation.
- Deriving country-specific value sets is crucial for accurate economic evaluations.
- No Korean value set for the SF-6Dv2 was previously available.
Purpose of the Study:
- To derive the first Korean value set for the SF-6Dv2.
- To enable accurate quality-adjusted life-year (QALY) calculations in Korea.
- To support health economic evaluations using SF-36v2 and SF-6Dv2 data.
Main Methods:
- An adapted international protocol using an online discrete choice experiment with duration (DCETTO) was employed.
- 3800 Korean adults representative of the general population participated.
- The experimental design included Core, Common, and Triplet Modules, with preferences analyzed using logit models.
Main Results:
- Model 9, based on the Core Module, was selected as the preferred model.
- The pain dimension showed the largest utility decrement (-0.496) at its worst level.
- The worst possible health state utility was -1.012, with 31.7% of states valued as worse than dead; significant preference heterogeneity was observed.
Conclusions:
- The first Korean SF-6Dv2 value set has been successfully derived.
- This value set facilitates QALY calculations from SF-36v2 and SF-6Dv2 data.
- The derived value set will support health economic evaluations within the Korean context.
Related Concept Videos
Decision Making: P-value Method
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
Convenience Sampling Method
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Factorial Design
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
Experimental Designs
An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
Response Surface Methodology
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
The process of RSM involves several key steps:
Randomized Experiments
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
