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

Factorial Design02:01

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...
Qualitative Analysis01:10

Qualitative Analysis

Qualitative analysis is the process of identifying elements, ions, or compounds in an unknown sample. It is the first and most fundamental type of analysis based on the hierarchy of analytical goals. This hierarchy is significant as it provides a structured approach to scientific research, with qualitative analysis serving as the initial step, providing essential information before moving on to quantitative or other forms of analysis.
There are two main approaches to qualitative analysis:...
Qualitative Analysis03:46

Qualitative Analysis

For solutions containing mixtures of different cations, the identity of each cation can be determined by qualitative analysis. This technique involves a series of selective precipitations with different chemical reagents, each reaction producing a characteristic precipitate for a specific group of cations. Metal ions within a group are further separated by varying the pH, heating the mixture to redissolve a precipitate, or adding other reagents to form complex ions.
For instance, group IV...
Experimental Designs01:16

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...
Decision Making: P-value Method01:09

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...
Study Design in Statistics01:15

Study Design in Statistics

A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...

You might also read

Related Articles

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

Sort by
Same author

Getting fairer over time? Assessing changes in health technology funding processes using the accountability for reasonableness (A4R) framework.

The European journal of health economics : HEPAC : health economics in prevention and care·2026
Same author

Clear decisions: improved perceptual clarity reduces age-related decision-making deficits.

The journals of gerontology. Series B, Psychological sciences and social sciences·2026
Same author

Assessing the feasibility of use and content validity of ICECAP-CPM with bereaved family members of young people who died from serious illness: a UK think-aloud study.

BMC palliative care·2026
Same author

England's 10 year health plan: aligning hope with economic reality.

BMJ (Clinical research ed.)·2026
Same author

Multifaceted Declines in Everyday Decision-Making in Older Adults: A Think-Aloud Study.

Journal of applied gerontology : the official journal of the Southern Gerontological Society·2026
Same author

The feasibility and validity of the EQ-5D-Y and CHU9D in a challenging context: adolescent mental health in India.

Journal of patient-reported outcomes·2026
Same journal

Air Pollution Control and Residents' Weight: Empirical Evidence From China's Action Plan.

Health economics·2026
Same journal

Healthcare Costs Following Medical Gender-Affirmation: Evidence From Whole-of-Population Australian Administrative Data.

Health economics·2026
Same journal

Lead in Drinking Water and Child Health: Evidence From Jackson, Mississippi.

Health economics·2026
Same journal

Health on the Move: The Impact of Poverty Alleviation Relocation on Healthcare Utilization in China.

Health economics·2026
Same journal

The Effects of Compulsory Licensing: A Case Study of HIV Drugs.

Health economics·2026
Same journal

Beyond Tobacco Prevention: The Effects of Tobacco 21 Laws on Young Adults' Body Weight.

Health economics·2026
See all related articles

Related Experiment Video

Updated: Jun 2, 2026

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

Using qualitative methods for attribute development for discrete choice experiments: issues and recommendations.

Joanna Coast1, Hareth Al-Janabi, Eileen J Sutton

  • 1Health Economics Unit, University of Birmingham, Birmingham, UK. j.coast@bham.ac.uk

Health Economics
|May 11, 2011
PubMed
Summary
This summary is machine-generated.

Attribute development for discrete choice experiments (DCEs) requires rigorous qualitative approaches. This study recommends a two-stage process and iterative analysis for better reporting in DCE research.

More Related Videos

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Related Experiment Videos

Last Updated: Jun 2, 2026

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Area of Science:

  • Behavioral Economics
  • Marketing Research
  • Health Economics

Background:

  • Attribute generation in discrete choice experiments (DCEs) is frequently underreported, raising concerns about research rigor.
  • Existing literature lacks comprehensive guidance on best practices for developing DCE attributes.

Purpose of the Study:

  • To explore challenges and contrast qualitative approaches in attribute development for DCEs.
  • To provide recommendations for improving the reporting and rigor of DCE attribute generation.

Main Methods:

  • Analysis of eight case studies, focusing on attribute development for both measurement and policy-related DCEs.
  • Comparison of different qualitative data collection and analysis techniques.
  • Application of principles from random utility theory to attribute design.

Main Results:

  • Attribute development is a two-stage process: conceptualization and linguistic refinement.
  • Challenges include balancing theoretical requirements (e.g., avoiding personality traits) and practical constraints of condensing qualitative data.
  • The choice of qualitative methods depends on question sensitivity and data availability.

Conclusions:

  • An iterative, constant comparative approach to qualitative analysis is recommended for DCE attribute development.
  • Improved reporting standards are crucial for enhancing the transparency and validity of DCE attribute generation.