SurveyEngine Knowledge Base
The knowledge base is organised around the stages of a DCE research project from start to finish. You'll find general guidance but also specifics for Health, Transport and Environment.
Jump directly to the stage that matches where you are or use the quick search below.
Knowledge Articles by Stage of Research
| Foundations | The conceptual and theoretical building blocks of discrete choice experiments - what they are, why they work, and when to use them. |
| Experiment Design | How to design a statistically efficient choice experiment - attributes, levels, D-efficiency, blocking, and advanced design methods. |
| Survey Building | Building the survey instrument around your choice experiment - question flow, display logic, variable piping, and platform integration. |
| Testing & QA | How to test and quality-assure your DCE before and during fieldwork - pilot studies, cognitive interviewing, soft launches, and consistency checks. |
| Respondent Sampling | Recruiting the right respondents for your study - sample size, panel providers, patient recruitment, and hard-to-reach populations. |
| Data Quality | Detecting and managing poor quality responses - fraud detection, speeders, straightliners, protest responses, and incidence rate monitoring. |
| Modelling & Analysis | Estimating choice models from your data - MNL, mixed logit, WTP space, latent class, and RP/SP joint estimation in Apollo. |
| Putting It All Together | End-to-end guidance for completing a DCE study - project planning, reporting standards, HTA submissions, and cost-benefit analysis. |
Article by domain
The same articles are tagged by research domain.
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