How to Explain AMCE Results to Nontechnical Readers
Translate conjoint estimates into plain language for collaborators, clients, committees, or students.
The Short Version
Translate conjoint estimates into plain language for collaborators, clients, committees, or students. A practical way to begin is to start by explaining the choice task, then define the reference level for each attribute. Finish by making sure you report uncertainty intervals. The full walkthrough below explains each part in order.
Is This Guide for You?
Researchers presenting conjoint findings outside a methods-focused audience.
Follow These Steps
Work through these 6 steps at your own pace. The wording is intentionally practical, and you can return to the checklist at the end when you are ready to review your work.
- Start by explaining the choice task.
- Define the reference level for each attribute.
- Describe an estimate as a change in choice probability relative to that reference.
- Use plots with clear labels.
- Avoid claiming individual-level preference certainty from aggregate estimates.
- Report uncertainty intervals.
What This Helps You Accomplish
Conjoint results are easy to overstate. Plain-language explanations help readers understand what the estimates do and do not show.
A Quick Confidence Check
- Name the reference level.
- Use percentage-point language when appropriate.
- Show uncertainty.
- Avoid causal claims beyond the design.
Common Questions
Can I use this guide if I am new to this?
Yes. Researchers presenting conjoint findings outside a methods-focused audience. Follow the steps in order, start with a small test, and use the final checklist before you field or report anything important.
What is the simplest way to get started?
Begin by start by explaining the choice task. Next, define the reference level for each attribute. You do not need to perfect every setting before running a small preview or pilot.
How do I know when I am ready?
Use the confidence check above. In particular: Name the reference level. Use percentage-point language when appropriate. Show uncertainty. Avoid causal claims beyond the design. When the decision is consequential, keep your study documentation and ask a qualified colleague or methods reviewer to examine the design as well.
Related Guides
Research artifact: sample data, codebook, and scriptsResearch Pathways
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