Reporting DCE results - standards and best practice

The PREFS checklist and ISPOR standards set the minimum bar for DCE reporting - but good reporting can go further.

This article explains how to report DCE results in line with PREFS and ISPOR standards for academic publication, and the additional reporting requirements for regulatory submissions and policy reports.

Ben White, 07.07.2026

Why reporting standards matter

A DCE study that is well-designed, well-executed, and well-analysed can still fail to influence decisions if it is poorly reported. Regulatory reviewers, HTA committees, and journal reviewers cannot evaluate a study they cannot fully understand.

The most common reporting failures in published DCE studies are: insufficient description of the experimental design; missing information about the attribute selection process; no description of data quality checks; incomplete WTP estimation results; and no sensitivity analyses.

Reporting standards for DCE studies

The PREFS checklist (Bridges et al., 2011, updated 2021) is the most widely used reporting standard for health preference studies and is referenced by ISPOR, FDA, and leading health economics journals. It covers: research question, experimental design, preference elicitation method, analysis method, and overall quality.

For transport and environmental DCE studies, the guidance from the Stated Choice Methods textbook (Louviere et al., 2000) and the Environmental Preference methods literature (Bateman et al., 2002) set comparable standards.

For regulatory submissions, the FDA's patient preference guidance (2019) specifies additional reporting requirements including the decision context, confirmation that the study meets the guidance's evidence standards, and a description of how the results will be used in the benefit-risk framework.

TLDR Quick links

SurveyEngine academic papers

Forum: reporting questions

Open a free account

Structuring your DCE results report

Methods section - must include: (1) research question and decision context; (2) target population and recruitment strategy; (3) attribute selection process and qualitative evidence; (4) experimental design including design type, number of choice sets, blocking, and D-efficiency; (5) data quality checks and exclusion criteria; (6) sample description with demographic table.

Results section - must include: (1) sample flow diagram (recruited, screened, eligible, completed, excluded, final analysis sample); (2) data quality check results (consistency check pass rate, speeder exclusions, etc.); (3) model specification and fit statistics; (4) utility parameter estimates with standard errors and t-ratios; (5) WTP estimates with 95% confidence intervals; (6) sensitivity analyses.

Discussion section - must include: (1) comparison of WTP estimates against prior literature or benchmarks; (2) discussion of preference heterogeneity; (3) study limitations; (4) implications for the decision context.

Supplementary materials - should include: full survey instrument; full design matrix; model code or estimation details; full WTP tables for all attributes.

Worked example - academic paper methods section checklist

A DCE study submitted to Value in Health goes through the PREFS checklist before submission. Items confirmed present: research question ✓, target population ✓, attribute selection qualitative basis ✓, design type and D-efficiency ✓, number of choice sets ✓, data quality checks ✓, sample flow ✓, model specification ✓, WTP with CI ✓, sensitivity analyses ✓.

Two items are initially missing: the full design matrix (added as supplementary material) and the consistency check pass rate (added to the results table). After revision, the paper passes the PREFS checklist and is accepted with minor revisions - the reviewers note that the reporting is 'unusually complete and transparent'.