conjoint-diagnostics

What problem does it solve?

Diagnostics framework that helps research teams evaluate and improve conjoint experiments by systematically identifying design, estimation, measurement error, external validity, and interpretation issues.

Core Features & Use Cases

• Comprehensive design diagnostics covering attribute/level selection, profile restrictions, number of tasks, randomization, and sampling considerations.
• Estimation and interpretation guidance focusing on estimand clarity, reference levels, subgroup analysis, standard errors, and multiple testing cautions.
• Measurement error diagnostics describing IRR, swapping error, bias correction methods, and sensitivity analyses.
• External validity and reporting guidance addressing profile distributions, forced-choice vs. real-world behavior, and transparent documentation.

Quick Start

Run through the conjoint study checklist, documenting how well design, estimation, measurement error, external validity, and interpretation checks are satisfied.