Importance and Prediction Models
Fast, Accurate Driver Analysis (2026)
This article explains faster ways to do driver analysis, which helps identify what factors matter most but can be very slow because it tests many combinations of variables. It focuses on a method ... Read More
The Handy (But Little Known) Q-Sort Rating Method: Plus anchored and HB-MNL extensions (2025)
The Q-sort method is a simple, effective alternative to traditional rating scales and an easier option than MaxDiff (since it doesn’t involve an experimental design) for evaluating preferences. It ... Read More
Rating Scales for Use in Driver Analysis (2024)
This paper covers rating scales commonly used in driver analysis, both for the overall measure and for the attribute ratings. Where possible we base our recommendations on research we (e.g., ... Read More
Situational Choice Experiments for Marketing Research: How to Design, Analyze and Report Them (2022)
Situational choice experiments (SCE) resemble choice-based conjoint experiments, but (a) they have different experimental design requirements and (b) they ask for a different type of response from ... Read More
Analysis Options for Patient Chart Studies (2022)
A type of choice modeling we do that's unique to pharmaceutical research is the patient chart study. These involve modeling physicians' prescribing decisions using data taken from patients' medical ... Read More
Driver Analysis: How to Do It Badly and Well (2022)
In a driver analysis we seek to measure the importance of various attributes in predicting some overall performance measure like an overall brand rating or a customer satisfaction rating. ... Read More
An Empirical Test of Six Stated Importance Measures (2006)
In this article, originally published in the International Journal of Market Research, Chrzan and Golovashkina compare six stated importance approaches for survey research: 1) Importance ratings, 2) ... Read More