Hierarchical Bayes Estimation

A Comparison of HB-MNL Estimation via Metropolis Hastings (Sawtooth Software’s CBC/HB Program), Hamiltonian Monte Carlo (via Stan), and Variational Bayes (via Stan) (2024)

22 Jan 2024 - 346 hits

Recently, Kevin van Horn (of Bayesium Analytics) did some R&D work for Sawtooth Software to compare Hamiltonian Monte Carlo (HMC) as implemented in Stan to the old standby, Sawtooth Software’s ... Read More

Enhance Conjoint with a Behavioral Framework (2021)

11 Nov 2021 - 2528 hits

Finding useful covariates (variables outside the conjoint task) that can boost the predictive validity of conjoint analysis via HB estimation is a topic that Peter and Stefan have investigated and ... Read More

What Are the Optimal HB Priors Settings for CBC and MaxDiff Studies? (2016)

06 Apr 2016 - 5605 hits

Sawtooth Software's Bryan Orme and Walter Williams report results of a meta analysis of about 50 commercial CBC and MaxDiff data sets. Specifically, they looked into how the priors settings in CBC/HB ... Read More

CBC/HB for Beginners (2009)

06 Mar 2009 - 8866 hits

This paper was originally created for the 2009 Sawtooth Software Conference. This paper focuses on what happens during the estimation of CBC/HB utilities. It takes a naïve approach assuming no ... Read More

Application of Covariates within Sawtooth Software’s CBC/HB Program: Theory and Practical Example (2009)

09 Jan 2009 - 6586 hits

The basic (generic) hierarchical Bayes estimation that the first versions of Sawtooth Software's CBC/HB program supported assumed that respondents were drawn from a single, multivariate-normal ... Read More

Perspectives Based on 10 Years of HB in Marketing Research (2003)

29 Aug 2003 - 3336 hits

Greg Allenby and Peter Rossi describe the history of HB methods as they relate to marketing research methods. They describe the theory behind HB, the challenges in implementing HB methods for ... Read More

New Advances Shed light on HB Anomalies (2003)

13 Jun 2003 - 2984 hits

Hierarchical Bayes estimation for choice data represents one of the most successful new developments in our field. HB has proven robust for ratings-based conjoint, ACA, and full-profile CBC projects. ... Read More

Hierarchical Bayes: Why All the Attention? (2000)

02 Jun 2000 - 6781 hits

This paper was originally published in the March 2000 Quirk's Marketing Research Review. HB has been receiving a lot of attention lately. Until recently, desktop PCs weren't powerful enough to handle ... Read More

Monotonicity Constraints in Choice-Based Conjoint with Hierarchical Bayes (2000)

14 Apr 2000 - 2692 hits

Conjoint analysts often discover that some of the part worths don't conform to expectations. We generally expect low prices to be preferred to high prices, high performance to low performance, etc. ... Read More

Understanding HB: An Intuitive Approach (2000)

03 Mar 2000 - 8160 hits

In this paper, Rich Johnson provides an intuitive example to explain Bayesian analysis. He explains how Bayesian analysis differs from conventional statistics. Rich introduces Bayes' rule, and talks ... Read More

The Joys and Sorrows of Implementing HB Methods for Conjoint Analysis (1999)

11 Nov 1999 - 3085 hits

This paper was originally delivered at the 1999 Hierarchical Bayes Conference at Ohio State University by Rich Johnson. Rich recaps his experience with HB methods, particularly as they relate to ... Read More