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| Author: | Hansen, D. Wittink, D. |
| Title: | Combining self-explicated priors with conjoint data using bayesian regression |
| Journal: | Marketing Letters
1995 : JAN, VOL. 6:1, p. 63-72 |
| Index terms: | MARKETING CONJOINT ANALYSIS REGRESSION ANALYSIS |
| Language: | eng |
| Abstract: | A Bayesian regression procedure (RBAYES) is proposed for the optimal combination of self-explicated data (priors) and conjoint judgments to be of full rank. The Bayesian regression procedure is similar to weighted least square in that it uses an information ratio to weigh the priors. The authors provide empirical comparisons for the proposed method against 91) a Stein-type estimator (SBAYES) using one data set and (2) OLS applied to the data from an adaptive conjoint analysis using a second data set. |
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