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Autor/inn/en | Fong, Duncan K. H.; Ebbes, Peter; DeSarbo, Wayne S. |
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Titel | A Heterogeneous Bayesian Regression Model for Cross-Sectional Data Involving a Single Observation per Response Unit |
Quelle | In: Psychometrika, 77 (2012) 2, S.293-314 (22 Seiten)
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Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 0033-3123 |
DOI | 10.1007/s11336-012-9252-x |
Schlagwörter | Monte Carlo Methods; Social Sciences; Computation; Models; Bayesian Statistics; Data Analysis; Evaluation Methods; Psychology; Observation; Feedback (Response) |
Abstract | Multiple regression is frequently used across the various social sciences to analyze cross-sectional data. However, it can often times be challenging to justify the assumption of common regression coefficients across all respondents. This manuscript presents a heterogeneous Bayesian regression model that enables the estimation of individual-level-regression coefficients in cross-sectional data involving a "single" observation per response unit. A Gibbs sampling algorithm is developed to implement the proposed Bayesian methodology. A Monte Carlo simulation study is constructed to assess the performance of the proposed methodology across a number of experimental factors. We then apply the proposed method to analyze data collected from a consumer psychology study that examines the differential importance of price and quality in determining perceived value evaluations. (As Provided). |
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Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2017/4/10 |