The Integration of Bayesian Regression Analysis and Bayesian Process Tracing in Mixed-Methods Research
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| Title: | The Integration of Bayesian Regression Analysis and Bayesian Process Tracing in Mixed-Methods Research |
|---|---|
| Language: | English |
| Authors: | Lion Behrens (ORCID |
| Source: | Sociological Methods & Research. 2026 55(1):186-218. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 33 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Bayesian Statistics, Regression (Statistics), Statistical Analysis, Mixed Methods Research |
| DOI: | 10.1177/00491241241295336 |
| ISSN: | 0049-1241 1552-8294 |
| Abstract: | In this article, we develop a mixed-methods design that combines Bayesian regression with Bayesian process tracing. A fully Bayesian multimethod design allows one to include empirical knowledge at each stage of the analysis and to coherently transfer information from the quantitative to the qualitative analysis, and vice versa. We present a complete mixed-methods workflow explaining how this is accomplished and how to integrate both methods. It is demonstrated how to use the posterior highest density interval and the Bayes factor from the regression analysis to update the prior level of confidence about what mechanisms possibly connect the cause to the outcome. It is further shown how to choose cases for the qualitative analysis through posterior predictive sampling. We illustrate this approach with an empirical analysis of colonial development and compare it with alternative designs, including nested analysis and the Bayesian integration of qualitative and quantitative methods. |
| Abstractor: | As Provided |
| Notes: | https://doi.org/10.5281/zenodo.13745067 |
| Entry Date: | 2026 |
| Accession Number: | EJ1496178 |
| Database: | ERIC |
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| Abstract: | In this article, we develop a mixed-methods design that combines Bayesian regression with Bayesian process tracing. A fully Bayesian multimethod design allows one to include empirical knowledge at each stage of the analysis and to coherently transfer information from the quantitative to the qualitative analysis, and vice versa. We present a complete mixed-methods workflow explaining how this is accomplished and how to integrate both methods. It is demonstrated how to use the posterior highest density interval and the Bayes factor from the regression analysis to update the prior level of confidence about what mechanisms possibly connect the cause to the outcome. It is further shown how to choose cases for the qualitative analysis through posterior predictive sampling. We illustrate this approach with an empirical analysis of colonial development and compare it with alternative designs, including nested analysis and the Bayesian integration of qualitative and quantitative methods. |
|---|---|
| ISSN: | 0049-1241 1552-8294 |
| DOI: | 10.1177/00491241241295336 |
