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http://hdl.handle.net/1893/38320| Appears in Collections: | Management, Work and Organisation Journal Articles |
| Peer Review Status: | Refereed |
| Title: | Inference in downstream analysis using individual-level posterior means from mixed logit models |
| Author(s): | Campbell, Danny Sandorf, Erlend Dancke Börger, Tobias Dekker, Thijs |
| Contact Email: | danny.campbell@stir.ac.uk |
| Keywords: | Mixed logit Second-stage inference Conditional distibutions Preference heterogeneity Bootstrap simulation |
| Issue Date: | Sep-2026 |
| Date Deposited: | 11-Aug-2026 |
| Citation: | Campbell D, Sandorf ED, Börger T & Dekker T (2026) Inference in downstream analysis using individual-level posterior means from mixed logit models. <i>Journal of Choice Modelling</i>, 60, Art. No.: 100624. https://doi.org/10.1016/j.jocm.2026.100624 |
| Abstract: | Mixed logit models are widely used to recover individual-level preferences for secondary analysis, yet both first-stage sampling uncertainty and variability in conditional distributions are often overlooked. This technical note illustrates the implications of ignoring these sources of uncertainty and provides reproducible R code, compatible with the apollo package, to better approximate the empirical sampling distribution and improve the reliability of second-stage inference. |
| DOI Link: | 10.1016/j.jocm.2026.100624 |
| Rights: | This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article. |
| Licence URL(s): | http://creativecommons.org/licenses/by/4.0/ |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 1-s2.0-S1755534526000308-main.pdf | Fulltext - Published Version | 1.23 MB | Adobe PDF | View/Open |
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