{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T19:55:45Z","timestamp":1790625345631,"version":"4.1.0"},"reference-count":54,"publisher":"National Academy of Sciences","issue":"40","license":[{"start":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T00:00:00Z","timestamp":1790553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2026,10,6]]},"abstract":"<jats:p>\n                    Conjoint experiments are extensively used across multiple disciplines to make inferences about preferences over multiattribute alternatives. Much previous research has analyzed the importance of attributes at the aggregate level. Here, we focus on understanding individual-level behavior and, specifically, on strategy use. We present a Bayesian cognitive model of strategy use that performs attribute weight inference (how important an attribute is), attribute level inference (which value of the attribute is favored), and latent-mixture inference to classify strategy use among well-established strategies in cognitive science. We then validate and apply our model to two conjoint experiments (\n                    <jats:italic toggle=\"yes\">N<\/jats:italic>\n                    = 3,762) focusing on three political domains (attitudes toward immigrants, political candidates, and climate policy). We find that the simplest heuristic strategy is the highest probability in all conditions and that approximately 67\u201376% of subjects are classified as using different strategies depending on the political domain. Our model additionally highlights how aggregate-level inference on the weight of an attribute can be meaningfully decomposed by individual differences in strategy use and preferences over attributes. In addition, our experiments include a set of experimental design manipulations that increase different dimensions of complexity and show their impact on strategy classification.\n                  <\/jats:p>","DOI":"10.1073\/pnas.2613113123","type":"journal-article","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T19:02:56Z","timestamp":1790622176000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":0,"title":["Classifying strategy use in multiattribute subjective choice: Application to conjoint experiments in political science"],"prefix":"10.1073","volume":"123","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2453-4202","authenticated-orcid":false,"given":"Nidhi V.","family":"Banavar","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01an7q238","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Political Science, University of California Berkeley","place":["Berkeley"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0229-9694","authenticated-orcid":false,"given":"Kirk","family":"Bansak","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01an7q238","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Political Science, University of California Berkeley","place":["Berkeley"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2026,9,28]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1017\/psrm.2018.26"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1306374110"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0003055420001136"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1108\/00070709710158825"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11109-019-09554-9"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2496(64)90015-X"},{"key":"e_1_3_4_7_2","doi-asserted-by":"crossref","unstructured":"F. Eggers H. Sattler T. Teichert F. V\u00f6lckner \u201cChoice-based conjoint analysis\u201d in Handbook of Market Research C. Homburg M. Klarmann A. Vomberg Eds. (Springer 2021) pp. 781\u2013819.","DOI":"10.1007\/978-3-319-57413-4_23"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0304-4076(98)00055-4"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.2165\/11537870-000000000-00000"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1521\/soco.2009.27.1.128"},{"key":"e_1_3_4_11_2","volume-title":"Discrete Choice Analysis: Theory and Application to Travel Demand","author":"Ben-Akiva M. E.","year":"1985","unstructured":"M. E. Ben-Akiva, S. R. Lerman, Discrete Choice Analysis: Theory and Application to Travel Demand (MIT Press, 1985), vol. 9."},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1093\/pan\/mpt024"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1017\/pan.2022.16"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1111\/ajps.12714"},{"key":"e_1_3_4_15_2","doi-asserted-by":"publisher","DOI":"10.1017\/pan.2021.4"},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1017\/pan.2021.41"},{"key":"e_1_3_4_17_2","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-psych-120709-145346"},{"key":"e_1_3_4_18_2","doi-asserted-by":"publisher","DOI":"10.1086\/321952"},{"key":"e_1_3_4_19_2","doi-asserted-by":"publisher","DOI":"10.1177\/147078530704900110"},{"key":"e_1_3_4_20_2","doi-asserted-by":"publisher","DOI":"10.1017\/S193029750000173X"},{"key":"e_1_3_4_21_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139173933"},{"key":"e_1_3_4_22_2","doi-asserted-by":"publisher","DOI":"10.3758\/BF03196581"},{"key":"e_1_3_4_23_2","doi-asserted-by":"publisher","DOI":"10.1002\/bdm.581"},{"key":"e_1_3_4_24_2","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.109.1.75"},{"key":"e_1_3_4_25_2","doi-asserted-by":"publisher","DOI":"10.1007\/s42113-020-00092-w"},{"key":"e_1_3_4_26_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0007123424000048"},{"key":"e_1_3_4_27_2","doi-asserted-by":"publisher","DOI":"10.2307\/1962397"},{"key":"e_1_3_4_28_2","doi-asserted-by":"publisher","DOI":"10.2307\/2082427"},{"key":"e_1_3_4_29_2","doi-asserted-by":"publisher","DOI":"10.2307\/2669334"},{"key":"e_1_3_4_30_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511791048"},{"key":"e_1_3_4_31_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139032490"},{"key":"e_1_3_4_32_2","doi-asserted-by":"publisher","DOI":"10.1017\/pan.2020.11"},{"key":"e_1_3_4_33_2","doi-asserted-by":"publisher","DOI":"10.1017\/pan.2025.1"},{"key":"e_1_3_4_34_2","doi-asserted-by":"publisher","DOI":"10.1111\/pops.13031"},{"key":"e_1_3_4_35_2","doi-asserted-by":"publisher","DOI":"10.1086\/727597"},{"key":"e_1_3_4_36_2","doi-asserted-by":"publisher","DOI":"10.3758\/s13423-014-0643-0"},{"key":"e_1_3_4_37_2","doi-asserted-by":"publisher","DOI":"10.1017\/pan.2017.40"},{"key":"e_1_3_4_38_2","doi-asserted-by":"publisher","DOI":"10.1017\/psrm.2019.13"},{"key":"e_1_3_4_39_2","doi-asserted-by":"publisher","DOI":"10.1086\/716290"},{"key":"e_1_3_4_40_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.aag2147"},{"key":"e_1_3_4_41_2","doi-asserted-by":"publisher","DOI":"10.1086\/715163"},{"key":"e_1_3_4_42_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06417-6"},{"key":"e_1_3_4_43_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0007123425101075"},{"key":"e_1_3_4_44_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.185.4157.1124"},{"key":"e_1_3_4_45_2","doi-asserted-by":"publisher","DOI":"10.1037\/0278-7393.14.3.534"},{"key":"e_1_3_4_46_2","doi-asserted-by":"publisher","DOI":"10.3998\/mpub.13933"},{"key":"e_1_3_4_47_2","doi-asserted-by":"publisher","DOI":"10.2307\/2111381"},{"key":"e_1_3_4_48_2","first-page":"3","volume-title":"Fast and Frugal Heuristics: The Adaptive Toolbox in Simple Heuristics that Make Us Smart","author":"Gigerenzer G.","year":"1999","unstructured":"G. Gigerenzer, P. M. Todd, Fast and Frugal Heuristics: The Adaptive Toolbox in Simple Heuristics that Make Us Smart (Oxford University Press, 1999), pp. 3\u201334."},{"key":"e_1_3_4_49_2","first-page":"1150","article-title":"Rational choice theory","volume":"3","author":"Oppenheimer J. A.","year":"2008","unstructured":"J. A. Oppenheimer, Rational choice theory. Encycl. Polit. Theory 3, 1150\u20131159 (2008).","journal-title":"Encycl. Polit. Theory"},{"key":"e_1_3_4_50_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbusres.2014.02.013"},{"key":"e_1_3_4_51_2","unstructured":"M. Plummer \u201cA program for analysis of Bayesian graphical models using Gibbs sampling\u201d in Proceedings of the 3rd International Workshop on Distributed Statistical Computing (Vienna Austria 2003) vol. 124 pp. 1\u201310."},{"key":"e_1_3_4_52_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmp.2010.04.001"},{"key":"e_1_3_4_53_2","doi-asserted-by":"crossref","unstructured":"K. Bansak J. Hainmueller D. J. Hopkins T. Yamamoto \u201cConjoint survey experiments\u201d in Advances in Experimental Political Science J. N. Druckman D. P. Green Eds. (Cambridge University Press 2021).","DOI":"10.1017\/9781108777919.004"},{"key":"e_1_3_4_54_2","doi-asserted-by":"crossref","unstructured":"N. V. Banavar K. Bansak Data from \u201cReplication materials for: Classifying strategy use in multi-attribute subjective choice: Application to conjoint experiments in political science.\u201d Harvard Dataverse. https:\/\/doi.org\/10.7910\/DVN\/POMLLB. Deposited 16 September 2026.","DOI":"10.31234\/osf.io\/p9ah8_v3"}],"container-title":["Proceedings of the National Academy of Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pnas.org\/doi\/pdf\/10.1073\/pnas.2613113123","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T19:03:33Z","timestamp":1790622213000},"score":1,"resource":{"primary":{"URL":"https:\/\/pnas.org\/doi\/10.1073\/pnas.2613113123"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,28]]},"references-count":54,"journal-issue":{"issue":"40","published-print":{"date-parts":[[2026,10,6]]}},"alternative-id":["10.1073\/pnas.2613113123"],"URL":"https:\/\/doi.org\/10.1073\/pnas.2613113123","relation":{},"ISSN":["0027-8424","1091-6490"],"issn-type":[{"value":"0027-8424","type":"print"},{"value":"1091-6490","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,28]]},"assertion":[{"value":"2026-04-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-16","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-28","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e2613113123"}}