{"title":"Cognitive and cultural models in psychological science: A tutorial on modeling free-list data as a dependent variable in Bayesian regression.","authors":"Theiss Bendixen, Benjamin Grant Purzycki","doi":"10.1037/met0000553","DOIUrl":null,"url":null,"abstract":"<p><p>Assessing relationships between culture and cognition is central to psychological science. To this end, free-listing is a useful methodological instrument. To facilitate its wider use, we here present the free-list method along with some of its many applications and offer a tutorial on how to prepare and statistically model free-list data as a dependent variable in Bayesian regression using openly available data and code. We further demonstrate the real-world utility of the outlined workflow by modeling within-subject agreement between a free-list task and a corollary item response scale on religious beliefs with a cross-culturally diverse sample. Overall, we fail to find a reliable statistical association between these two instruments, an original empirical finding that calls for further inquiry into identifying the cognitive processes that item response scales and free-list tasks tap into. Throughout, we argue that free-listing is an unambiguous measure of cognitive and cultural information and that the free-list method therefore has broad potential across the social sciences aiming to measure and model individual-level and cross-cultural variation in mental representations. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":"223-239"},"PeriodicalIF":7.6000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychological methods","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/met0000553","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/3/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Assessing relationships between culture and cognition is central to psychological science. To this end, free-listing is a useful methodological instrument. To facilitate its wider use, we here present the free-list method along with some of its many applications and offer a tutorial on how to prepare and statistically model free-list data as a dependent variable in Bayesian regression using openly available data and code. We further demonstrate the real-world utility of the outlined workflow by modeling within-subject agreement between a free-list task and a corollary item response scale on religious beliefs with a cross-culturally diverse sample. Overall, we fail to find a reliable statistical association between these two instruments, an original empirical finding that calls for further inquiry into identifying the cognitive processes that item response scales and free-list tasks tap into. Throughout, we argue that free-listing is an unambiguous measure of cognitive and cultural information and that the free-list method therefore has broad potential across the social sciences aiming to measure and model individual-level and cross-cultural variation in mental representations. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
期刊介绍:
Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.