naa a22 4500 510776671 CHVBK 20180411083232.0 cr unu---uuuuu 180411e20130901xx s 000 0 eng 10.3758/s13428-012-0300-3 doi (NATIONALLICENCE)springer-10.3758/s13428-012-0300-3 Bayesian Thurstonian models for ranking data using JAGS [Elektronische Daten] [Timothy Johnson, Kristine Kuhn] A Thurstonian model for ranking data assumes that observed rankings are consistent with those of a set of underlying continuous variables. This model is appealing since it renders ranking data amenable to familiar models for continuous response variables—namely, linear regression models. To date, however, the use of Thurstonian models for ranking data has been very rare in practice. One reason for this may be that inferences based on these models require specialized technical methods. These methods have been developed to address computational challenges involved in these models but are not easy to implement without considerable technical expertise and are not widely available in software packages. To address this limitation, we show that Bayesian Thurstonian models for ranking data can be very easily implemented with the JAGS software package. We provide JAGS model files for Thurstonian ranking models for general use, discuss their implementation, and illustrate their use in analyses. Psychonomic Society, Inc., 2013 Ranking data nationallicence Thurstonian models nationallicence Bayesian statistics nationallicence JAGS nationallicence Johnson Timothy Department of Statistical Science, University of Idaho, 875 Perimeter Drive Stop 1104, 83844-1104, Moscow, ID, USA aut Kuhn Kristine Department of Management, Information Systems, and Entrepreneurship, College of Business, Washington State University, 99164-4750, Pullman, WA, USA aut Behavior Research Methods Springer US; http://www.springer-ny.com 45/3(2013-09-01), 857-872 45:3<857 2013 45 13428 https://doi.org/10.3758/s13428-012-0300-3 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.3758/s13428-012-0300-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Johnson Timothy Department of Statistical Science, University of Idaho, 875 Perimeter Drive Stop 1104, 83844-1104, Moscow, ID, USA aut NATIONALLICENCE 700 1- Kuhn Kristine Department of Management, Information Systems, and Entrepreneurship, College of Business, Washington State University, 99164-4750, Pullman, WA, USA aut NATIONALLICENCE 773 0- Behavior Research Methods Springer US; http://www.springer-ny.com 45/3(2013-09-01), 857-872 45:3<857 2013 45 13428 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer