Course abstract
To prevent response biases associated with the use of rating scales, test items may be presented as comparative judgements. These include the popular ‘forced choice’ where respondents rank two or more stimuli. The extent of preference can also be expressed, for example by selecting ‘grades of preference’ using categories such as “much more” or “slightly more”, or ‘proportions-of-total’ distributing a fixed number of points between several stimuli. Responses collected with such formats are relative within the person, leading to major psychometric challenges – interpersonally incomparable (ipsative) data. Since measurement of individual differences requires absolute position on the traits of interest, appropriate methods of scaling ipsative data are required.
This workshop will introduce participants to state-of-the-art methods for analysing and scoring comparative judgments, and provide recommendations for designing effective comparative measures. I will focus on the Thurstonian factor-analytic approach, applicable to all types of ipsative data – binary, ordinal and continuous. The Thurstonian family include the TIRT model for choice and ranking (Brown & Maydeu-Olivares, 2011), the compositional model for percentage-of-total data (Brown, 2016) and the ordinal IRT model for graded-preference data (Brown & Maydeu-Olivares, 2017). This unified approach will be demonstrated with empirical data analysis examples, including well-known personality questionnaires.