Using the Rasch model for prediction
Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review
Rasch measurement is widely used for measurement of latent variables in psychologicaltesting, education, health status measurement, and other fields. The Raschmodel expresses ideal measurement requirements and much research has dealt withtesting whether these assumptions are met in real data. Latent variables are often ofinterest in terms of their relation to other variables, some examples being self ratedhealth as predictor of mortality or psychosocial work environment factors as predictorsof job turnover. This chapter deals with prediction of a binary outcome variableusing latent variables measured using the Rasch model. Three approaches are compared:(i) prediction using the sufficient score, (ii) prediction using the estimated valuesfor each person, and (iii) prediction based on a joint model. Extensions of the Raschmodel including uniform differential item functioning and uniform local dependencebetween items are also discussed. The approaches are illustrated and motivated usingan example from occupational epidemiology.
Original language | English |
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Title of host publication | Psychological Tests and Testing Research Trends |
Number of pages | 16 |
Publisher | Nova Science Publishers |
Publication date | 1 Dec 2007 |
Pages | 295-310 |
ISBN (Print) | 9781600215698 |
Publication status | Published - 1 Dec 2007 |
ID: 199064227