Rasch measurement is a way to analyze data when we have different categories or choices. It helps us understand a hidden quality or trait that we cannot directly measure. It uses a model called the Rasch model, which was developed by Rasch in 1960 for yes-or-no type questions. In Rasch measurement, there is the assumption that there is one main quality or trait that is of interest. This quality or trait is like a line or scale, and everyone samples can be placed on this line.
Over time, researchers have come up with different variations of Rasch measurement to deal with different types of data. For example, when we have rating scales like Likert scales, we can use models like the Partial Credit Model (Masters, 1982 ) or the Rating Scale Model (Andrich, 1978). These models help researchers understand how people’s responses relate to different levels or categories on the scale.
Rasch measurement can be used to check if our measurements are valid and reliable. It helps confirm if the quality or trait we’re interested in is one-dimensional or has different aspects. It also helps make sure that the order of the rating scale is correct and that the questions are consistent.
In the field of sport and exercise psychology, researchers have been using Rasch models since the 1980s. They have found that it has many advantages compared to other theories that focus on measurement errors (Strauss et al., 2012).
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Strauss, B., Bu ̈ sch, D., & Tenenbaum, G. (2012). Rasch- modeling in sports. In G. Tenenbaum, R. Eklund, & A. Kamata (Eds.), Measurement in sport and exercise psychol- ogy (pp. 75 81). Champaign, IL: Human Kinetics.