Rasch analysis can be applied to assessments in a wide range of disciplines, including health studies, education, psychology, marketing, economics and social sciences.
Many assessments in these disciplines involve a well defined group of people responding to a set of items for assessment. Generally, the responses to the items are scored 0, 1 (for two ordered categories); or 0, 1, 2 (for three ordered categories); or 0, 1, 2, 3 (for four ordered categories) and so on, to indicate increasing levels of a response on some variable such as health status or academic achievement. These responses are then added across items to give each person a total score. This total score summarise the responses to all the items, and a person with a higher total score than another one is deemed to show more of the variable assessed. Summing the scores of the items to give a single score for a person implies that the items are intended to measure a single variable, often referred to as a unidimensional variable.
The Rasch model is the only item response theory (IRT) model in which the total score across items characterizes a person totally. It is also the simplest of such models having the minimum of parameters for the person (just one), and just one parameter corresponding to each category of an item. This item parameter is generically referred to as a threshold. There is just one in the case of a dichotomous item, two in the case of three ordered categories, and so on.
1. What is Rasch Analysis
2. Why undertake a Rasch analysis?
3. The research paradigm and the Rasch model
4. Is there more than one Rasch model?
For the case where the response categories are the same across items (e.g. SD, D, A, SA), the Rasch model has been called "the rating scale model"; the case where the response categories are different across items has been called the "partial credit model". It is stressed, however, that the structure and response process for a person responding to an item is identical in the two specifications. Rather than emphasizing two models for the above different specifications, it can be more efficient to refer to one Rasch Unidimensional Measurement Model (RUMM) with different numbers of categories and different parameterizations (as in RUMM2030). Thus it might be better to refer to the former as a rating scale parameterization; the latter as a partial credit parameterization.
6. Thresholds and Steps
7. Disordered Thresholds as an Anomaly
8. Who should use a Rasch analysis?
9. An ideal approach to a Rasch analysis?
10. Recommended Rasch Software
11. The RUMM approach to Rasch Analysis
12. What courses and workshops are available on Rasch analysis?
13. What cloud analysis engines and API's are available?
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