Introductory Rasch Model Workshop: Applications in Survey Research and Educational Measurement

The research paradigm and the Rasch model

There is a philosophical or paradigm difference between the application of the Rasch model and other IRT models, for example, the two-parameter and three-parameter models are designed for responses scored just 0, 1.. In the paradigm of other IRT models, the emphasis is on finding a model that best characterizes the given data; in the Rasch paradigm, the emphasis is in identifying and studying anomalies in the data disclosed by the Rasch model. Thus, in the paradigm of applying other than Rasch models, if the Rasch model does not work then a more complicated model, relative to the simpler Rasch model, that might explain the data better is sought. In the case of dichotomously scored data, this might be the two parameter model which has a second parameter for each item. 

Is there more than one Rasch model?

There is only one Rasch model for unidimensional responses at the level of one person responding to one item.However, there are different specifications when more than two ordered response categories are present. In one specification, all items might be hypothesized to have the same parameters across all items, as for example in the case that all items have the same response structure (e.g. SD, D, A, SA). In a second specification, different parameters across items may be needed when items do not have the same response categories, as in achievement testing when different items may have a different number of ordered categories and most certainly a different description of the categories 

Different Rasch Model Specifications

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 RaschUnidimensional 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. 

Thresholds and Steps

One particular difference that has arisen in different Rasch analysis reporting is the use of "step", when the parameters are different across items, and "thresholds", when they are the same across items. This can give the impression that the response process characteristized by the Rasch model is a sequential process. However, the Rasch model is NOT a sequential processing model but a static model, which just specifies the probability of a person with a given location responding, or being classified, in one of the categories of an item. 

For example, the term "step" is not used in the dichotomous case because it would imply, implausibly, that a person goes from being wrong to being right, or goes from disagreeing to agreeing. Instead the person is either wrong or right, or either disagrees or agrees; there is no sequential processing here. The response process is a classification into ordered categories defined by thresholds which can be seen as analogous to markings on a ruler except that the thresholds do not have to be equidistant as they are in a ruler - they are estimated. The threshold is the point where the probability of a response in either one of two adjacent categories is 50%. 

Disordered Thresholds as an Anomaly

As in the case of a ruler, thresholds marking off successive categories need to be ordered to be interpretable. However, in estimating the thresholds from the data, it is possible to discover that the estimates are not properly ordered. This is a sign that the categories are not working as intended and an anomaly in the data that needs to be understood and corrected is disclosed.

Prior to the work of Rasch, Thurstone had constructed a model for ordered categories which also involved thresholds. These may be derived from the Rasch thresholds. The problem with the Thurstone thresholds is that they are always ordered as a property of the model no matter what the features of the data - they have no use in disclosing whether categories are working in the ordering intended. Thurstone thresholds cannot disclose any anomalies in the ordering; indeed they will hide them. 

If you are interested to LEARN and KNOW more about Introductory Rasch Model Workshop: Applications in Survey Research and Educational Measurement, you can join our workshop.

The details of the workshops are as follow:

Course Title : Introductory Rasch Model Workshop: Applications in Survey Research and Educational Measurement

Date:  17 - 18 March 2014 (Monday - Tuesday)
Time:  8:30 am – 5:30 pm 
Medium:  English 
Fee:  RM300 (early bird rate) / RM400 (normal rate) 
Venue:  MPWS Training Centre, 63-1, 63-2, JalanKajangImpian 1/11,
Taman KajangImpian, Seksyen 7, 43650 Bandar BaruBangi, Selangor

For registration and more information, please go to the following link:

>> http://postgraduateworkshop.com/raschanalysis/

This workshop is open to all researchers, academicians and postgraduate students from government agencies, local and international higher learning institutions, as well as private sector.
 

We also accept payment via LO/PO. However, the price will be normal price and the LO/PO must be sent prior to the event. If your company/organization is having difficulty to prepare LO/PO prior to the event, we do accept Letter of Undertaking (LoU) as an assurance that the payment will be made after the event. 

Registration fees cover refreshments and lunch. All fees must be fully paid before the commencement of the course. Otherwise, participants will not be allowed to enter the lecture hall. 

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For registration and more information, please go to the following link:

>> http://postgraduateworkshop.com/raschanalysis/