Rasch Model: Simply Easy to Make a Measurement & Assessment!
Rasch
Model 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.
What is Rasch Model?
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.
Working in Quantitative Data Analysis? So What?
The Rasch model, where the total score summarizes completely a person's standing on a variable, arises from a more fundamental requirement: that the comparison of two people is independent of which items may be used within the set of items assessing the same variable. Thus the Rasch model is taken as a criterion for the structure of the responses, rather than a mere statistical description of the responses.
For example, the comparison of the performance of two students' work marked by different graders should be independent of the graders. In this case it is considered that the researcher is deliberately developing items that are valid for the purpose and that meet the Rasch requirements of invariance of comparisons.
Analyzing
data according to the Rasch model, that is, conducting a Rasch
analysis, gives a range of details for checking whether or not adding
the scores is justified in the data. This is called the test of fit
between the data and the model. If the invariance of responses across
different groups of people does not hold, then taking the total score to
characterize a person is not justified. Of course, data never fit the
model perfectly, and it is important to consider the fit of data to the
model with respect to the uses to be made of the total scores.
If
the data do fit the model adequately for the purpose, then the Rasch
analysis also linearises the total score, which is bounded by 0 and the
maximum score on the items, into measurements. The linearised value is
the location of the person on the unidimensional continuum - the value
is called a parameter in the model and there can be only one number in a
unidimensional framework. This parameter can then be used in analysis
of variance and regression more readily than the raw total score which
has floor and ceiling effects.
- A researcher who is developing items of a test or questionnaire intending to sum the scores on the items can use a Rasch model analysis to check the degree to which this scoring and summing is defensible in the data collected. For example, if two groups are to be compared on the variable of interest (e.g. males and females), it is important to demonstrate that the workings of the items is the same in the two groups. Working in the same way permits interpreting the total score as meaning the same in the two groups.
- In checking how well the data fit the model, it is important to be able to diagnose very quickly where the misfit is the worst, and then proceed to try to understand this misfit in terms of the construction of the items and the understanding of the variable in terms of its theoretical development.
- A very important part of the Rasch analysis from this perspective is to be in dynamic and interactive control of an analysis and to be able to follow the evidence to see where the responses may be invalid.
(Sources: http://www.rasch-analysis.com/rasch-measurement.htm)
Our next workshop. Don't miss it!
| Date |
»
|
19 & 20 May 2014 (Monday - Tuesday) |
| Time |
»
|
8.30 a.m. - 5.30 p.m. |
| Venue |
»
|
MPWS Training Centre,
63-1, 63-2, Jalan Kajang Impian 1/11, Taman Kajang Impian, Seksyen 7, 43650 Bandar Baru Bangi, Selangor # map |
| Speaker |
»
|
Dr. Akbariah Binti Mohd Mahdzir |
| Registration Fee |
»
|
RM300 (early bird rate) / RM400 (normal rate) |
| Medium |
»
|
English |
| Website |
»
|
http://postgraduateworkshop.com/raschanalysis |
No comments:
Post a Comment