# [Rasch] Re: Rasch Digest, Vol 35, Issue 12

Thomas Salzberger Thomas.Salzberger at wu-wien.ac.at
Wed Jul 2 06:11:44 EST 2008

```Juanito,

I am not sure whether you got a response already.
I had to sort out my internet access, so I was offline a copule of days.

>1. For each item (or person), Rasch provides m-1
>thresholds for the m response categories.  The
>arithmetic mean of the m-1 thresholds for each
>item(person) is then the item (or person)
>location or commonly called item (or person) measure.  Am I right?
>

Yes, the mean of the thresholds (the tau
parameters) is the (overall) item location
(delta). However, for persons there is just one
parameter, so no need to calculate a mean.

>
>
>2. If we call the item measure as "item
>endorsability", how do we call the person measure?
I personally call them simply person measures.
You may call it attitude or measure of attitude
(if it attitude what you are measuring) or whatever it is.

>3. What is your idea about the infit and outfit for each measure?

Infit and outfit are provided by winsteps. I am
not familiar with winsteps. The outfit is said to
be equivalent to RUMM's fit residual. As it is
the case with all fit statistics, it is not so
much one statistic that counts but you should use
multiple fit/misfit indicators.

>4. Relative to the instrument, how do we
>interpret the item and person separation and reliability?
First, note that separation is defiend
differently in RUMM and WINSTEPS, respectively.
In RUMM, person separation essentially is
reliability using the Rasch measures. It is what
it is in classical test theory. It tells you how
well the instrument discriminates between the
persons in the sample. Its sample dependence
makes it much less relevant in Rasch analysis
compared to classical test theory. In RUMM, it is
used as a (rough) indication of the power of the
test of fit (excellent, very good etc. the
classification solely sepends on the person
separation index). In practice, many factors
influence the person separation. If person
separation is very low, there are major problems
in the data, in most cases, the items do not form
a unidimensional scale but represent more or less
unique ideas. In summary, the fit statistics and
the correspondence of what you expected from the
items and the actual item location estimates
count more than a high person separation.

Liebe Gruesse
Thomas Salzberger
_______________________________________________________
Dr. Thomas Salzberger
Österreichische Gesellschaft für Absatzwirtschaft
c/o Department of Marketing, Institute for Marketing Management
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