http://spssx-discussion.165.s1.nabble.com/do-repeat-tp5719707p5719794.html
Can you explain me more on applying regression results to rescore? I have not come across such technique and would appreciate if you can throw some light.
Once I am done with this issue on hand, I am going to conduct a seperate study to measure the impact and will be more than happy to share the results with you all.
> Mike,
>
> The only thing I can think of is to run the survey on a subset of
> individuals (preferably a stratified random sample) using both forms of the
> scale. Then regress one score on the other. You can then apply the
> regression results to rescore your previous survey into the alternative
> scale form.
>
> Garry Gelade
>
>
> -----Original Message-----
> From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of MR
> Sent: 28 April 2013 01:23
> To:
[hidden email]
> Subject: Normalizing scores
>
> Team,
>
> I have one problem on my hand and am running out of options on which
> statistics to use in SPSS. First, I know that the what I want to do is not
> advisable but trust me, I have fought my battle on this. This is what I want
> to achieve:
>
> Issue: We did wave 1 survey using 5-point satisfaction scale. The second
> wave was conducted using 5-point agreement scale. Expectedly, top-box scores
> from agreement scale when compared to top-box score of satisfaction scale
> was low by 10% points. For e.g., agreement scale top box in wave 2 came out
> as 50% while wave 1 it was 60%.
>
> Goal: I have compared the historical data and conclude that score difference
> is purely due to scale change. However, i want to normalize the wave 2 score
> so that I can compare with wave 1. I know this is not advisable but I have
> to do this. I googled but could not find any statistics that helps to
> normalize the scores - indeed I don't know where to begin. I need a
> scientific method to normalize the scores so that they are comparable. I
> don't want to conclude that performance dropped by 10% just because scale
> changed.
>
> Your wisdom and help is very much required.
>
> Thanks,
> Mike
>
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