Posted by
Art Kendall on
Nov 15, 2017; 1:47pm
URL: http://spssx-discussion.165.s1.nabble.com/combining-scores-from-questions-measuring-the-same-construct-but-with-different-scales-tp5735150p5735153.html
For the benefit of those who may look at this topic in the archives:
Unfortunately many intro courses fail to communicate basic principles
clearly. Two of these are:
(1) that it possible to *coarsen* measurements, but it is not possible to
to refine them, i.e., make them more fine grained. For measures of
location, if one only asks state, it is not possible to break down results
by county. Recall that the maximum correlation a variable can have is
limited by how many legitimate values are in you data.
(2) Failing to prompt number line thinking. Note that the first example
first response scale does not go from less to more liking. In many cultures
"un", less, low, West, etc are on the left end of a number line. Unless you
are stuck with strictly nominal level measurements, it is desirable to
implicitly prompt number line thinking.)
For the OP:
Is it correct that these are not repeated measures of the same construct,
but that the construct was measured differently by different groups of
respondents?
Do you intend to relate the liking construct to other variables in each data
set? If so, an additional approach to z-scores would be to calculate some
association/similarity/correlation, and think in a meta-analytic framework
of analyzing set of coefficients.
If you have just these 3 studies, you could show sets of 3 scatterplots
(with or without regression or loess fits). That would be 1 set for each
variable you want to relate to liking, e.g., age, gender, physical test
results, etc.
List members, I need to go to a meeting, but if someone has the time to
generate syntax to
(1) create a simulation with a known pop correlation with continuous X and
Y, then coarsen Y to 10,9,8,. . .2 levels
(2) correlate Xwith the set of 11 Y variables.
This would be a nice exercise for instructors to have when discussing
measurement levels, etc.
-----
Art Kendall
Social Research Consultants
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Art Kendall
Social Research Consultants