Re: Presenting unorthodox factor analysis findings
- From: Ray Koopman <koopman@xxxxxx>
- Date: Mon, 7 Jan 2008 23:28:13 -0800 (PST)
On Jan 7, 2:39 pm, shysong <shys...@xxxxxxxxx> wrote:
Hi everyone,
I have a somewhat unorthodox set of findings and I'm trying to figure
out what the best way of presenting them would be in a paper or
abstract. I have a set of 12 measures that were collected over 7 time
points on approximately 133 subjects. I ran an exploratory factor
analysis with the measures at each of the time points, to see what the
factor structure was and whether the factor structure was stable over
the 7 time points.
The bad news is that the factor structure was not stable over time;
some time points showed a four factor structure whereas others showed
a five factor structure. And the measures that fell into the each
factor tended to vary somewhat. The interesting finding, however, was
that there were small clusters of variables that always seemed to
appear together, regardless of what factor they were in. So for
example, measures 1 and 2 always appeared together, almost always as
a single factor, though sometimes they were factor 3 and sometimes
they were factor 4; measures 6,8,9, and 10 appeared together in 1/2 of
the time points, always as factor 1 (factor 1 was always composed of
four measures).
This is the finding that I would like to present, because the sets of
variables that cluster together consistently are of interest. But of
course, this is not the usual kind of thing you report from a factor
analysis. So the question is, what would an appropriate table in the
results section contain? Maybe a graph with correlations over time?
Any ideas would be appreciated on how to credibly present and report
the piece of the analysis I'm interested in.
Many thanks,
Sylvia Hysong
Probably the best you can do is to treat your results as suggestive,
a source of hypotheses for future studies, and to hope that your
audience is sympathetic to the substance of what you have to say and
is willing to forgive the lack of methodological rigor. Your results
will be accepted more or less to the extent that you can point to
previous theory and data that make them seem unsurprising, to-be-
expected. And even then there will almost certainly be suggestions,
some of which you may have to accede to, as to how you ought to re-
analyze your data.
.
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