Hi All,
In analysing data from a large number of items in a questionaire, a collegue
and myself undertook an exploratory factor analysis. Subsequently it was
possible to investigate the factor scores to see if they were influenced by
'demographic' variables i.e. did the factor scores differ between professions,
were they related to age groups, sex etc.
However having used FA to identify the structure within the data we decided
that
rather than further analysing the factor scores, we would prefer to analyse a
'representative item' from each factor - one of the original questions, the
result of which was highly correlated to the factor score and (obviously) to
other items which were themselves highly correlated to the factor score. Our
logic for doing this was that it would be easier for the readers to
interpret our findings if we related them to original items on the questionaire
- and also that in demonstrating the 'effect size' of differences (say) between
sexes it was clearer to tell the reader that the mean score for males was 1.2
and for females was 3.5 rather than telling them the difference in factor
scores. Not surprisingly the results from interpreting the factor scores and
the representative items are essentially the same.
A reviewer has indicated that they don't think that analysing representative
items is a valid approach to the analysis stating that the purpose of
identifying factors is to develop scores based upon multiple items; I quite
agree that this is a benefit/use of FA; but I can't instantly see that our
approach is flawed.
The reviewer may well be right - I am not the greatest expert on FA;
consequently I would most grateful to members of the list if they could tell me
if analysing 'representative items' is/is not a legitamate approach.
Many thanks
Graham Clarke
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