🚀 go-pugleaf

The issue of phi coefficients in factoring dichotomous data is a RED HERRING.
If the data are dichotomous, SAS, SPSS and other packages will yield a matrix
of PEARSON correlations, NOT phi coefficients.  True, extreme p values will
skew the data, but that's because of the DATA, not the correlation matrix.
You'll know if this is a problem in your particular data set if you get
Heywood cases (loadings greater than 1.00).  But until this becomes an
actual problem, go ahead and factor.  The issue of scaled loadings reflecting
differential "skill levels" calls into question when in the research sequence
the factor analysis is performed. IRT (Hambleton et al) deal effectively with
this question.   John

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John B. Collins                         Voice Tel: (604) 922-4223
Adult Education Research Centre               Fax: (604) 622-6665
University of British Columbia        e-mail: USERJBC@MTSG.UBC.CA
Vancouver, B. C.  CANADA
      V6T 1W5
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