Factor Analysis help--Senior Thesis

I am an undergraduate and working on my senior research project. I am doing a study of the construct validity of a critical thinking test using factor analysis. The test is 52 item multiple choice test (a, b, or c) with 6 subtests. According to the developer, the test measures 6 aspects of critical thinking. As the developer has a background in philosophy, it seems relevant to validate the test using quantitative methodology and determine whether the test actual measures 6 distinct constructs.

Here’s where I’m at. I have an extremely large sample size (N=1000) and have coded all of the individual responses of each case (a=1, b=2, c=3). I originally thought that examining the variances in the actual responses my reveal a factor structure, but now realize that since the test is not uniform (“a” does not mean the same thing throughout the test) that would be inappropriate. Thus, I have transformed the responses to correct or incorrect (0=incorrect, 1=correct). It seems logical that if individuals were deficient in a particular area of the hypothesized critical thinking construct, then their incorrect response variances would emerge in a factor structure (and vice versa). Now however, I am having reservations about the appropriateness of conducting a factor analysis on binary data. I have searched many forums and sought much advice and seem to get a lot of contradictory information. My advisor thinks that factor analysis is still the way to go, but I am not so sure. Any advice on this matter would be greatly appreciated.
Factor Analysis and binary data

Yes to using factor analysis. In fact, factor analysis is used extensively in educational testing where the answers are binary coded. So go ahead with your analysis.


TS Contributor
Factor analysis is used when the data are at least ordinal with at least 7-8 levels. If the data are 0 and 1 latent class analysis is used. How about cluster analysis? it is easy in SPSS.