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.