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Image Analysis

April 14, 2010

Although I’ve been absent from this blog for well over a month, I haven’t abandoned it. I have been busy working on a few projects that are using Bayesian methods and have been very busy with school work. The projects that I have been working on are the multilevel ZIP project that I’ve been discussing on this blog for a while and the other one is a confirmatory factor analysis project. I will be giving presentations on both of these approaches on the 27th of April and will post PDFs of these talks. The latter talk, on CFA, will also include code for rjags, a package to call JAGS from R. I’ve been playing around with this particular Gibbs Sampler a little bit and I think it’s a good option for Linux and Mac users. So I will be posting some code on here, similar to my SEM code, but this time it will be JAGS and rjags syntax and therefore can be used on all platforms without the need of wine.

On a related note, I recently gave a talk on Guttman’s image analysis for a seminar on factor analysis. Image analysis seems to be pretty interesting and able to overcome many of the issues associated with factor analysis, including factor score indeterminancy and factorial invariance. However, there are still issues of rotational indeterminancy. Basically image analysis breaks manifest variables into two chunks: Images and partial anti-images. The images are the parts of a variable that are shared with the other manifest variables, while the anti-image is the part that is unique. Further, images are similar to common factors and the anti-image is similar to unique factors. If you are interested in factor analysis, please read my image analysis talk (by clicking here) and let me know what you think. I am not an expert on image analysis but am happy to host a discussion on the topic and will try to answer questions.

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