Thanks for the detailed response, Aeh.
We wrapped up the testing process last week, and everything went smoothly, thanks to the resources provided by Indigo and other info found on this forum. We haven�t received the detailed report yet, but we know he qualified for DYS!
I have a few more questions after doing some more research, if you don�t mind indulging my curiosity a bit further:
From what I�ve since read about factor analysis, it picks the axis which minimizes the average shortest distance between each data point and the axis and projects each data point onto this axis using its aforementioned shortest distance. It then scales the projected point toward the mean by the average of the variances of the data along axes orthogonal to the chosen axis (unexplained variance) in order to extract the correlation between the variables by eliminating the correlation among the error vectors (vectors pointing from the final projected, scaled point to the original data point). This also implies that the result will stop changing as more variables with similar correlations to the original group are added, as there�s only so much correlation to extract.
Data from the technical and interpretive manual show the correlations between indices and their two primary subtests is very high, often above 0.9 (such as SI and VC with VCI both above 0.9), but correlations between indices and their extra subtests is much lower, usually around 0.7. This to me seems like the indices were computed based on only their primary subtests, while the extra subtests were kept around due to having similar correlations with the primary subtests as the primary tests have with each other (as that would suggest the average unexplained variance wouldn�t change significantly if substituted in for the FSIQ, but could have a sizable effect if substituted in for an index score, as there are only two to substitute). Is this why substitutions are only allowed for the FSIQ (and why the average score < composite score effect described in my original post doesn�t apply to the expanded indices)?
However, the GAI and CPI have middling correlation with each other but high correlation with the FSIQ (analogous to VC and SI with the VCI), yet the FSIQ is a direct average of those two indices (whereas the VCI gets a boost); is this due to the FSIQ explaining most of the correlation among subtests within the GAI and CPI separately?
Thanks in advance.
