Hi everyone,
My son is taking the WISC-V soon, and I�m trying to learn all I can about the test. After reading the
extended norms report, I�m left with a couple questions:
If I understand correctly, the WISC-V subtests are all normally distributed and imperfectly correlated with one another, so composite indices derived from multiple subtests should have lower standard deviations than what is obtained through averaging those of its components (for example, an index comprised of two subtests with mean = 10 and standard deviation = 3: an index averaging the two should have a mean of 10 but a standard deviation less than 3). This makes sense to me, as a student averaging +1 SD on two sufficiently unique but equally relevant tasks would yield a > +1 SD composite score. Indices such as the VCI and FRI, both derived from two subtests, seem to support this, as a sum of 38 on either index, or average score of 19 (+3 SD), yields a composite score of 155 (+3.67 SD). The effect is even stronger in the GAI, derived from five subtests: an average subtest score of 19 yields a GAI of 160 (+4 SD). However, when three more subtests are added to the GAI to make the EGAI, the effect stays the same (mean = 19 : +4 SD). This is also true for the VCI and VECI and the GAI, CPI, and FSIQ. Was this done to maintain consistency in interpretation, or have the additional subtests been designed with substitution in mind? In the last case, the FSIQ seems to be an average of the other two top-level indices.
I am also struggling to understand why the confidence intervals listed are the same size throughout the scaled score continuum for every index. From what I�ve read on Item Response Theory, the standard error of measurement is calculated from the inverse square root of the test�s information function (which I assume is high around the average score of 100 and tapers off at the extremes, since the test is designed to work best around the population average). I took the expected score moving up within the confidence intervals the higher the score as an indication of the information function bottoming out and scores subsequently regressing to the mean, but the size of the SEm appears to be constant. The gifted sample undoubtedly helps in providing more information for the upper extreme, but even so, I can�t imagine why the SEm wouldn�t change throughout such a large scale.
I am neither a psychologist nor a statistician, so anything I�ve written here could be erroneous; nevertheless, any help would be appreciated.
Thanks in advance.
