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By definition, the primary focus of the study of human individual
differences is on variation. As we have seen, the covariation between
family members can be especially informative about the causes of
variation, so we now turn to the statistical techniques used to
measure both variation within and covariation between family
members. We start by reviewing
the calculation of variances and covariances by hand, and then
illustrate how one may use pograms such as SAS, SPSS and PRELIS
[SAS, 1988,SPSS, 1988,] to compute these summary
statistics in a convenient form for use with
Mx. Our initial treatment assumes that we have well-behaved,
normally-distributed variables for analysis
(see Section 2.2).
However, almost all studies involve some measures that are certainly
not normal because they consist of a few ordered categories, which we
call *ordinal* scales. In Section 2.3,
we deal with the summary of these cruder forms of
measurement, and discuss the concepts of degrees of freedom and
goodness-of-fit that arise in this context.
During this decade advances in computer software and hardware have
made the direct analysis of raw data quite practical. As we shall
see, this method has some advantages over the analysis of summary
statistics, especially when there are missing data. Section 2.4
describes the preparation of raw data for analysis with Mx.

** Next:** 2 Continuous Data Analysis
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Jeff Lessem
2002-03-21