A procedure is presented to generate standardized
scores from raw test data that are, as far as
possible, age independent and normally distributed.
The model is fitted to the percentile points of
the raw score distribution, and assumes a linear
trend of each percentile with age. The fitted slopes
can be constant or can vary quadratically with the
percentiles. A nonlinear transformation of the data
is also possible to allow for "ceiling effects."
These models are described and the methods used
to fit them to test data are discussed; examples are
presented of their use in standardizing tests, and
the use of the diagnostic plots produced by the
program are discussed. Index terms: age standardization,
linear regression, nonlinear regression,
nonparallel regression, parallel linear regression, percentiles,