The clinical actuarial controversy relates to whether it's better
to make decisions using our own best human judgment,
based on our experience and training and so on,
or whether it's better to make decisions using statistical models.
These are called actuarial models.
They might be developed by multiple regression or analysis of variance.
The question is, which of these is better?
This is an ongoing controversy and with people
on both sides of the controversy have very strong feelings.
This becomes very emotional.
With the actuarial approach to judgment,
we simply eliminate the human judge.
Instead, we use forums such as multiple regression analysis to
find how predictor variables seem to combine and how they're weighted,
in order to best predict some criterion variables,
some outcome or event of interest.
For example, if we wanted to predict psychosis,
we might consider a set of variables that we think might be predictors
at the extent to which those variables do in fact predict psychosis,
and the resulting model, the actuarial model,
could then be used to predict whether
particular individuals would show signs of psychosis.