"Clinical versus Statistical Prediction" is Paul Meehl's famous
examination of benefits and disutilities related to the different
ways of combining information to make predictions. It is a
clarifying analysis as relevant today as when it first
appeared.
A major methodological problem for clinical psychology concerns
the relation between clinical and actuarial methods of arriving at
diagnoses and predicting behavior. Without prejudging the question
as to whether these methods are fundamentally different, we can at
least set forth the obvious distinctions between them in practical
applications. The problem is to predict how a person is going to
behave: What is the most accurate way to go about this task?
"Clinical versus Statistical Prediction" offers a penetrating
and thorough look at the pros and cons of human judgment versus
actuarial integration of information as applied to the prediction
problem. Widely considered the leading text on the subject, Paul
Meehl's landmark analysis is reprinted here in its entirety,
including his updated preface written forty-two years after the
first publication of the book.
This classic work is a must-have for students and practitioners
interested in better understanding human behavior, for anyone
wanting to make the most accurate decisions from all sorts of data,
and for those interested in the ethics and intricacies of
prediction. As Meehl puts it, ""When one is dealing with human
lives and life opportunities, it is immoral to adopt a mode of
decision-making which has been demonstrated repeatedly to be either
inferior in success rate or, when equal, costlier to the client or
the taxpayer.""
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