文档介绍：Introductory Biostatistics. Chap T. Le
Copyright ¶ 2003 John Wiley & Sons, Inc.
ISBN: 0-471-41816-1
8
CORRELATION AND REGRESSION
Methods discussed in Chapters 6 and 7 are tests of significance; they provide
analyses of data where a single measurement was made on each element of a
sample, and the study may involve one, two, or several samples. If the mea-
surement made is binary or categorical, we are often concerned with -
parison of proportions, the topics of Chapter 6. If the measurement made is
continuous, we are often concerned with parison of means, the topics of
Chapter 7. The main focus of both chapters was the di¤erence between pop-
ulations or subpopulations. In many other studies, however, the purpose of the
research is to assess relationships among a set of variables. For example, the
sample consists of pairs of values, say a mother’s weight and her newborn’s
weight measured from each of 50 sets of mother and baby, and the research
objective is concerned with the association between these weights. Regression
analysis is a technique for investigating relationships between variables; it can
be used both for assessment of association and for prediction. Consider, for
example, an analysis of whether or not a woman’s age is predictive of her
systolic blood pressure. As another example, the research question could be
whether or not a leukemia patient’s white blood count is predictive of his sur-
vival time. Research designs may be classified as experimental or observational.
Regression analyses are applicable to both types; yet the confidence one has in
the results of a study can vary with the research type. In most cases, one vari-
able is usually taken to be the response or dependent variable, that is, a vari-
able to be predicted from or explained by other variables. The other variables
are called predictors,orexplanatory variables or independent variables. The
examples above, and others, show a wide range of applications in which