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Books > Science & Mathematics > Mathematics > Probability & statistics
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Regression with Linear Predictors (Hardcover, 2010 ed.)
Loot Price: R1,674
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Regression with Linear Predictors (Hardcover, 2010 ed.)
Series: Statistics for Biology and Health
Expected to ship within 10 - 15 working days
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This is a book about regression analysis, that is, the situation in
statistics where the distribution of a response (or outcome)
variable is related to - planatory variables (or covariates). This
is an extremely common situation in the application of statistical
methods in many ?elds, andlinear regression, - gistic regression,
and Cox proportional hazards regression are frequently used for
quantitative, binary, and survival time outcome variables,
respectively. Several books on these topics have appeared and for
that reason one may well ask why we embark on writing still another
book on regression. We have two main reasons for doing this: 1.
First, we want to highlightsimilaritiesamonglinear, logistic,
proportional hazards,
andotherregressionmodelsthatincludealinearpredictor. These
modelsareoftentreatedentirelyseparatelyintextsinspiteofthefactthat
alloperationsonthemodelsdealingwiththelinearpredictorareprecisely
the same, including handling of categorical and quantitative
covariates, testing for linearity and studying interactions. 2.
Second, we want to emphasize that, for any type of outcome
variable, multiple regression models are composed of simple
building blocks that areaddedtogetherinthelinearpredictor: thatis,
t-tests, one-wayanalyses of variance and simple linear regressions
for quantitative outcomes, 2x2, 2x(k+1) tables and simple logistic
regressions for binary outcomes, and 2-and (k+1)-sample logrank
testsand simple Cox regressionsfor survival data.
Thishastwoconsequences. Allthesesimpleandwellknownmethods can be
considered as special cases of the regression models. On the other
hand, the e?ect of a single explanatory variable in a multiple
regression model can be interpreted in a way similar to that
obtained in the simple analysis, however, now valid only for the
other explanatory variables in the model "held ?xed.""
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