Logistic Regression: A Self-learning Text, Third Edition (Statistics in the Health Sciences)

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Introduction We begin our discussion of statistical inference by describ-
ing the computer information required for making infer-
ences about the logistic model. We then introduce
examples of three logistic models that we use to describe
hypothesis testing and confidence interval estimation pro-
cedures. We consider models with no interaction terms
first, and then we consider how to modify procedures
when there is interaction. Two types of testing procedures
are given, namely, the likelihood ratio test and the Wald
test. Confidence interval formulae are provided that are
based on large sample normality assumptions. A final
review of all inference procedures is described by way of
a numerical example.


Abbreviated
Outline


The outline below gives the user a preview of the material
to be covered by the presentation. A detailed outline for
review purposes follows the presentation.

I. Overview (page 132)
II. Information for making statistical inferences
(pages 132–133)
III. Models for inference-making (pages 133–134)
IV. The likelihood ratio test (pages 134–138)
V. The Wald test (pages 138–140)
VI. Interval estimation: one coefficient
(pages 140–142)
VII. Interval estimation: interaction (pages 142–146)
VIII. Numerical example (pages 146–153)

130 5. Statistical Inferences Using Maximum Likelihood Techniques

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