Abstract
We begin our discussion of statistical inference by describing the computer information required for making inferences about the logistic model. We then introduce examples of three logistic models that we use to describe hypothesis testing and confidence interval estimation procedures. 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.
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© 2010 Springer Science+Business Media, LLC
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Kleinbaum, D.G., Klein, M. (2010). Statistical Inferences Using Maximum Likelihood Techniques. In: Logistic Regression. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1742-3_5
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DOI: https://doi.org/10.1007/978-1-4419-1742-3_5
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-1741-6
Online ISBN: 978-1-4419-1742-3
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