Get 20M+ Full-Text Papers For Less Than $1.50/day. Subscribe now for You or Your Team.

Learn More →

Applied Logistic Regression Analysis

Applied Logistic Regression Analysis BOOK REVIEWS section covers polytomous response variable classifications in a similar spirit to the coverage of binary response variables given earlier in the chapter. The third chapter covers the topic of inference-how to draw conclusions about the population from a sample. The chapter covers the topics of likelihood and how this can be used to estimate the parameters in a hypothesized model and their standard errors. Other topics discussed include the calibration process, testing the goodness of fit and sample size calculations. A wide range of statistical distributions are described in Chapter Four. The first group of distributions considered is those relevant to count data: uniform, binomial, Poisson, negative bino­ mial, geometric and zeta distributions. The second section covers distributions which derive from the normal-distribution: the power transformed normal (i.e. Box-Cox), log-normal, inverse Gaussian, logistic and the normal distribution itself. Duration distributions are considered next: exponential, Pareto, gamma and Weibull distributions. In all the sections examples are given of survey data which may be approximated by each distribution. Chapter Five covers the topics of normal regression and analysis of variance. The explanation given of both these modelling tools is clear, but brief. This section also contains material on the http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the Royal Statistical Society Series D: The Statistician Oxford University Press

Loading next page...
 
/lp/oxford-university-press/applied-logistic-regression-analysis-NiUe8xqkS9

References (0)

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
Oxford University Press
Copyright
© 1996 Royal Statistical Society
ISSN
2515-7884
eISSN
1467-9884
DOI
10.2307/2988559
Publisher site
See Article on Publisher Site

Abstract

BOOK REVIEWS section covers polytomous response variable classifications in a similar spirit to the coverage of binary response variables given earlier in the chapter. The third chapter covers the topic of inference-how to draw conclusions about the population from a sample. The chapter covers the topics of likelihood and how this can be used to estimate the parameters in a hypothesized model and their standard errors. Other topics discussed include the calibration process, testing the goodness of fit and sample size calculations. A wide range of statistical distributions are described in Chapter Four. The first group of distributions considered is those relevant to count data: uniform, binomial, Poisson, negative bino­ mial, geometric and zeta distributions. The second section covers distributions which derive from the normal-distribution: the power transformed normal (i.e. Box-Cox), log-normal, inverse Gaussian, logistic and the normal distribution itself. Duration distributions are considered next: exponential, Pareto, gamma and Weibull distributions. In all the sections examples are given of survey data which may be approximated by each distribution. Chapter Five covers the topics of normal regression and analysis of variance. The explanation given of both these modelling tools is clear, but brief. This section also contains material on the

Journal

Journal of the Royal Statistical Society Series D: The StatisticianOxford University Press

Published: Dec 5, 2018

There are no references for this article.