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Online Public Access Catalogue

题名/责任者:

Handbook for Applied Modeling: Non-Gaussian and Correlated Data Jamie D. Riggs,Trent L. Lalonde

出版发行项:

Cambridge University Press 2017

ISBN:

9781107146990

载体形态项:

236

翻译题名:

应用建模手册: 非高斯和相关数据

一般附注:

Hardcover

摘要附注:

Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data. Many practitioners work with data that fail the assumptions of the common linear regression models, necessitating more advanced modeling techniques. This Handbook presents clearly explained modeling options for such situations, along with extensive example data analyses. The book explains core models such as logistic regression, count regression, longitudinal regression, survival analysis, and structural equation modelling without relying on mathematical derivations. All data analyses are performed on real and publicly available data sets, which are revisited multiple times to show differing results using various modeling options. Common pitfalls, data issues, and interpretation of model results are also addressed. Programs in both R and SAS are made available for all results presented in the text so that readers can emulate and adapt analyses for their own data analysis needs.

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