Looking for an examination copy?
This title is not currently available for examination. However, if you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact email@example.com providing details of the course you are teaching.
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. Data, R, and SAS scripts can be found online at http://www.spesi.org.Read more
- Designed for scientists and students with minimal mathematical background and limited modeling experience
- Full R and SAS code for all analyses is available for free download
- Uses real and publicly available data sets, showing common issues and their solutions
Reviews & endorsements
'This book is a guide to modeling and analyzing non-Gaussian and correlated data. There is clearly a need for such a book to help less experienced data scientists … The data sets and models are well explained, and the limitations of each type of model on the various data sets is illustrated by frequent plots.' Peter Rabinovitch, MAA Reviews
Not yet reviewed
Be the first to review
Review was not posted due to profanity×
- Date Published: July 2017
- format: Paperback
- isbn: 9781316601051
- length: 228 pages
- dimensions: 254 x 178 x 10 mm
- weight: 0.48kg
- availability: In stock
Table of Contents
1. The data sets
2. The model-building process
3. Constance variance response models
4. Non-constant variance response models
5. Discrete, categorical response models
6. Counts response models
7. Time-to-event response models
8. Longitudinal response models
9. Structural equation modeling
10. Matching data to models.
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email firstname.lastname@example.orgRegister Sign in
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.Continue ×
Are you sure you want to delete your account?
This cannot be undone.
Thank you for your feedback which will help us improve our service.
If you requested a response, we will make sure to get back to you shortly.×