Looking for an inspection copy?
This title is not currently available for inspection. However, if you are interested in the title for your course we can consider offering an inspection copy. To register your interest please contact email@example.com providing details of the course you are teaching.
Logistic models are widely used in economics and other disciplines and are easily available as part of many statistical software packages. This text for graduates, practitioners and researchers in economics, medicine and statistics, which was originally published in 2003, explains the theory underlying logit analysis and gives a thorough explanation of the technique of estimation. The author has provided many empirical applications as illustrations and worked examples. A large data set - drawn from Dutch car ownership statistics - is provided online for readers to practise the techniques they have learned. Several varieties of logit model have been developed independently in various branches of biology, medicine and other disciplines. This book takes its inspiration from logit analysis as it is practised in economics, but it also pays due attention to developments in these other fields.Read more
- Written not only for economists but for those working in statistics, social sciences and medicine
- Many worked examples
- Large online data set for readers to practise learned techniques
Reviews & endorsements
Review of the hardback: '…the worked examples … will be invaluable for those new to logit analysis.' Short Book Reviews
Not yet reviewed
Be the first to review
Review was not posted due to profanity×
- Date Published: March 2011
- format: Paperback
- isbn: 9780521188036
- length: 184 pages
- dimensions: 229 x 152 x 11 mm
- weight: 0.28kg
- availability: Available
Table of Contents
2. The binary model
3. Maximum likelihood estimation of the binary logit model
4. Some statistical tests and measures of fit
5. Outliers, misclassification of outcomes, and omitted variables
6. Analyses of separate samples
7. The standard multinomial logit model
8. Discrete choice of random utility models
9. The origins of the logistic function.
Find resources associated with this titleYour search for '' returned .
Type Name Unlocked * Format Size
This title is supported by one or more locked resources. Access to locked resources is granted exclusively by Cambridge University Press to lecturers whose faculty status has been verified. To gain access to locked resources, lecturers should sign in to or register for a Cambridge user account.
Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other lecturers may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.
Supplementary resources are subject to copyright. Lecturers are permitted to view, print or download these resources for use in their teaching, but may not change them or use them for commercial gain.
If you are having problems accessing these resources please contact firstname.lastname@example.org.
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email email@example.comRegister 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.×