An Introduction to Generalized Linear Models
Nonfiction, Reference & Language, Reference, Research, Social & Cultural Studies, Social Science
| Author: | George Henry Dunteman, Dr. Moon-Ho R. Ho | ISBN: | 9781506320748 |
| Publisher: | SAGE Publications | Publication: | September 22, 2005 |
| Imprint: | SAGE Publications, Inc | Language: | English |
| Author: | George Henry Dunteman, Dr. Moon-Ho R. Ho |
| ISBN: | 9781506320748 |
| Publisher: | SAGE Publications |
| Publication: | September 22, 2005 |
| Imprint: | SAGE Publications, Inc |
| Language: | English |
Do you have data that is not normally distributed and don't know how to analyze it using generalized linear models (GLM)? Beginning with a discussion of fundamental statistical modeling concepts in a multiple regression framework, the authors extend these concepts to GLM and demonstrate the similarity of various regression models to GLM. Each procedure is illustrated using real life data sets. The book provides an accessible but thorough introduction to GLM, exponential family distribution, and maximum likelihood estimation; includes discussion on checking model adequacy and description on how to use SAS to fit GLM; and describes the connection between survival analysis and GLM. It is an ideal text for social science researchers who do not have a strong statistical background, but would like to learn more advanced techniques having taken an introductory course covering regression analysis.
Do you have data that is not normally distributed and don't know how to analyze it using generalized linear models (GLM)? Beginning with a discussion of fundamental statistical modeling concepts in a multiple regression framework, the authors extend these concepts to GLM and demonstrate the similarity of various regression models to GLM. Each procedure is illustrated using real life data sets. The book provides an accessible but thorough introduction to GLM, exponential family distribution, and maximum likelihood estimation; includes discussion on checking model adequacy and description on how to use SAS to fit GLM; and describes the connection between survival analysis and GLM. It is an ideal text for social science researchers who do not have a strong statistical background, but would like to learn more advanced techniques having taken an introductory course covering regression analysis.
