Association Models
Nonfiction, Reference & Language, Reference, Research, Social & Cultural Studies, Social Science, Sociology
| Author: | Raymond Sin-Kwok Wong | ISBN: | 9781483343044 |
| Publisher: | SAGE Publications | Publication: | February 9, 2010 |
| Imprint: | SAGE Publications, Inc | Language: | English |
| Author: | Raymond Sin-Kwok Wong |
| ISBN: | 9781483343044 |
| Publisher: | SAGE Publications |
| Publication: | February 9, 2010 |
| Imprint: | SAGE Publications, Inc |
| Language: | English |
Offers readers invaluable guidance on handling cross-classified data
Broadening the scope of association models beyond the typical sociological and psychological fields, author Raymond S. Wong shows readers how to analyze and comprehend any social science data presented in cross-classified formats. Through a careful exposition of various association models, the text examines the underlying structure of odds-ratios, offering a unified framework for students and researchers in the process.
Rich illustrative examples (from data generated by the General Social Survey and other sources) demonstrate why and how association models are a better option than conventional log-linear models or non-parametric specifications.
This resource is appropriate for graduate students and researchers across the social and behavioral sciences who need to chose and apply the appropriate statistical tools to decipher and interpret cross-classified data. Students can enhance their experience by visiting the study site at www.sagepub.com/wongstudy.
Offers readers invaluable guidance on handling cross-classified data
Broadening the scope of association models beyond the typical sociological and psychological fields, author Raymond S. Wong shows readers how to analyze and comprehend any social science data presented in cross-classified formats. Through a careful exposition of various association models, the text examines the underlying structure of odds-ratios, offering a unified framework for students and researchers in the process.
Rich illustrative examples (from data generated by the General Social Survey and other sources) demonstrate why and how association models are a better option than conventional log-linear models or non-parametric specifications.
This resource is appropriate for graduate students and researchers across the social and behavioral sciences who need to chose and apply the appropriate statistical tools to decipher and interpret cross-classified data. Students can enhance their experience by visiting the study site at www.sagepub.com/wongstudy.
