Association Models

This book offers a unified framework for analyzing social science data in cross-classified formats, enhancing understanding and application for researchers and students.

In Association Models, author Raymond S. Wong provides a comprehensive framework designed to assist students and researchers in navigating the complexities of social science data organized in cross-classified formats. The book broadens the traditional scope of association models, extending their application beyond just sociological and psychological contexts. Wong meticulously illustrates various association models, emphasizing their advantages over conventional methods such as log-linear models and non-parametric specifications. This approach not only enhances understanding but also equips readers with the necessary tools to analyze diverse datasets effectively.

Rich with illustrative examples drawn from reputable sources like the General Social Survey, Association Models showcases the practical application of these models. Wong explains the underlying structure of odds ratios in a clear and accessible manner, making complex concepts easier to grasp. The text is designed to be a valuable resource for graduate students and researchers in the social and behavioral sciences, guiding them in selecting and applying the appropriate statistical techniques for their specific research needs.

Ultimately, Association Models serves as an essential guide for those looking to deepen their understanding of cross-classified data analysis. By providing a unified framework, Wong empowers readers to make informed decisions in their research, ensuring they can effectively interpret and derive meaningful insights from their data.