Log-Linear Models, Vol. 2

Discusses the innovative log-linear model of statistical analysis. This model makes no distinction between independent and dependent variables, but is used to examine relationships among categoric variables by analyzing expected cell frequencies.

Introduces methods for quantitative assessment of relationships among categoric variables in multivariable crosstabulations. Procedures to estimate and interpret effect parameters for hierarchical models are described for both the general loglinear model and its logit version.

Davd Knoke (Ph.D., University of Michigan 1972) coauthored Network Analysis (1982) and has published fifteen books and more than a hundred articles and book chapters, primarily on organizations, networks, politics, and social statistics. He was principal co-investigator on several National Science Foundation-funded projects on voluntary associations, lobbying organizations in national policy domains, and organizational surveys of diverse establishments. A current project on the Global Information Sector examines strategic alliance network evolution among international corporations. At Minnesota, he teaches a graduate network analysis seminar that attracts students from diverse disciplines.