Bücher von Scott Menard

The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.

This is a study of successful youth development in poor, disadvantaged neighborhoods in Denver and Chicago - a study of how children living in the worst neighborhoods develop or fail to develop the values, competencies and commitments that lead to a productive, healthy responsible adult life. While there is a strong focus on neighborhood effects, the study employs a multicontextual model examining both the direct effects of the neighborhood ecology, social organization and contexts embedded in the neighborhood. The unique and combined influence of the neighborhood, family, school, peer group and individual attributes on developmental success is estimated. The view that growing up in a poor, disadvantaged neighborhood condemns one to a life of repeated failure and personal pathology is revealed as a myth, as most youth in these neighborhoods are completing the developmental tasks of adolescence successfully.

Multiple Problem Youth addresses the complex connections among drug abuse, delinquency, and mental health problems as they apply to adolescents and young adults.

Logistic Regression is designed for readers who have a background in statistics at least up to multiple linear regression, who want to analyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally.

The focus in this Second Edition is on logistic regression models for individual level (but aggregate or grouped) data. Multiple cases for each possible combination of values of the predictors are considered in detail and examples using SAS and SPSS included. New to this edition:┬╖ More detailed consideration of grouped as opposed to casewise data throughout the book┬╖ Updated discussion of the properties and appropriate use of goodness of fit measures, R2 analogues, and indices of predictive efficiency┬╖ Discussion of the misuse of odds ratios to represent risk ratios, and of overdispersion and underdispersion for grouped data┬╖ Updated coverage of unordered and ordered polytomous logistic regression models.

Written in nontechnical language, this popular and practical volume has been completely updated to bring readers the latest advice on major issues involved in longitudinal research. It covers: research design strategies; methods of data collection; how longitudinal and cross-sectional research compares in terms of consistency and accuracy of results.