Bøger af 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 book uses life-course longitudinal data collected from a national probability sample of respondents over a span of nearly three decades to examine the impact of multiple forms of exposure to violence in adolescence on a broad range of outcomes in adulthood. The forms of adolescent exposure to violence include general violence victimization, parental physical abuse, witnessing parental violence, and exposure to neighborhood violence. The adult outcomes include adult educational attainment, employment, marital status, income and wealth, mental health, life satisfaction, illicit and problem substance use, general violence victimization and perpetration, intimate partner violence victimization and perpetration, and arrest. The results demonstrate the complex pattern of how the different forms of exposure to violence in adolescence have varying effects on different types of adult outcomes, and matter differently for females and males. Based on these results, implications for theory, policy, and future research are considered.

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.