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.

In this text, author Scott Menard provides coverage of not only the basic logistic regression model but also advanced topics found in no other logistic regression text. The book keeps mathematical notation to a minimum, making it accessible to those with more limited statistics backgrounds, while including advanced topics of interest to more statistically sophisticated readers. Not dependent on any one software package, the book discusses limitations to existing software packages and ways to overcome them. Key Features Examines the logistic regression model in detailIllustrates concepts with applied examples to help readers understand how concepts are translated into the logistic regression modelHelps readers make decisions about the criteria for evaluating logistic regression models through detailed coverage of how to assess overall models and individual predictors for categorical dependent variablesOffers unique coverage of path analysis with logistic regression that shows readers how to examine both direct and indirect effects using logistic regression analysisApplies logistic regression analysis to longitudinal panel data, helping students understand the issues in measuring change with dichotomous, nominal, and ordinal dependent variablesShows readers how multilevel change models with logistic regression are different from multilevel growth curve models for continuous interval or ratio-scaled dependent variables

Logistic Regression is intended for courses such as Regression and Correlation, Intermediate/Advanced Statistics, and Quantitative Methods taught in departments throughout the behavioral, health, mathematical, and social sciences, including applied mathematics/statistics, biostatistics, criminology/criminal justice, education, political science, public health/epidemiology, psychology, and sociology."

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. Interrelationships in this area exist in a vast variety of ways, further complicated by extraneous factors such as demographics, sex, and time. The authors incorporate these factors and analyze the correlations among substance use, delinquency, and mental health problems, as well as discussing developmental patterns and reviewing theories of deviant behavior.

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.

Longitudinal research is a broad field in which substantial advances have been made over the past decade. Unlike many of the existing books that only address the analysis of information. The Handbook of Longitudinal Research covers design and measurement as well as the data analysis.
Designed for use by a wide-ranging audience, this Handbook not only includes perspective on the methodological and data analysis problems in longitudinal research but it also includes contributors' data sets that enable readers who lack sophisticated statistics skills to move from theories about longitudinal data into practice.
As "the" comprehensive reference, this Handbook has no direct competition as most books in this subject area are more narrowly specialized and are pitched at a high mathematical level.
*Contributors and subject areas are interdisciplinary to reach the broadest possible audience (i.e., psychology, epidemiology, and economics research fields)
*Summary material will be included for less sohisticated readers
*Extensive coverage is provided of traditional advanced topics

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.

Written in non-technical 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; and how longitudinal and cross-sectional research compares in terms of consistency and accuracy of results.

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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.