Propensity Score Analysis: Statistical Methods and Applications (Advanced Quantitative Techniques in the Social Sciences) [ハードカバー]

Propensity Score Matching provides readers with a systematic review of the origins, history, and statistical foundations of PSM and illustrates how to use PSM methods for solving evaluation problems. With a strong focus on practical applications, the authors explore various types of data and evaluation problems, strategies for using the methods, and the limitations of PSM. Unlike the existing textbooks on program evaluation, Guo and Fraser’s Propensity Score Matching delves into statistical concepts, formulas, and models underlying the application of PSM.

(20110706)

Mark W. Fraser, Ph.D., holds the John A. Tate Distinguished Professorship for Children in Need at the School of Social Work, University of North Carolina at Chapel Hill. He has written numerous chapters and articles on risk and resilience, child behavior, child and family services, and research methods. With colleagues, he is the co-author or editor of eight books. These include Families in Crisis, a study of intensive family-centered services, and Evaluating Family-Based Services, a text on methods for family research. In Risk and Resilience in Childhood, he and his colleagues describe resilience-based perspectives for child maltreatment, school dropout, substance abuse, violence, unwanted pregnancy, and other social problems. In Making Choices, Dr. Fraser and his co-authors outline a program to help children build enduring social relationships with peers and adults. In The Context of Youth Violence, he explores violence from the perspective of resilience, risk, and protection, and in Intervention with Children and Adolescents, Fraser and his colleagues review advances in intervention knowledge for social and health problems. His award-winning text, Social Policy for Children and Families, reviews the bases for public policy in child welfare, juvenile justice, mental health, developmental disabilities, and health. His most recent book, Intervention Research: Developing Social Programs, describes five steps in the design and development of evidence-based programs.


Shenyang Guo, Ph.D., is a Professor at UNC. He has a MA in economics from Fudan University and a Ph.D. in Sociology from the University of Michigan. He has done post-doctoral work at Brown University and held research associate or faculty appointments at the University of Michigan, Case Western Reserve University, the University of Tennessee, and the University of North Carolina. He is the author of numerous research reports in child welfare, child mental health services, welfare, and health care. He has expertise in applying advanced statistical models to solving social welfare problems and has taught graduate courses that address event history analysis, hierarchical linear modeling, growth curve modeling, and program evaluation. He has given many invited workshops on statistical methods-including event history analysis and propensity score matching-to NIH Summer Institute, Children’s Bureau, and the Society of Social Work and Research conferences. He is the Director of Applied Statistical Working Group at UNC. He leads the data analysis planning for the National Survey of Child and Adolescent Well-Being (NSCAW) longitudinal analysis and has developed analytic strategies that address issues of weighting, clustering, growth modeling, and propensity score analysis. He is also directing the analysis of data from the Making Choices Project, a NIDA funded prevention trial. He has published many articles that include methodological works on the analysis of longitudinal data, multivariate failure time data, program evaluation, and multi-level modeling. He is on the editorial board of Social Service Review and a frequent guest reviewer for journals seeking a critique of advanced methodological analyses.