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Propensity Score Analysis: Statistical Methods and Applications (Advanced Quantitative Techniques in the Social Sciences)
 
 
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Propensity Score Analysis: Statistical Methods and Applications (Advanced Quantitative Techniques in the Social Sciences) [Hardcover]

Shenyang Y. Guo (Author), Mark W. Fraser (Author)
5.0 out of 5 stars  See all reviews (2 customer reviews)

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Book Description

1412953561 978-1412953566 July 16, 2009 1
Propensity Score Analysis provides readers with a systematic review of the origins, history, and statistical foundations of PSA and illustrates how it can be used for solving evaluation problems. With a strong focus on practical applications, the authors explore various types of data and evaluation problems related to, strategies for employing, and the limitations of PSA. Unlike the existing textbooks on program evaluation, Propensity Score Analysis delves into statistical concepts, formulas, and models underlying the application.
 
Key Features

  • Presents key information on model derivations 
  • Summarizes complex statistical arguments but omits their proofs
  • Links each method found in this book to specific Stata programs and provides empirical examples 
  • Guides readers using two conceptual frameworks: the Neyman-Rubin counterfactual framework and the Heckman econometric model of causality 
  • Contains examples representing real challenges commonly found in social behavioral research 
  • Utilizes data simulation and Monte Carlo studies to illustrate key points 
  • Presents descriptions of new statistical approaches necessary for understanding the four evaluation methods incorporated throughout the text

Intended Audience
 
This text is appropriate for graduate and doctoral students taking Evaluation, Quantitative Methods, Survey Research, and Research Design courses across business, social work, public policy, psychology, sociology, and health/medicine disciplines.


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Propensity Score Analysis: Statistical Methods and Applications (Advanced Quantitative Techniques in the Social Sciences) + Counterfactuals and Causal Inference: Methods and Principles for Social Research (Analytical Methods for Social Research) + Mostly Harmless Econometrics: An Empiricist's Companion
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Editorial Reviews

Review

"The approach the authors take in writing this book is very effective for novices and experiences users...This balance between the practical and applied approach is a useful model for researchers to understand the process and interpretation of these analyses...[it] goes a long way in making propensity score analysis techniques more accessible, understandable, and useful to psychologists." (Karl N. Kelley PsycCRITIQUES )

"Guo and Fraser’s book Propensity Score Analysis: Statistical Methods and Applications is the first comprehensive book that discusses and compares different PS techniques from theoretical and practical points of view. One of the book’s strengths is its focus on the application of PS to real data.
[T]his textbook gives a good introduction to PS matching techniques and some alternative approaches for estimating causal treatment effects. With its many examples in Stata, it may be useful for graduate students and applied researchers who have no or limited experience with PS methods but are familiar with basic regression methods and mathematical/statistical notation."
(Peter M. Steiner PSYCHOMETRIKA-VOL. 75, NO. 4, 775–777 )

About the Author

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.

Product Details

  • Hardcover: 392 pages
  • Publisher: Sage Publications, Inc; 1 edition (July 16, 2009)
  • Language: English
  • ISBN-10: 1412953561
  • ISBN-13: 978-1412953566
  • Product Dimensions: 9.1 x 6.1 x 0.9 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Best Sellers Rank: #47,675 in Books (See Top 100 in Books)

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15 of 16 people found the following review helpful:
5.0 out of 5 stars Very comprehensive source on pscore matching and treatment effects, March 1, 2010
This review is from: Propensity Score Analysis: Statistical Methods and Applications (Advanced Quantitative Techniques in the Social Sciences) (Hardcover)
I am a fourth year PhD student at University of Toronto and this textbook has been a very useful source on estimating treatment effects as part of my research.

I think it is particularly good at (1) explaining the differences between Heckman-type selection models and matching models; and at (2) summarizing different matching approaches including propensity score, matching estimators, and non-parametric techniques. Moreover, it provides details on how to perform sensitivity analysis and perform diagnostics for each technique. I liked that each chapter explains briefly the theoretical foundations of every approach and provides detailed guidance using examples on how to run STATA or R code.
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4 of 5 people found the following review helpful:
5.0 out of 5 stars Nice job!, March 8, 2011
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This review is from: Propensity Score Analysis: Statistical Methods and Applications (Advanced Quantitative Techniques in the Social Sciences) (Hardcover)
There are many causal inference books out there, including Rubin's and Rosenbaum's. This one is completely into propensity scoring and is very comprehensive and practical. It includes some latest variations. I would highly recommend it.

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