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Advanced Statistics in Criminology and Criminal Justice - David Weisburd, David B. Wilson, Alese Wooditch, Chester Britt

Advanced Statistics in Criminology and Criminal Justice

Buch | Hardcover
IX, 550 Seiten
2021 | 5th ed. 2022
Springer International Publishing (Verlag)
978-3-030-67737-4 (ISBN)
CHF 164,75 inkl. MwSt
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This book provides the student, researcher or practitioner with the tools to understand many of the most commonly used advanced statistical analysis tools in criminology and criminal justice, and also to apply them to research problems.  

The volume is structured around two main topics, giving the user flexibility to find what they need quickly. The first is "the general linear model" which is the main analytic approach used to understand what influences outcomes in crime and justice.  It presents a series of approaches from OLS multivariate regression, through logistic regression and multi-nomial regression, hierarchical regression, to count regression. The volume also examines alternative methods for estimating unbiased outcomes that are becoming more common in criminology and criminal justice, including analyses of randomized experiments and propensity score matching. It also examines the problem of statistical power, and how it can be used to better designstudies. Finally, it discusses meta analysis, which is used to summarize studies; and geographic statistical analysis, which allows us to take into account the ways in which geographies may influence our statistical conclusions.


lt;p>David Weisburd is a leading researcher and scholar in criminology and criminal justice. He is Distinguished Professor of Criminology, Law and Society at George Mason University in Virginia and Walter E. Meyer Professor of Law and Criminal Justice at the Hebrew University of Jerusalem. Professor Weisburd has received many awards and prizes for his contributions to criminology and criminal justice including the Stockholm Prize in Criminology and the Sutherland and Vollmer Awards from the American Society of Criminology. 

Chester Britt was a leading researcher and scholar in the field of criminology. During his career, he taught at a number of universities and led departments at Northeastern University, Arizona State University, and the University of Iowa. His research addressed theories of criminal behavior and victimization, demography of crime and criminal careers, criminal justice decision-making, and quantitative research methods.

David Wilson is a Professor in the Criminology, Law and Society Department at George Mason University in Virginia. He is a leading statistician in the field of criminology and was the recipient of the Mosteller Award from the Campbell Collaboration for his contributions to the science of systematic review and meta-analysis.

 Alese Wooditch is an Assistant Professor of Criminal Justice at Temple University. She received her PhD from George Mason University. Professor Wooditch has worked in the area of innovative spatial statistical analyses and has contributed to a number of research programs focusing on crime prevention and Agent-Based Modeling.

 


Chapter 1. Introduction.- Chapter 2. Multiple Regression- Chapter 3. Multiple Regression: Additional Topics.- Chapter 4. Logistic Regression.- Chapter 5. Multivariate Regression With Multiple Category Nominal or Ordinal Measures.- Chapter 6. Count-Based Regression Models.- Chapter 7. Multilevel Regression Models.- Chapter 8. Statistical Power.- Chapter 9. Special Topics: Randomized Experiments.- Chapter 10. Propensity Score Matching.- Chapter 11. Meta-Analysis.- Chapter 12. Spatial Regression.

Erscheinungsdatum
Zusatzinfo IX, 550 p. 68 illus., 10 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 178 x 254 mm
Gewicht 1235 g
Themenwelt Recht / Steuern Strafrecht Kriminologie
Sozialwissenschaften Soziologie Empirische Sozialforschung
Schlagworte Criminal Justice Methodology • evidence-based research • Experimental Criminology • Experimental Design • Multivariate regression • Quantitative Criminology • Research design • Statistical Methods • statistical power
ISBN-10 3-030-67737-0 / 3030677370
ISBN-13 978-3-030-67737-4 / 9783030677374
Zustand Neuware
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