Advanced Statistics in Criminology and Criminal Justice
AvDavid Weisburd,David B. Wilson
1 273 kr
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Beskrivning
Produktinformation
- Utgivningsdatum:2021-10-22
- Mått:178 x 254 x 39 mm
- Vikt:1 206 g
- Format:Inbunden
- Språk:Engelska
- Antal sidor:550
- Upplaga:5
- Förlag:Springer Nature Switzerland AG
- ISBN:9783030677374
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Mer om författaren
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.
Innehållsförteckning
- 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.
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