Advanced statistics in criminology and criminal justice / David Weisburd, David B. Wilson, Alese Wooditch, and Chester Britt.
Weisburd, David, author.; Wilson, David B., 1961- author.; Wooditch, Alese, author.; Britt, Chester L., author.
2022
HV7415
Available Online

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Title Advanced statistics in criminology and criminal justice / David Weisburd, David B. Wilson, Alese Wooditch, and Chester Britt.
Author Weisburd, David, author.
Edition Fifth edition.
ISBN 9783030677381 (electronic bk.)
3030677389 (electronic bk.)
9783030677374 (print)
DOI https://doi.org/10.1007/978-3-030-67738-1
Published Cham, Switzerland : Springer, [2022]
Language English
Description 1 online resource (ix, 550 pages) : illustrations (some color)
Other Standard Identifiers 10.1007/978-3-030-67738-1 doi
Call Number HV7415
Dewey Decimal Classification 364.02/1
Summary 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 design studies. 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
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed October 25, 2021).
Added Author Wilson, David B., 1961- author.
Wooditch, Alese, author.
Britt, Chester L., author.
Available in Other Form Print version: 9783030677374
Print version: 9783030677398
Print version: 9783030677404
Linked Resources Online Access
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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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