Handbook of quantitative criminology
著者
書誌事項
Handbook of quantitative criminology
Springer, c2010
大学図書館所蔵 件 / 全3件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references and index
内容説明・目次
内容説明
Quantitative criminology has certainly come a long way since I was ?rst introduced to a largely qualitative criminology some 40 years ago, when I was recruited to lead a task force on science and technology for the President's Commission on Law Enforcement and Administration of Justice. At that time, criminology was a very limited activity, depending almost exclusively on the Uniform Crime Reports (UCR) initiated by the FBI in 1929 for measurement of crime based on victim reports to the police and on police arrests. A ty- cal mode of analysis was simple bivariate correlation. Marvin Wolfgang and colleagues were makingan importantadvancebytrackinglongitudinaldata onarrestsin Philadelphia,an in- vation that was widely appreciated. And the ?eld was very small: I remember attending my ?rst meeting of the American Society of Criminology in about 1968 in an anteroom at New York University; there were about 25-30 people in attendance, mostly sociologists with a few lawyers thrown in. That Society today has over 3,000 members, mostly now drawn from criminology which has established its own clear identity, but augmented by a wide variety of disciplines that include statisticians, economists, demographers, and even a few engineers. This Handbook provides a remarkable testimony to the growth of that ?eld. Following the maxim that "if you can't measure it, you can't understand it," we have seen the early dissatisfaction with the UCR replaced by a wide variety of new approaches to measuring crime victimization and offending.
目次
Introduction
I. Topics in Research Design
1). Experiments - trials
2). Experiments - block/randomized and subgroup
3). Propensity scores
4). Regression discontinuity designs
5) Quantitative and Qualitative Data
6) Statistical power
II) Methods for Overcoming Data Limitations
7) Data reliability and data comparisons
8) Missing data
III) Innovative Descriptive Methods
10) Geographic mapping of crime
11) Visualizing data
12) Trajectories
13) Growth curve models
IV) Estimation Techniques for Theory and Policy
14) Estimating Costs of Crime
15) Estimating treatment effects
16) Meta-analysis
V) Topics in Multiple Regression
17) Instrumental variables
18) Multilevel modeling
19) Logic and related extensions
20) Count models
VI) New Directions in Statistical Analysis
21) Geographic statistical analysis of crime
22) Data mining
23) Time series
24) Network analysis
Conclusion
「Nielsen BookData」 より
