Suchergebnisse

Meta-analysis was designed to synthesize empirical relationships across studies, such as the effects of a specific crime prevention intervention on criminal offending behavior. Meta-analysis focuses on the size & direction of effects across studies, examining the consistency of effects & the relationship between study features & observed effects. The findings from meta-analysis not only reveal robust empirical relationships but also identify existing weaknesses in the knowledge base. Furthermore, meta-analytic results can easily be translated into summary statistics useful for informing public policy regarding effective crime prevention efforts. 1 Figure, 1 Appendix, 23 References. [Copyright 2001 Sage Publications, Inc.]

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.

Introduction: Statistics as a Research Tool -- Measurement: the Basic Building Block of Research -- Representing and Displaying Data -- Describing the Typical Case: Measures of Central Tendency -- How Typical is the Typical Case?: Measuring Dispersion -- The Logic of Statistical Inference: Making Statements About Populations from Sample Statistics -- Defining the Observed Significance Level of a Test: A simple Example Using the Binomial Distribution -- Steps in a Statistical Test: Using the Binomial Distribution to Make Decisions About Hypotheses -- Chi-Square: A Test Commonly Used for Nominal-Level Measures -- The Normal Distribution and Its Application to Tests of Statistical Significance -- Comparing Means and Proportions in Two Samples -- Comparing Means Among More than Two Samples: Analysis of Variance -- Measures of Association for Nominal and Ordinal Variables -- Measuring Association for Interval-Level Data: Pearson's Correlation Coefficient -- An Introduction to Bivariate Regression.

Many respondents to opinion surveys say that the citizen's race influences how police officers treat the public, yet recent expert social‐science panels have declared that research findings are too contradictory to form a conclusion on whether American police are biased against racial minorities. We perform a meta‐analysis of quantitative research that estimates the effect of race on the police decision to arrest. Screening nearly 4,500 potential sources, we analyze the results based on 27 independent data sets that generated 40 research reports (both published and unpublished) that permitted an estimate of the effect size of the suspect's race on the probability of arrest. The meta‐analysis shows with strong consistency that minority suspects are more likely to be arrested than White suspects. Depending on the method of estimation, the effect size of race varied between 1.32 and 1.52. Converting the race effect size to probabilities shows that compared with the average probability in these studies of a White being arrested (.20), the average probability for a non‐White was calculated at .26. The significant race effect persists when taking into account the studies' variations in research methods and the nature of explanatory models used in the studies. Implications for future research are presented.

A systematic review incorporating meta-analytic techniques of correctional boot camps studies was conducted. An intensive search identified 771 documents of which 144 were deemed potential relevant, located, & evaluated for eligibility. In 37 documents, 29 studies were judged eligible for inclusion in the systematic review. The 29 studies resulted in 44 samples providing the primary unit of analysis. Quasi-experimental & experimental studies evaluated a residential program with a militaristic environment & compared the recidivism of participants to a comparison group receiving another correctional sanction. In 9 studies, boot camp participants had lower recidivism than did comparison groups; in 58, comparison groups had lower recidivism; & in the remaining studies, no significant differences were found. A meta-analysis found no overall significant differences in recidivism between boot camp participants & comparison samples. Further analyses indicated the results cannot be explained by differences in study methodology, offender characteristics, or boot camp program components. 4 Tables, 1 Figure, 1 Appendix, 51 References. [Copyright 2001 Sage Publications, Inc.]