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How can societies effectively reduce crime without exacerbating adversarial relationships between the police and citizens? In recent decades, perhaps the most celebrated innovation in police reform has been the introduction of community policing, where citizens are involved in building channels of dialogue and improving police-citizen collaboration. Despite the widespread adoption of community policing in the United States and increasingly in the developing world, there is still limited credible evidence about whether it realistically increases trust in the police or reduces crime. Through simultaneously coordinated field experiments in a diversity of political contexts, this book presents the outcome of a major research initiative into the efficacy of community policing. Scholars from around the world uncover whether, and under what conditions, this highly influential strategy for tackling crime and insecurity is effective. With its highly innovative approach to cumulative learning, this project represents a new frontier in the study of police reform.
A central problem in clinical psychology is how to draw statistical inferences about the causal effects of treatments (i.e., interventions) from randomized and nonrandomized data. For example, does exposure to childhood trauma really impair cognitive functioning in adults, or does a new medication for treating a psychological condition reduce the occurrence of negative physical health outcomes relative to existing treatments? This chapter describes a general approach to the estimation of such causal effects based on the Rubin Causal Model (RCM). Under this framework, causal effects are defined in terms of potential outcomes and inferences are based on a probabilistic assignment mechanism, which mathematically describes how treatments are given to units. Frequentist and model-based forms of statistical inference for causal effects in randomized experiments and observational studies are presented, and the application of this approach to a number of data collection designs and associated problems commonly encountered in clinical research is discussed.
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