Chapter 5 moves from theory into evidence and discusses how empirical economists think about causality. First, the chapter covers common issues that make it difficult to have confidence in causal claims based on associational evidence alone. Then, experimental evidence is discussed: how to run an experiment, common pitfalls that can undermine confidence in experimental evidence, and what can be done to avoid them. Next, major experimental studies on the impact of health insurance are described. Finally, the chapter discusses the concept of quasi-experimental evidence and how it fits into economics. The end of chapter supplement discusses ethics in research with human subjects and the role of institutional review boards.

Randomized experiments, quasi-experiments and systematic reviews are critical for developing the evidence for evidence-based policing. In this paper, we explore the role of experiments in contributing to the evidence base in policing. Drawing on the Global Policing Database (GPD) corpus of 3,487 high quality evaluation studies in policing, including 431 randomized controlled trials, we describe the breadth and depth of the evidence base in policing. We find that randomized controlled trials form only about 12 percent of the total evidence based in policing, yet this small number of trials has had enormous policy influence over the last fifty years. We also find that most of the evidence in policing is around frontline policing practices and about half of the RCTs in the world come from the US: a greater proportion of RCTs coming from outside of the US than previously reported. We conclude that the breadth of people and places generating high quality evidence will help generalize policing policies and practices beyond the US and is likely to have a snowball effect in fostering the next generation of experimentalists in policing.

In this chapter, we discuss the logic and practice of quasi-experimentation. Specifically, we describe four quasi-experimental designs – one-group pretest–posttest designs, non-equivalent group designs, regression discontinuity designs, and interrupted time-series designs – and their statistical analyses in detail. Both simple quasi-experimental designs and embellishments of these simple designs are presented. Potential threats to internal validity are illustrated along with means of addressing their potentially biasing effects so that these effects can be minimized. In contrast to quasi-experiments, randomized experiments are often thought to be the gold standard when estimating the effects of treatment interventions. However, circumstances frequently arise where quasi-experiments can usefully supplement randomized experiments or when quasi-experiments can fruitfully be used in place of randomized experiments. Researchers need to appreciate the relative strengths and weaknesses of the various quasi-experiments so they can choose among pre-specified designs or craft their own unique quasi-experiments.

Psychological research is often organized into three broad categories: true experiments, quasi-experiments, and nonexperiments. Evolutionary psychology is no exception to this. In this chapter, we define and describe these categories, and discuss various evolutionary psychological studies (and their results) within these categories. The benefits and limitations of these designs are also discussed. Evolutionary psychologists have employed a wide array of true experiments, quasi-experiments, and nonexperiments to examine sexual behaviors. These methods range from simple self-reports (both quantitative and qualitative) and validated scales to naturalistic observations, complex manipulations of participants’ environments, longitudinal studies, meta-analyses, and creative dependent measures of perception, preferences, and behavior. Journals that may serve as publication outlets for evolutionary perspectives on sexual psychology are also mentioned.