When second best is good enough: a comparison between a true experiment and a regression discontinuity quasi-experiment
By Richard A. Berk, G. Barnes, Lindsay Ahlman, E. Kurtz. 2010
81 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/666f1b04dfbecd43a55d9ea4dd724479635cd826
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
In Statistics and Probability
Citations in the corpus
- Forecasting Domestic Violence: A Machine Learning Approach to Help Inform Arraignment Decisions (2016, background): “…three different categories of crime committed while on probation or parole to rationalize the intensity of supervision and the kinds of services offered (Berk et al. 2010), and future violence to help judges make post-conviction sentencing decisions (Berk & Bleich 2013, 2014; Berk & Hyatt 2015).”
- Examining Prison Effects on Recidivism: A Regression Discontinuity Approach (2017, unknown): “Specifically, it employs a research design, regression discontinuity (RD), that has the potential to provide high levels of internal validity (see, e.g. Berk, Barnes, Ahlman, & Kurtz, 2010; Dunning, 2012; Murnane & Willett, 2011; Thistlethwaite & Campbell, 1960).”
- Agnostic notes on regression adjustments to experimental data: Reexamining Freedman's critique (2012, background): “For example, Berk et al. (2010) write: “Random assignment does not justify any form of regression with covariates.”
- What You Can and Can’t Properly Do with Regression (2010, background): “2 The many problems with causal modeling are well articulated in a very large literature (e.g., Box 1976; Leamer 1978; 1983; Lieberson 1985; Holland 1986; Rubin 1986; Freedman 1987, 2005; Kish, 1987; de Leeuw 1994; Manski 1995; Pearl 2000; Heckman 2000; Breiman 2001; Berk 2004; Imbens 2009).”
- Statistical Procedures for Forecasting Criminal Behavior (2013, background): “As already noted, in some applications the intent is to work with three crime categories: arrests for violent crimes, arrests for crimes that are not violent, and no arrest at all (Berk et al., 2010).”
- An impact assessment of machine learning risk forecasts on parole board decisions and recidivism (2017, background): “A somewhat surprising oversight is that with few exceptions (Berk et al. 2010b; Holsinger 2013; Miller and Malony 2013; Trochim2001; McCafferty 2015) the debates have unfolded with scant information about how actuarial risks assessments have affected practices and outcomes.”