Matched Sampling for Causal Effects

By Angie Wade. 2008

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Citations in the corpus

Interventions over Predictions: Reframing the Ethical Debate for Actuarial Risk Assessment (2017, methodology): “Causal inference in cases where it is not possible to do an RCT is usually derived from applying the same concepts to observational data, with donor pooling and other matching methods to fill the counter-factual values for each unit based on identifying similar units receiving the two different inte”
The Econometrics of Randomized Experiments (2016, methodology): “We also draw on the literature on causal inference, both in experimental and observational settings, Rosenbaum (1995, 2002, 2009), Rubin (2006), Cox (1992), Morgan and Winship (2007), Morton Williams (2010) and Lee (2005), and Imbens and Rubin (2015).”
Automated versus Do-It-Yourself Methods for Causal Inference: Lessons Learned from a Data Analysis Competition (2017, methodology): “The propensity score is also an important component of the Targeted Maximum Likelihood Estimation (TMLE) (van der Laan and Robins, 2003; van der Laan and Rubin, 2006) approach used in several of the submitted methods.”
Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching Package for R (2008, unknown): “Matching has become an increasingly popular method of causal inference in many fields including statistics (Rubin 2006; Rosenbaum 2002), medicine (Christakis and Iwashyna 2003; Rubin 1997), economics (Abadie and Imbens 2006; Dehejia and Wahba 2002, 1999), political science (Bowers and Hansen 2005;…”
An Introduction to the Augmented Inverse Propensity Weighted Estimator (2010, background): “See Rubin (2006) for a book-length treatment on matching or Diamond and Sekhon (2005) and Ho et al. (2007) for recent influential papers on matching in political science.”
Examining the influence of service additions on manufacturing firms' bankruptcy likelihood (2017, methodology): “While we matched firms by product portfolio, we also employed statistical control variables directly in the model (Rubin, 2006; Sheppard, 1994) to account for other potentially confounding factors (further discussion follows).”
Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index (2016, methodology): “Although matching estimators are generally not efficient in settings with unconfoundedness (Rubin, 2006; Abadie and Imbens, 2006, 2016), they have a lot of intuitive appeal, and it is instructive to see how a matching strategy could be implemented in this case.”
On the Importance of Reliable Covariate Measurement in Selection Bias Adjustments Using Propensity Scores (2011, methodology): “…of the ATE to measurement errors in covariates (Lunceford & Davidian, 2004; Morgan & Winship, 2007; Rosenbaum, 2002; Rosenbaum & Rubin, 1983, 1984; Rubin, 2006): (a) stratification based on PS quintiles; (b) linear regression including PS logits using Yi ¼ b0 þ tZi þ X0i þ L0i þ ei; where Li is a…”
Auditing Search Engines for Differential Satisfaction Across Demographics (2017, methodology): “We drew on well-established ideas from the causal inference literature to develop a matching method similar to those used in medicine and the social sciences [36].”
Robust Text Classification in the Presence of Confounding Bias (2016, background): “Matching is commonly used to estimate causal effects from observational studies (Rosenbaum and Rubin 1983; Dehejia and Wahba 2002; Rubin 2006).”
Mobile Ad Effectiveness: Hyper-Contextual Targeting with Crowdedness (2016, background): “Then, the pseudo-treatment is exogenous and confounds are randomized away, so that the effects on mobile ad purchases are attributed to crowdedness (Rosenbaum and Rubin 1983, Rubin 2006).”
An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies (2011, background): “The reader is referred to the following books for a more indepth discussion (Guo & Fraser, 2009; Morgan & Winship, 2007; Rosenbaum, 2002, 2010; Rubin, 2006).”
What mediation analysis can (not) do (2011, methodology): “With regard to long-term consequences of early attachment styles, Simpson, Collins, Tran, and Haydon (2007) conclude “.”