Improving Generalizations From Experiments Using Propensity Score Subclassification

By Elizabeth Tipton. 2013

207 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/52495d556077d52007b714d567fd39984bcac00e

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In Statistics and Probability

Citations in the corpus

Generalizing causal inferences from randomized trials: counterfactual and graphical identification (2019, background): “Yet, this condition (or close variants) has been invoked in prior work [2–8, 45, 46].”
From Local to Global: External Validity in a Fertility Natural Experiment (2015, unknown): “This follows recent work by Hotz, Imbens, and Mortimer (2005), Stuart et al. (2011), Hartman et al. (2015), and Tipton (2013), all of whom used the potential outcomes framework to characterize conditions necessary for extrapolation from a reference population for which experiments are available to…”
Generalizing from unrepresentative experiments: a stratified propensity score approach (2014, methodology): “Tipton (2013) has studied analytically the bias that may be induced by such mismatches in distribution shape and offered approximate estimates of the relative bias reduction and variance inflation of the PATE estimate derived from the stratified estimator compared with the standard estimator.”
Worth Weighting? How to Think About and Use Weights in Survey Experiments (2017, background): “Relatedly, O’Muircheartaigh and Hedges (2014) and Tipton (2013) propose poststratified estimators, stratifying on these estimated weights.”
Conformal inference of counterfactuals and individual treatment effects (2020, background): “Inference on ATE and CATE in this setting has been a subject of much recent research, and is known under the name of generalizability, or transportability, or external validity (e.g. Pearl & Bareinboim, 2014; Tipton, 2013).”
How Generalizable Is Your Experiment? An Index for Comparing Experimental Samples and Populations (2014, methodology): “Tipton (2013) refers to this problem as a coverage error, akin to the type of error that arises in survey sampling when the target population and population frame do not align exactly (see Groves, Fowler, Couper, Lepkowski, & Singer, 2009).”