Comparison of propensity score methods for causal inference : matching, weighting, subclassification, and double propensity score adjustment
نویسندگان
چکیده
منابع مشابه
Uncertain Neighbors: Bayesian Propensity Score Matching for Causal Inference
In this paper we compare the performance of standard nearest-neighbor propensity score matching with that of an analogous Bayesian propensity score matching procedure. We show that the Bayesian approach has several advantages, including that it makes better use of available information, since it makes less arbitrary decisions about which observations to drop and which ones to keep in the matche...
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Propensity score matching (PSM) is a widely used method for performing causal inference with observational data. PSM requires fully specifying the set of confounding variables of treatment and outcome. In the case of relational data, this set may include nonintuitive relational variables, i.e., variables derived from the relational structure of the data. In this work, we provide an automated me...
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In a randomized study, subjects are randomly assigned to either a treated group or a control group. Random assignment ensures that the distribution of the covariates is the same in both groups and that the treatment effect can be estimated by directly comparing the outcomes for the subjects in the two groups. In contrast, subjects in an observational study are not randomly assigned. In order to...
متن کاملHead to head comparison of the propensity score and the high-dimensional propensity score matching methods.
BACKGROUND Comparative performance of the traditional propensity score (PS) and high-dimensional propensity score (hdPS) methods in the adjustment for confounding by indication remains unclear. We aimed to identify which method provided the best adjustment for confounding by indication within the context of the risk of diabetes among patients exposed to moderate versus high potency statins. M...
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This paper considers causal inference and sample selection bias in nonexperimental settings in which (i) few units in the nonexperimental comparison group are comparable to the treatment units, and (ii) selecting a subset of comparison units similar to the treatment units is difficult because units must be compared across a high-dimensional set of pretreatment characteristics. We discuss the us...
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ژورنال
عنوان ژورنال: Journal of Curriculum and Evaluation
سال: 2019
ISSN: 1229-1544
DOI: 10.29221/jce.2019.22.2.269