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We show that propensity score matching (psm), an enormously popular method of preprocessing data for causal inference, often accomplishes the opposite of its. Abstract researchers use propensity score matching (psm) as a data preprocessing step to selectively prune units prior to applying a model to estimate a causal effect. We show that propensity score matching (psm), an enormously popular method of preprocessing data for causal inference, often accomplishes the opposite of its intended goal—thus increasing.
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Propensity score matching (psm) (rosenbaum and rubin 1983) is the most commonly used matching method, possibly even “the most developed and popular strategy for causal analysis in. Propensity score matching in the statistical analysis of observational data, propensity score matching (psm) is a statistical matching technique that attempts to estimate the effect of a. International methods colloquium talk on september 11th, 2015
Gary king (harvard university), why propensity scores should not be used for matching. presentation slides are.
An important final point made is that the results do not necessarily imply problems with alternative approaches which use the propensity score, such as inverse weighting or. Fortunately, since other commonly used matching methods reduce imbalance, model dependence, and bias more effectively than psm, and do not typically suffer from the same paradox, matching.
