Propensity Score Methods

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Overview of Propensity Score Methods

The propensity score methods are widely used to adjust confounding effects in observational studies when comparing treatment effects. The propensity score is defined as the probability of treatment assignment conditioning on some observed baseline characteristics and it provides a balanced score for the treatment conditions as conditioning on the propensity score, the treatment groups are compa...

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Comparing Weighting Methods in Propensity Score Analysis

The propensity score method is frequently used to deal with bias from standard regression in observational studies. The propensity score method involves calculating the conditional probability (propensity) of being in the treated group (of the exposure) given a set of covariates, weighting (or sampling) the data based on these propensity scores, and then analyzing the outcome using the weighted...

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Head 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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An Application of Non-response Bias Reduction Using Propensity Score Methods

‎Normal distribution is widely used in many applications‎. ‎The problem of testing whether observations come from a normal distribution has been studied extensively by many researchers‎. ‎Our main goal in this article is to present a simple test procedure for testing multivariate ‎normality‎‎.

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An Application of Non-response Bias Reduction Using Propensity Score Methods

‎In many statistical studies some units do not respond to a number or all of the questions‎. ‎This situation causes a problem called non-response‎. ‎Bias and variance inflation are two important consequences of non-response in surveys‎. ‎Although increasing the sample size can prevented variance inflation‎, ‎but cannot necessary adjust for the non-response bias‎. ‎Therefore a number of methods ...

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ژورنال

عنوان ژورنال: Anesthesia & Analgesia

سال: 2018

ISSN: 0003-2999

DOI: 10.1213/ane.0000000000002920