It is increasingly important to accurately and comprehensively estimate the effects of
particular clinical treatments. Although randomization is the current gold standard …

Propensity score analysis (PSA) is a powerful technique that it balances pretreatment
covariates, making the causal effect inference from observational data as reliable as …

Propensity score matching has been used with increasing frequency in the analyses of non-
prespecified subgroups of randomized clinical trials, and in retrospective analyses of clinical …

Propensity score matching (PSM) has been widely used to reduce confounding biases in
observational studies. Its properties for statistical inference have also been investigated and …

Propensity score matching is a method to reduce bias in non-randomized and observational
studies. Propensity score matching is mainly applied to two treatment groups rather than …

I first wish to thank Dr Austin for an important paper on the use of propensity score methods
in practice. It follows a series of papers by Dr Austin highlighting issues that applied …

The use of propensity score methods to adjust for selection bias in observational studies has
become increasingly popular in public health and medical research. A substantial portion of …

In order to derive unbiased inference from observational data, matching methods are often
applied to produce balanced treatment and control groups in terms of all background …

Background Propensity score matching is a statistical method that is often used to make
inferences on the treatment effects in observational studies. In recent years, there has been …

The propensity score plays a central role in a variety of causal inference settings. In
particular, matching and weighting methods based on the estimated propensity score have …