Transparency of high‐dimensional propensity score analyses: Guidance for diagnostics and reporting
Sign Up to like & getrecommendations! Published in 2022 at "Pharmacoepidemiology and Drug Safety"
DOI: 10.1002/pds.5412
Abstract: The high‐dimensional propensity score (HDPS) is a semi‐automated procedure for confounder identification, prioritisation and adjustment in large healthcare databases that requires investigators to specify data dimensions, prioritisation strategy and tuning parameters. In practice, reporting of… read more here.
Keywords: high dimensional; propensity score; dimensional propensity; transparency ... See more keywords
High‐dimensional propensity scores for empirical covariate selection in secondary database studies: Planning, implementation, and reporting
Sign Up to like & getrecommendations! Published in 2022 at "Pharmacoepidemiology and Drug Safety"
DOI: 10.1002/pds.5566
Abstract: Real‐world evidence used for regulatory, payer, and clinical decision‐making requires principled epidemiology in design and analysis, applying methods to minimize confounding given the lack of randomization. One technique to deal with potential confounding is propensity… read more here.
Keywords: covariate selection; propensity; dimensional propensity; high dimensional ... See more keywords
Can We Train Machine Learning Methods to Outperform the High-dimensional Propensity Score Algorithm?
Sign Up to like & getrecommendations! Published in 2018 at "Epidemiology"
DOI: 10.1097/ede.0000000000000787
Abstract: The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing patient’s health status–related information from claims datasets as surrogates or proxies for mismeasured and… read more here.
Keywords: machine learning; high dimensional; propensity score; dimensional propensity ... See more keywords