Scholarworks (University of Massachusetts Amherst) · 2020 · 86 citations · 14 references
Public HealthBiostatisticsCausal InferenceClinical EpidemiologyOutcomes ResearchCausal Effect EstimationExperimental EvaluationMatching MethodsPropensity ModelingPropensity Score MethodsSelection BiasBiasesPropensity Score AdjustmentPropensity ScoringSelection Bias AdjustmentSelection Of Comparison Groups
Propensity score weighting is one of the techniques used in controlling for selection biases in non-experimental studies. Propensity scores can be used as weights to account for selection assignment differences between treatment and comparison groups. One of the advantages of this approach is that all the individuals in the study can be used for the outcomes evaluation. In this paper, we demonstrate how to conduct propensity score weighting using R. The purpose is to provide a step-by-step guide to propensity score weighting implementation for practitioners. In addition to strengths, some limitations of propensity score weighting are discussed. Accessed 24,338 times on https://pareonline.net from June 27, 2015 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
14
R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
<b>MatchIt</b>: Nonparametric Preprocessing for Parametric Causal Inference
Daniel E. Ho, Kosuke Imai, Gary King et al. · Journal of Statistical Software · 2011 · 4.4K citations · Full text