%0 Journal Article %1 Austin2009 %A Austin, Peter C %A Lee, Douglas S %D 2009 %J Pharmacoepidemiology and drug safety %K Adrenergicbeta-Antagonists Adrenergicbeta-Antagonists:administration&dosa Adrenergicbeta-Antagonists:therapeuticuse Algorithms Bias(Epidemiology) Biometry Biometry:methods ConfoundingFactors(Epidemiology) DataInterpretation HeartFailure HeartFailure:drugtherapy HeartFailure:epidemiology Humans Hydroxymethylglutaryl-CoAReductaseInhibitors Hydroxymethylglutaryl-CoAReductaseInhibitors:th Matched-PairAnalysis Models MyocardialInfarction MyocardialInfarction:drugtherapy MyocardialInfarction:epidemiology Observation PatientSelection Statistical %N 6 %P 469-82 %R 10.1002/pds.1733 %T The concept of the marginally matched subject in propensity-score matched analyses. %U http://dx.doi.org/10.1002/pds.1733 http://www.ncbi.nlm.nih.gov/pubmed/19319923 %V 18 %X Propensity-score matching is increasingly being used to reduce the impact of treatment-selection bias when estimating causal treatment effects using observational data. Matching on the propensity score creates sets of treated and untreated subjects who have a similar distribution of baseline covariates. Propensity-score matching frequently relies upon calipers, such that matched treated and untreated subjects must have propensity scores that lie within a specified caliper distance of each other. We define the 'marginally matched' subject as a subject who would be matched using the specified caliper width, but who would not have been matched had calipers with a narrower width been employed. Using patients hospitalized with an acute myocardial infarction (or heart attack) and with exposure to a statin prescription at discharge, we demonstrate that the inclusion of marginally matched subjects can have both a quantitative and qualitative impact upon the estimated treatment effect. Furthermore, marginally matched treated subjects can differ from marginally matched untreated subjects to a substantially greater degree than the differences between non-marginally matched treated and untreated subjects in the propensity-score matched sample. The concept of the marginally matched subject can be used as a sensitivity analysis to examine the impact of the matching method on the estimates of treatment effectiveness. %@ 1099-1557

@article{Austin2009, abstract = {Propensity-score matching is increasingly being used to reduce the impact of treatment-selection bias when estimating causal treatment effects using observational data. Matching on the propensity score creates sets of treated and untreated subjects who have a similar distribution of baseline covariates. Propensity-score matching frequently relies upon calipers, such that matched treated and untreated subjects must have propensity scores that lie within a specified caliper distance of each other. We define the 'marginally matched' subject as a subject who would be matched using the specified caliper width, but who would not have been matched had calipers with a narrower width been employed. Using patients hospitalized with an acute myocardial infarction (or heart attack) and with exposure to a statin prescription at discharge, we demonstrate that the inclusion of marginally matched subjects can have both a quantitative and qualitative impact upon the estimated treatment effect. Furthermore, marginally matched treated subjects can differ from marginally matched untreated subjects to a substantially greater degree than the differences between non-marginally matched treated and untreated subjects in the propensity-score matched sample. The concept of the marginally matched subject can be used as a sensitivity analysis to examine the impact of the matching method on the estimates of treatment effectiveness.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Austin, Peter C and Lee, Douglas S}, biburl = {https://www.bibsonomy.org/bibtex/2cb0df3b3defc428cfa0bceb161ba46af/jepcastel}, city = {Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada; Department of Health Policy, Management and Evaluation, University of Toronto, Canada; Division of C}, doi = {10.1002/pds.1733}, interhash = {1ba3864800332d46f8bf49be7bf9f337}, intrahash = {cb0df3b3defc428cfa0bceb161ba46af}, isbn = {1099-1557}, issn = {1099-1557}, journal = {Pharmacoepidemiology and drug safety}, keywords = {Adrenergicbeta-Antagonists Adrenergicbeta-Antagonists:administration&dosa Adrenergicbeta-Antagonists:therapeuticuse Algorithms Bias(Epidemiology) Biometry Biometry:methods ConfoundingFactors(Epidemiology) DataInterpretation HeartFailure HeartFailure:drugtherapy HeartFailure:epidemiology Humans Hydroxymethylglutaryl-CoAReductaseInhibitors Hydroxymethylglutaryl-CoAReductaseInhibitors:th Matched-PairAnalysis Models MyocardialInfarction MyocardialInfarction:drugtherapy MyocardialInfarction:epidemiology Observation PatientSelection Statistical}, month = {6}, note = {5173<m:linebreak></m:linebreak>CP: Copyright © 2009 John Wiley &amp; Sons, Ltd.; PN: 1053-8569;<m:linebreak></m:linebreak>Propensity score}, number = 6, pages = {469-82}, pmid = {19319923}, timestamp = {2023-02-03T11:44:35.000+0100}, title = {The concept of the marginally matched subject in propensity-score matched analyses.}, url = {http://dx.doi.org/10.1002/pds.1733 http://www.ncbi.nlm.nih.gov/pubmed/19319923}, volume = 18, year = 2009 }