When conducting research on pain and symptom management interventions for seriously ill individuals, randomized controlled trials are not always feasible or ethical to conduct. Secondary analyses of observational data sets that include information on treatments experienced and outcomes for individuals who did and did not receive a given treatment can be conducted, but confounding because of selection bias can obscure the treatment effect in which one is interested. Propensity scores provide a way to adjust for observable characteristics that differ between treatment and comparison groups. This article provides conceptual guidance in addition to an empirical example to illustrate two areas of propensity score analysis that often lead to confusion in practice: covariate selection and interpretation of resultant treatment effects.
%0 Journal Article
%1 Garrido2014a
%A Garrido, Melissa M
%D 2014
%J Journal of pain and symptom management
%K DataInterpretation Humans OutcomeAssessment(HealthCare) OutcomeAssessment(HealthCare):methods Pain Pain:diagnosis Pain:epidemiology PainManagement PainManagement:statistics&numericaldata PainMeasurement PainMeasurement:methods Prevalence PropensityScore ReproducibilityofResults RiskAssessment SensitivityandSpecificity Statistical SymptomAssessment SymptomAssessment:methods RCT
%N 4
%P 711-8
%R 10.1016/j.jpainsymman.2014.05.014
%T Propensity scores: a practical method for assessing treatment effects in pain and symptom management research.
%U http://www.ncbi.nlm.nih.gov/pubmed/24937162
%V 48
%X When conducting research on pain and symptom management interventions for seriously ill individuals, randomized controlled trials are not always feasible or ethical to conduct. Secondary analyses of observational data sets that include information on treatments experienced and outcomes for individuals who did and did not receive a given treatment can be conducted, but confounding because of selection bias can obscure the treatment effect in which one is interested. Propensity scores provide a way to adjust for observable characteristics that differ between treatment and comparison groups. This article provides conceptual guidance in addition to an empirical example to illustrate two areas of propensity score analysis that often lead to confusion in practice: covariate selection and interpretation of resultant treatment effects.
@article{Garrido2014a,
abstract = {When conducting research on pain and symptom management interventions for seriously ill individuals, randomized controlled trials are not always feasible or ethical to conduct. Secondary analyses of observational data sets that include information on treatments experienced and outcomes for individuals who did and did not receive a given treatment can be conducted, but confounding because of selection bias can obscure the treatment effect in which one is interested. Propensity scores provide a way to adjust for observable characteristics that differ between treatment and comparison groups. This article provides conceptual guidance in addition to an empirical example to illustrate two areas of propensity score analysis that often lead to confusion in practice: covariate selection and interpretation of resultant treatment effects.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Garrido, Melissa M},
biburl = {https://www.bibsonomy.org/bibtex/222e8165c5b208939bfb9d21ef7e5d387/jepcastel},
doi = {10.1016/j.jpainsymman.2014.05.014},
interhash = {56d87e918aa5565d3665ec6af1aceca9},
intrahash = {22e8165c5b208939bfb9d21ef7e5d387},
issn = {1873-6513},
journal = {Journal of pain and symptom management},
keywords = {DataInterpretation Humans OutcomeAssessment(HealthCare) OutcomeAssessment(HealthCare):methods Pain Pain:diagnosis Pain:epidemiology PainManagement PainManagement:statistics&numericaldata PainMeasurement PainMeasurement:methods Prevalence PropensityScore ReproducibilityofResults RiskAssessment SensitivityandSpecificity Statistical SymptomAssessment SymptomAssessment:methods RCT},
month = {10},
note = {Propensity score; Introductori; Dolor},
number = 4,
pages = {711-8},
pmid = {24937162},
timestamp = {2023-05-04T09:00:45.000+0200},
title = {Propensity scores: a practical method for assessing treatment effects in pain and symptom management research.},
url = {http://www.ncbi.nlm.nih.gov/pubmed/24937162},
volume = 48,
year = 2014
}