High-dimensional propensity score adjustment in studies of treatment effects using health care claims data
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Does design matter? Systematic evaluation of the impact of analytical choices on effect estimates in observational studiesEvaluating the impact of database heterogeneity on observational study resultsComparative safety of antidepressant agents for children and adolescents regarding suicidal actsClopidogrel and proton pump inhibitors--where do we stand in 2012?Applications of propensity score methods in observational comparative effectiveness and safety research: where have we come and where should we go?Measuring frailty using claims data for pharmacoepidemiologic studies of mortality in older adults: evidence and recommendationsMaximum likelihood, profile likelihood, and penalized likelihood: a primerGoals in Nutrition Science 2015-2020Novel data-mining methodologies for adverse drug event discovery and analysisPharmacovigilance Using Clinical NotesModel feedback in Bayesian propensity score estimationEmpirical assessment of methods for risk identification in healthcare data: results from the experiments of the Observational Medical Outcomes Partnership.Active safety monitoring of newly marketed medications in a distributed data network: application of a semi-automated monitoring systemMining high-dimensional administrative claims data to predict early hospital readmissionsSignal detection and monitoring based on longitudinal healthcare dataDetecting and correcting the bias of unmeasured factors using perturbation analysis: a data-mining approach.A modular, prospective, semi-automated drug safety monitoring system for use in a distributed data environment.Estimating causal effects in observational studies using Electronic Health Data: Challenges and (some) solutionsEstimation of biomarker distributions using laboratory data collected during routine delivery of medical care.Methodological considerations in assessing the effectiveness of antidepressant medication continuation during pregnancy using administrative data.A Method to Combine Signals from Spontaneous Reporting Systems and Observational Healthcare Data to Detect Adverse Drug Reactions.Chances and challenges of using routine data collections for renal health care research.Controlling confounding of treatment effects in administrative data in the presence of time-varying baseline confounders.Improving therapeutic effectiveness and safety through big healthcare data.Dimension reduction and shrinkage methods for high dimensional disease risk scores in historical data.P-values and decision-making: discussion of 'Limitations of empirical calibration of p-values using observational data'.Validity of a stroke severity index for administrative claims data research: a retrospective cohort study.A General Framework for Considering Selection Bias in EHR-Based Studies: What Data Are Observed and Why?Commentary: Multiple Causes of Death: The Importance of Substantive Knowledge in the Big Data Era.Can purchasing information be used to predict adherence to cardiovascular medications? An analysis of linked retail pharmacy and insurance claims data.Evidence of potential bias in a comparison of β blockers and calcium channel blockers in patients with chronic obstructive pulmonary disease and acute coronary syndrome: results of a multinational study.Variation in the risk of suicide attempts and completed suicides by antidepressant agent in adults: a propensity score-adjusted analysis of 9 years' dataInfluence of healthy candidate bias in assessing clinical effectiveness for implantable cardioverter-defibrillators: cohort study of older patients with heart failureThe use and impact of cancer medicines in routine clinical care: methods and observations in a cohort of elderly AustraliansCardiovascular outcomes and mortality in patients using clopidogrel with proton pump inhibitors after percutaneous coronary intervention or acute coronary syndromeA basic study design for expedited safety signal evaluation based on electronic healthcare data.Propensity score methods for confounding control in nonexperimental researchPropensity scores for confounder adjustment when assessing the effects of medical interventions using nonexperimental study designs.Higher potency statins and the risk of new diabetes: multicentre, observational study of administrative databases.Increasing medication adherence and income assistance access for first-episode psychosis patients.
P2860
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P2860
High-dimensional propensity score adjustment in studies of treatment effects using health care claims data
description
2009 nî lūn-bûn
@nan
2009 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
High-dimensional propensity sc ...... using health care claims data
@ast
High-dimensional propensity sc ...... using health care claims data
@en
type
label
High-dimensional propensity sc ...... using health care claims data
@ast
High-dimensional propensity sc ...... using health care claims data
@en
prefLabel
High-dimensional propensity sc ...... using health care claims data
@ast
High-dimensional propensity sc ...... using health care claims data
@en
P2093
P2860
P1433
P1476
High-dimensional propensity sc ...... using health care claims data
@en
P2093
Helen Mogun
Jeremy A Rassen
Jerry Avorn
M Alan Brookhart
Robert J Glynn
Sebastian Schneeweiss
P2860
P304
P356
10.1097/EDE.0B013E3181A663CC
P577
2009-07-01T00:00:00Z