jepcastel > epidemiologicresearchdesign

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1Propensity scores for confounder adjustment when assessing the effects of medical interventions using nonexperimental study designs.
T. Stürmer, R. Wyss, R. Glynn, und M. Brookhart. Journal of internal medicine, 275 (6): 570-80 (Juni 2014)Propensity score; Introductori.
vor 2 Jahren von @jepcastel
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Pharmacoepidemiology:methods
Comorbidity
Humans
PropensityScore
OutcomeAssessment(HealthCare):methods
EpidemiologicResearchDesign
OutcomeAssessment(HealthCare):standards
OutcomeAssessment(HealthCare)
AgeFactors
OutcomeAssessment(HealthCare):statistics&num
ComparativeEffectivenessResearch:standards
Pharmacoepidemiology
DrugTherapy
Combination
ComparativeEffectivenessResearch
ComparativeEffectivenessResearch:methods
ConfoundingFactors(Epidemiology)
SexFactors
Pharmacoepidemiology:methodsComorbidityHumansPropensityScoreOutcomeAssessment(HealthCare):methodsEpidemiologicResearchDesignOutcomeAssessment(HealthCare):standardsOutcomeAssessment(HealthCare)AgeFactorsOutcomeAssessment(HealthCare):statistics&numComparativeEffectivenessResearch:standardsPharmacoepidemiologyDrugTherapyCombinationComparativeEffectivenessResearchComparativeEffectivenessResearch:methodsConfoundingFactors(Epidemiology)SexFactors
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1What can be learnt from nothing? - A statistical perspective.
O. Gefeller, A. Pfahlberg, und W. Uter. Contact dermatitis, 69 (6): 350-4 (Dezember 2013)Anàlisi de dades; Límits de confiança.
vor 2 Jahren von @jepcastel
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AllergicContact:diagnosis
AllergicContact
AllergicContact:epidemiology
PatchTests
Prevalence
PatchTests:statistics&numericaldata
Humans
ConfidenceIntervals
Statistical
EpidemiologicResearchDesign
Dermatitis
DataInterpretation
AllergicContact:diagnosisAllergicContactAllergicContact:epidemiologyPatchTestsPrevalencePatchTests:statistics&numericaldataHumansConfidenceIntervalsStatisticalEpidemiologicResearchDesignDermatitisDataInterpretation
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1Completion potentials of sufficient component causes.
W. Lee. Epidemiology (Cambridge, Mass.), 23 (3): 446-53 (Mai 2012)7565<m:linebreak></m:linebreak>JID: 9009644; ppublish;<m:linebreak></m:linebreak>Risc atribuïble; Causalitat.
vor 2 Jahren von @jepcastel
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RiskFactors
Case-ControlStudies
OddsRatio
Statistical
Models
EpidemiologicResearchDesign
DataInterpretation
Causality
ProportionalHazardsModels
RiskFactorsCase-ControlStudiesOddsRatioStatisticalModelsEpidemiologicResearchDesignDataInterpretationCausalityProportionalHazardsModels
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1The case-cohort design in outbreak investigations.
O. de Waroux, H. Maguire, und A. Moren. Euro surveillance : bulletin Européen sur les maladies transmissibles = European communicable disease bulletin, 17 (25): 20202 (Januar 2012)6829<m:linebreak></m:linebreak>JID: 100887452; 0 (Vaccines); epublish;<m:linebreak></m:linebreak>Dissenys híbrids.
vor 2 Jahren von @jepcastel
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GastrointestinalDiseases
DiseaseOutbreaks
Case-ControlStudies
Humans
OddsRatio
PopulationSurveillance
Vaccines
GastrointestinalDiseases:epidemiology
Statistical
EpidemiologicResearchDesign
CohortStudies
DataInterpretation
GastrointestinalDiseasesDiseaseOutbreaksCase-ControlStudiesHumansOddsRatioPopulationSurveillanceVaccinesGastrointestinalDiseases:epidemiologyStatisticalEpidemiologicResearchDesignCohortStudiesDataInterpretation
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1Novel metrics for evaluating improvement in discrimination: net reclassification and integrated discrimination improvement for normal variables and nested models.
M. Pencina, R. D'Agostino, und O. Demler. Statistics in medicine, 31 (2): 101-13 (Januar 2012)6488<br/>CI: Copyright (c) 2011; JID: 8215016; aheadofprint;<br/>Models predictius; Proves diagnòstiques.
vor 2 Jahren von @jepcastel
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ROCCurve
RiskAssessment
CardiovascularDiseases:prevention&control
Humans
Male
Statistical
Models
EpidemiologicResearchDesign
RiskAssessment:methods
DiscriminantAnalysis
CardiovascularDiseases
ROCCurveRiskAssessmentCardiovascularDiseases:prevention&controlHumansMaleStatisticalModelsEpidemiologicResearchDesignRiskAssessment:methodsDiscriminantAnalysisCardiovascularDiseases
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1Random allocation in observational data: how small but robust effects could facilitate hypothesis-free causal inference.
G. Smith. Epidemiology (Cambridge, Mass.), 22 (4): 460-3; discussion 467-8 (Juli 2011)6254<m:linebreak></m:linebreak>JID: 9009644; ppublish;.
vor 2 Jahren von @jepcastel
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Humans
FalseNegativeReactions
EpidemiologicResearchDesign
FalsePositiveReactions
HumansFalseNegativeReactionsEpidemiologicResearchDesignFalsePositiveReactions
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1Metabias: a challenge for comparative effectiveness research.
S. Goodman, und K. Dickersin. Annals of internal medicine, 155 (1): 61-2 (Juli 2011)6245<m:linebreak></m:linebreak>Metaanàlisi; Meta-metaanàlisi; Bias; CER.
vor 2 Jahren von @jepcastel
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Meta-AnalysisasTopic
RandomizedControlledTrialsasTopic:standards
RCT
MulticenterStudiesasTopic:standards
Humans
ComparativeEffectivenessResearch
Bias(Epidemiology)
EpidemiologicResearchDesign
MulticenterStudiesasTopic
TreatmentOutcome
Meta-AnalysisasTopicRandomizedControlledTrialsasTopic:standardsRCTMulticenterStudiesasTopic:standardsHumansComparativeEffectivenessResearchBias(Epidemiology)EpidemiologicResearchDesignMulticenterStudiesasTopicTreatmentOutcome
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1Compound treatments, transportability, and the structural causal model: the power and simplicity of causal graphs.
M. Petersen. Epidemiology (Cambridge, Mass.), 22 (3): 378-81 (Mai 2011)6099<m:linebreak></m:linebreak>Editorial; NLM Journal Code: a2t, 9009644;.
vor 2 Jahren von @jepcastel
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EpidemiologicStudies
RCT
PatientSelection
Humans
Male
EpidemiologicResearchDesign
DecisionMaking
SelectionBias
CombinedModalityTherapy
Statistical
Models
SensitivityandSpecificity
Causality
Female
Observation
EpidemiologicStudiesRCTPatientSelectionHumansMaleEpidemiologicResearchDesignDecisionMakingSelectionBiasCombinedModalityTherapyStatisticalModelsSensitivityandSpecificityCausalityFemaleObservation
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1Designs for the combination of group- and individual-level data.
S. Haneuse, und S. Bartell. Epidemiology (Cambridge, Mass.), 22 (3): 382-9 (Mai 2011)6098<m:linebreak></m:linebreak>Review; NLM Journal Code: a2t, 9009644;.
vor 2 Jahren von @jepcastel
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BirthWeight
EthnicGroups
Humans
Male
Infant
EpidemiologicResearchDesign
EthnicGroups:statistics&numericaldata
DataInterpretation
Epidemiologic
NorthCarolina
Newborn
LowBirthWeight
RiskFactors
EffectModifier
Statistical
Models
DataCollection
ConfoundingFactors(Epidemiology)
Bias(Epidemiology)
SexFactors
Female
BirthWeightEthnicGroupsHumansMaleInfantEpidemiologicResearchDesignEthnicGroups:statistics&numericaldataDataInterpretationEpidemiologicNorthCarolinaNewbornLowBirthWeightRiskFactorsEffectModifierStatisticalModelsDataCollectionConfoundingFactors(Epidemiology)Bias(Epidemiology)SexFactorsFemale
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1Implementation of G-computation on a simulated data set: demonstration of a causal inference technique.
J. Snowden, S. Rose, und K. Mortimer. American journal of epidemiology, 173 (7): 731-8 (April 2011)6073<m:linebreak></m:linebreak>JID: 7910653; aheadofprint;.
vor 2 Jahren von @jepcastel
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Humans
Statistical
Models
ConfoundingFactors(Epidemiology)
EpidemiologicResearchDesign
RegressionAnalysis
Causality
ComputerSimulation
HumansStatisticalModelsConfoundingFactors(Epidemiology)EpidemiologicResearchDesignRegressionAnalysisCausalityComputerSimulation
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1Marginal Structural Models: unbiased estimation for longitudinal studies.
E. Moodie, und D. Stephens. International journal of public health, 56 (1): 117-9 (Februar 2011)6250<m:linebreak></m:linebreak>GR: Canadian Institutes of Health Research/Canada; JID: 101304551; 2010/05/07 received; 2010/09/12 accepted; 2010/08/01 revised; 2010/10/08 aheadofprint; ppublish;<m:linebreak></m:linebreak>Propensity score; Marginal structural models; Introductori.
vor 2 Jahren von @jepcastel
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LikelihoodFunctions
LongitudinalStudies:standards
Humans
LongitudinalStudies
Probability
EpidemiologicResearchDesign
DataInterpretation
TimeFactors
LongitudinalStudies:statistics&numericaldata
Statistical
Models
ConfoundingFactors(Epidemiology)
Bias(Epidemiology)
LikelihoodFunctionsLongitudinalStudies:standardsHumansLongitudinalStudiesProbabilityEpidemiologicResearchDesignDataInterpretationTimeFactorsLongitudinalStudies:statistics&numericaldataStatisticalModelsConfoundingFactors(Epidemiology)Bias(Epidemiology)
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1Adjusting for selection effects in epidemiologic studies: why sensitivity analysis is the only "solution".
S. Geneletti, A. Mason, und N. Best. Epidemiology (Cambridge, Mass.), 22 (1): 36-9 (Januar 2011)6260<m:linebreak></m:linebreak>LR: 20110518; JID: 9009644; CON: Epidemiology. 2011 Jan;22(1):27-35. PMID: 21150352; CON: Epidemiology. 2011 Jan;22(1):18-26. PMID: 21150351; CIN: Epidemiology. 2011 May;22(3):446. PMID: 21464660; ppublish;.
vor 2 Jahren von @jepcastel
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Cross-SectionalStudies
Humans
Statistical
Models
EpidemiologicResearchDesign
SensitivityandSpecificity
SelectionBias
Cross-SectionalStudiesHumansStatisticalModelsEpidemiologicResearchDesignSensitivityandSpecificitySelectionBias
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1Web-based questionnaires: the future in epidemiology?
M. van Gelder, R. Bretveld, und N. Roeleveld. American journal of epidemiology, 172 (11): 1292-8 (Dezember 2010)5789<m:linebreak></m:linebreak>JID: 7910653; aheadofprint;.
vor 2 Jahren von @jepcastel
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DataCollection:methods
PostalService:economics
PopulationSurveillance
Questionnaires:economics
Questionnaires
EpidemiologicResearchDesign
Forecasting
PostalService
PostalService:trends
DataCollection:trends
ReproducibilityofResults
PopulationSurveillance:methods
DataCollection:economics
DataCollection
Internet
Internet:economics
Internet:trends
DataCollection:methodsPostalService:economicsPopulationSurveillanceQuestionnaires:economicsQuestionnairesEpidemiologicResearchDesignForecastingPostalServicePostalService:trendsDataCollection:trendsReproducibilityofResultsPopulationSurveillance:methodsDataCollection:economicsDataCollectionInternetInternet:economicsInternet:trends
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1Design of clinical trials.
D. Rollo, S. Machado, und M. Ceschin. Seminars in nuclear medicine, 40 (5): 332-7 (September 2010)5927<m:linebreak></m:linebreak>CI: Copyright 2010; JID: 1264464; 0 (Radiopharmaceuticals); ppublish;<m:linebreak></m:linebreak>Disseny; Tipus d'estudis; RCT.
vor 2 Jahren von @jepcastel
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Radiopharmaceuticals:economics
Radiopharmaceuticals:supply&distribution
ResearchDesign
Radiopharmaceuticals:adverseeffects
Humans
Radiopharmaceuticals:diagnosticuse
EarlyTerminationofClinicalTrials
EpidemiologicResearchDesign
Drug-RelatedSideEffectsandAdverseReactions
DiagnosticImaging
Disclosure
TimeFactors
NuclearMedicine:methods
NuclearMedicine
Bias(Epidemiology)
ClinicalTrialsasTopic
Radiopharmaceuticals
SocialResponsibility
DrugLabeling
ClinicalTrialsasTopic:methods
Radiopharmaceuticals:economicsRadiopharmaceuticals:supply&distributionResearchDesignRadiopharmaceuticals:adverseeffectsHumansRadiopharmaceuticals:diagnosticuseEarlyTerminationofClinicalTrialsEpidemiologicResearchDesignDrug-RelatedSideEffectsandAdverseReactionsDiagnosticImagingDisclosureTimeFactorsNuclearMedicine:methodsNuclearMedicineBias(Epidemiology)ClinicalTrialsasTopicRadiopharmaceuticalsSocialResponsibilityDrugLabelingClinicalTrialsasTopic:methods
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1Comparative effectiveness research: Policy context, methods development and research infrastructure.
S. Tunis, J. Benner, und M. McClellan. Statistics in medicine, 29 (19): 1963-76 (August 2010)5705<m:linebreak></m:linebreak>CP: Copyright © 2010 John Wiley & Sons, Ltd.; PN: 0277-6715;<m:linebreak></m:linebreak>CER.
vor 2 Jahren von @jepcastel
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Evidence-BasedMedicine:standards
ComparativeEffectivenessResearch:organization&
Humans
Evidence-BasedMedicine
CostControl
Benchmarking
EpidemiologicResearchDesign
HealthCare
HealthCare:methods
HealthPolicy
ConsumerParticipation
CostControl:methods
QualityAssurance
ComparativeEffectivenessResearch:standards
HealthCare:standards
Evidence-BasedMedicine:methods
HealthCare:organization&administration
ComparativeEffectivenessResearch
ComparativeEffectivenessResearch:methods
Evidence-BasedMedicine:organization&administra
UnitedStates
Evidence-BasedMedicine:standardsComparativeEffectivenessResearch:organization&HumansEvidence-BasedMedicineCostControlBenchmarkingEpidemiologicResearchDesignHealthCareHealthCare:methodsHealthPolicyConsumerParticipationCostControl:methodsQualityAssuranceComparativeEffectivenessResearch:standardsHealthCare:standardsEvidence-BasedMedicine:methodsHealthCare:organization&administrationComparativeEffectivenessResearchComparativeEffectivenessResearch:methodsEvidence-BasedMedicine:organization&administraUnitedStates
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1Instrumental variable methods in comparative safety and effectiveness research.
M. Brookhart, J. Rassen, und S. Schneeweiss. Pharmacoepidemiology and drug safety, 19 (6): 537-54 (Juni 2010)5676<m:linebreak></m:linebreak>GR: 1 K01 HS018088/HS/AHRQ HHS/United States; GR: 290-2005-0016-I-TO3-WA1/PHS HHS/United States; GR: K25AG027400/AG/NIA NIH HHS/United States; JID: 9208369; NIHMS205457; OID: NLM: NIHMS205457 Available on 06/01/11; OID: NLM: PMC2886161 Available on 06/01/11; ppublish;<m:linebreak></m:linebreak>Variables instrumentals.
vor 2 Jahren von @jepcastel
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Humans
Statistical
Models
ComparativeEffectivenessResearch
ComparativeEffectivenessResearch:methods
ConfoundingFactors(Epidemiology)
EpidemiologicResearchDesign
PharmaceuticalPreparations
PharmaceuticalPreparations:adverseeffects
HumansStatisticalModelsComparativeEffectivenessResearchComparativeEffectivenessResearch:methodsConfoundingFactors(Epidemiology)EpidemiologicResearchDesignPharmaceuticalPreparationsPharmaceuticalPreparations:adverseeffects
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1The Janus face of statistical adjustment: confounders versus colliders.
I. Janszky, A. Ahlbom, und A. Svensson. European journal of epidemiology, 25 (6): 361-3 (Juni 2010)5668<m:linebreak></m:linebreak>JID: 8508062; 2010/03/18 received; 2010/04/22 accepted; 2010/05/07 aheadofprint; ppublish;<m:linebreak></m:linebreak>Mesures d'associació.
vor 2 Jahren von @jepcastel
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Humans
Statistical
ConfoundingFactors(Epidemiology)
Bias(Epidemiology)
EpidemiologicResearchDesign
DataInterpretation
Causality
HumansStatisticalConfoundingFactors(Epidemiology)Bias(Epidemiology)EpidemiologicResearchDesignDataInterpretationCausality
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1Blinded sample size reestimation with count data: methods and applications in multiple sclerosis.
T. Friede, und H. Schmidli. Statistics in medicine, 29 (10): 1145-56 (Mai 2010)5506<m:linebreak></m:linebreak>JID: 8215016; aheadofprint;<m:linebreak></m:linebreak>Sample size; Count data.
vor 2 Jahren von @jepcastel
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PoissonDistribution
Relapsing-Remitting
Humans
Relapsing-Remitting:pathology
PilotProjects
EpidemiologicResearchDesign
Relapsing-Remitting:drugtherapy
DataInterpretation
EndpointDetermination:methods
MultipleSclerosis
TimeFactors
Double-BlindMethod
SampleSize
Single-BlindMethod
Statistical
ClinicalTrialsasTopic
BinomialDistribution
EndpointDetermination
ClinicalTrialsasTopic:methods
PoissonDistributionRelapsing-RemittingHumansRelapsing-Remitting:pathologyPilotProjectsEpidemiologicResearchDesignRelapsing-Remitting:drugtherapyDataInterpretationEndpointDetermination:methodsMultipleSclerosisTimeFactorsDouble-BlindMethodSampleSizeSingle-BlindMethodStatisticalClinicalTrialsasTopicBinomialDistributionEndpointDeterminationClinicalTrialsasTopic:methods
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1The ongoing tyranny of statistical significance testing in biomedical research.
A. Stang, C. Poole, und O. Kuss. European journal of epidemiology, 25 (4): 225-30 (April 2010)5552<m:linebreak></m:linebreak>M3: 10.1007/s10654-010-9440-x;<m:linebreak></m:linebreak>Significació estadística.
vor 2 Jahren von @jepcastel
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Biostatistics
BiomedicalResearch
TimeFactors
BiomedicalResearch:methods
Humans
ConfidenceIntervals
Probability
Statistical
Bias(Epidemiology)
EpidemiologicResearchDesign
DataInterpretation
Biostatistics:methods
BiostatisticsBiomedicalResearchTimeFactorsBiomedicalResearch:methodsHumansConfidenceIntervalsProbabilityStatisticalBias(Epidemiology)EpidemiologicResearchDesignDataInterpretationBiostatistics:methods
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1Overadjustment bias and unnecessary adjustment in epidemiologic studies.
E. Schisterman, S. Cole, und R. Platt. Epidemiology (Cambridge, Mass.), 20 (4): 488-95 (Juli 2009)5214<m:linebreak></m:linebreak>GR: R03-AI 071763/AI/NIAID NIH HHS/United States; JID: 9009644; CIN: Epidemiology. 2009 Jul;20(4):496-9. PMID: 19525686; ppublish;.
vor 2 Jahren von @jepcastel
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Humans
Infant
EpidemiologicResearchDesign
InfantMortality
Newborn
InfantMortality:trends
Smoking
Statistical
Models
Bias(Epidemiology)
PopulationDynamics
Smoking:adverseeffects
Causality
Female
HumansInfantEpidemiologicResearchDesignInfantMortalityNewbornInfantMortality:trendsSmokingStatisticalModelsBias(Epidemiology)PopulationDynamicsSmoking:adverseeffectsCausalityFemale
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1Propensity scores for confounder adjustment when assessing the effects of medical interventions using nonexperimental study designs.

1What can be learnt from nothing? - A statistical perspective.

1Completion potentials of sufficient component causes.

1The case-cohort design in outbreak investigations.

1Novel metrics for evaluating improvement in discrimination: net reclassification and integrated discrimination improvement for normal variables and nested models.

1Random allocation in observational data: how small but robust effects could facilitate hypothesis-free causal inference.

1Metabias: a challenge for comparative effectiveness research.

1Compound treatments, transportability, and the structural causal model: the power and simplicity of causal graphs.

1Designs for the combination of group- and individual-level data.

1Implementation of G-computation on a simulated data set: demonstration of a causal inference technique.

1Marginal Structural Models: unbiased estimation for longitudinal studies.

1Adjusting for selection effects in epidemiologic studies: why sensitivity analysis is the only "solution".

1Web-based questionnaires: the future in epidemiology?

1Design of clinical trials.

1Comparative effectiveness research: Policy context, methods development and research infrastructure.

1Instrumental variable methods in comparative safety and effectiveness research.

1The Janus face of statistical adjustment: confounders versus colliders.

1Blinded sample size reestimation with count data: methods and applications in multiple sclerosis.

1The ongoing tyranny of statistical significance testing in biomedical research.

1Overadjustment bias and unnecessary adjustment in epidemiologic studies.

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