2003
Efficient Bayesian Sample Size Calculation for Designing a Clinical Trial with Multi‐Cluster Outcome Data
Zou K, Resnic F, Gogate A, Ondategui‐Parra S, Ohno‐Machado L. Efficient Bayesian Sample Size Calculation for Designing a Clinical Trial with Multi‐Cluster Outcome Data. Biometrical Journal 2003, 45: 826-836. DOI: 10.1002/bimj.200390052.Peer-Reviewed Original ResearchBayesian methodsSample size calculation methodBeta prior distributionBeta-binomial modelBayesian beta-binomial modelBayesian sample size calculationsPrior distributionSample size calculationNecessary sample sizePosterior intervalsHierarchical data structureMain outcome eventPercutaneous coronary interventionHealth care utilizationLength criterionSize calculationCoronary interventionCare utilizationMajor complicationsClinical trialsOutcome eventsOutcome dataOutcome studiesCalculation methodHealth providers
2000
Major complications after angioplasty in patients with chronic renal failure: a comparison of predictive models.
Lacson R, Ohno-Machado L. Major complications after angioplasty in patients with chronic renal failure: a comparison of predictive models. AMIA Annual Symposium Proceedings 2000, 457-61. PMID: 11079925, PMCID: PMC2243840.Peer-Reviewed Original ResearchConceptsPercutaneous transluminal coronary angioplastyEnd-stage renal diseaseChronic renal failureMajor complicationsRenal failureCongestive heart failurePatient risk factorsTransluminal coronary angioplastyLogistic regression modelsCoronary angioplastyHeart failureRenal diseasePoor outcomeMyocardial infarctionRisk factorsPrior historyPresence of shockComplicationsLogistic regressionPatientsDiscriminatory abilityDemographic characteristicsAngioplastyRegression modelsStandard logistic regression model