Featured Publications
The required size of cluster randomized trials of nonpharmaceutical interventions in epidemic settings
Sheen J, Haushofer J, Metcalf C, Kennedy‐Shaffer L. The required size of cluster randomized trials of nonpharmaceutical interventions in epidemic settings. Statistics In Medicine 2022, 41: 2466-2482. PMID: 35257398, PMCID: PMC9111156, DOI: 10.1002/sim.9365.Peer-Reviewed Original ResearchConceptsCluster randomized trialEffectiveness of interventionsSample sizeRandomized trialsPlanning such trialsApproximate sample size formulaeReduce transmissionEffect sizeNonpharmaceutical interventionsInfectious disease outbreaksObservational studyInterventionEpidemic settingsSample size methodsAdequate powerSARS-CoV-2 pandemicSARS-CoV-2 transmissionSample size formulaTested individualsSimulated bankTreatment effectsTrialsCommunity transmissionOutbreak settingsSize formulaNovel methods for the analysis of stepped wedge cluster randomized trials
Kennedy‐Shaffer L, de Gruttola V, Lipsitch M. Novel methods for the analysis of stepped wedge cluster randomized trials. Statistics In Medicine 2019, 39: 815-844. PMID: 31876979, PMCID: PMC7247054, DOI: 10.1002/sim.8451.Peer-Reviewed Original ResearchConceptsSW-CRTsRobust inference proceduresStepped wedge cluster randomized trialParametric model assumptionsModel assumptionsCluster randomized trialNonparametric analysis methodsTheoretical propertiesInference proceduresNonparametric methodsIncorporating covariatesRestrictive assumptionsAssumptionsEffects modelControl approachFeasibility advantagesSynthetic control approachIncreased powerRandomized trialsIntervention clustersMixed effects modelsEstimationTime trendsInterventionModel-based approach
2021
How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19
Accorsi E, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, Goldstein E, Stensrud M, Niehus R, Cevik M, Lipsitch M. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. European Journal Of Epidemiology 2021, 36: 179-196. PMID: 33634345, PMCID: PMC7906244, DOI: 10.1007/s10654-021-00727-7.Peer-Reviewed Original ResearchConceptsRisk Factors StudyPublic health scientistsPotential sources of biasBody of literatureSources of biasStudy designFactor studiesHealth scientistsCategories of studiesObservational studyCOVID-19Selection biasPotential biasSecondary attack rateRisk of infectionGeographical areasAttack rateRiskSusceptibility to infectionStudy of COVID-19Cross-sectional seroprevalenceConfoundingCoronavirus diseaseIntervention