Xin Zhou, PhD
Assistant Professor of BiostatisticsDownloadHi-Res Photo
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Assistant Professor of Biostatistics
Biography
Dr. Zhou is an assistant professor in the Department of Biostatistics at the Yale School of Public Health. He received his Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill in 2015. Prior to arriving at Yale, Dr. Zhou was a Postdoc Fellow in the Departments of Biostatistics and Epidemiology at Harvard T.H. Chan School of Public Health. His research is focused on statistical and machine learning methods in precision medicine, measurement error correction, cluster randomized trials, and high dimensional data analysis.
Last Updated on January 06, 2025.
Appointments
Biostatistics
Assistant ProfessorPrimary
Other Departments & Organizations
- Biostatistics
- Cancer Prevention and Control
- R3EDI Implementation Science Hub
- Yale Cancer Center
- Yale School of Public Health
Education & Training
- Postdoc Fellow
- Harvard T.H. Chan School of Public Health (2018)
- PhD
- University of North Carolina at Chapel Hill, Biostatistics (2015)
- MS
- University of North Carolina at Chapel Hill, Biostatistics (2013)
Research
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Overview
Medical Research Interests
Biostatistics; Clinical Trial; Dimensional Measurement Accuracy; Epidemiologic Methods; Implementation Science; Precision Medicine; Randomized Controlled Trial; Research Design
Public Health Interests
Survival Analysis; Nutrition; Infectious Diseases; Environmental Health; Epidemiology Methods; Cancer; Clinical Trials
ORCID
0000-0003-2238-2890
Research at a Glance
Yale Co-Authors
Frequent collaborators of Xin Zhou's published research.
Publications Timeline
A big-picture view of Xin Zhou's research output by year.
Research Interests
Research topics Xin Zhou is interested in exploring.
Donna Spiegelman, ScD
Luke Davis, MD
Ashley Hagaman, PhD, MPH
Carmen Black, MD, MHS-Med Ed
Christopher Fields
Dylan Gee, PhD
23Publications
442Citations
Research Design
Publications
2025
Longitudinal and Geographic Trends in Perceived Racial Discrimination Among Adolescents in the United States: The Adolescent Brain Cognitive Development Study
Fields C, Black C, Calhoun A, Rosenblatt M, Rodriguez R, Aina J, Thind J, Grayson J, Khalifa F, Assari S, Zhou X, Nagata J, Gee D. Longitudinal and Geographic Trends in Perceived Racial Discrimination Among Adolescents in the United States: The Adolescent Brain Cognitive Development Study. Journal Of Adolescent Health 2025, 77: 118-127. PMID: 40382724, DOI: 10.1016/j.jadohealth.2025.03.014.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsNon-Hispanic youthPerceived DiscriminationDevelopment studiesHigher levels of perceived discriminationAmerican Community SurveyAnti-Black biasLevels of perceived discriminationPacific IslandersPerceived Discrimination ScaleWhite non-Hispanic youthNeighborhood segregationBlack householdsBlack youthContext-specific approachImmigrant backgroundPerceived Racial DiscriminationRacial discriminationCommunity surveyRacial biasYouthGeographic variationStructural contextAdolescent Brain Cognitive Development StudyNational representativesRacial/ethnic groups
2023
Correcting for Bias Due to Mismeasured Exposure History in Longitudinal Studies with Continuous Outcomes
Cai J, Zhang N, Zhou X, Spiegelman D, Wang M. Correcting for Bias Due to Mismeasured Exposure History in Longitudinal Studies with Continuous Outcomes. Biometrics 2023, 79: 3739-3751. PMID: 37222518, PMCID: PMC11214728, DOI: 10.1111/biom.13877.Peer-Reviewed Original ResearchCitationsImplementation of a Hardware-Assisted Bluetooth-Based COVID-19 Tracking Device in a High School: Mixed Methods Study
Li D, Shelby T, Brault M, Manohar R, Vermund S, Hagaman A, Forastiere L, Caruthers T, Egger E, Wang Y, Manohar N, Manohar P, Davis J, Zhou X. Implementation of a Hardware-Assisted Bluetooth-Based COVID-19 Tracking Device in a High School: Mixed Methods Study. JMIR Formative Research 2023, 7: e39765. PMID: 36525333, PMCID: PMC10131711, DOI: 10.2196/39765.Peer-Reviewed Original ResearchCitationsAltmetricConceptsContact tracingPilot implementation studyPublic health toolMixed-methods evaluationTechnical difficultiesSignificant numberQualitative focus group discussionsClose contactInfectious diseasesHealth toolsLarge-scale pandemicMixed-methods studyImplementation outcomesCOVID-19Significant differencesImplementation studyEmotional reassuranceFocus group discussionsMost contactMixed methods designMethods studySustained useCase interviewsMaintenance frameworkHabits
2021
Evaluating the Quality of Tuberculosis (TB) Care in Low and Middle Income Countries
Saranjav A, Parisi C, Zhou X, Chuluun A, Spiegelman D, Davaasambuu G, Davis J. Evaluating the Quality of Tuberculosis (TB) Care in Low and Middle Income Countries. 2021, a3917-a3917. DOI: 10.1164/ajrccm-conference.2021.203.1_meetingabstracts.a3917.Peer-Reviewed Original Research
2018
A Modified Partial Likelihood Score Method for Cox Regression with Covariate Error Under the Internal Validation Design
Zucker DM, Zhou X, Liao X, Li Y, Spiegelman D. A Modified Partial Likelihood Score Method for Cox Regression with Covariate Error Under the Internal Validation Design. Biometrics 2018, 75: 414-427. PMID: 30525191, PMCID: PMC6555694, DOI: 10.1111/biom.13012.Peer-Reviewed Original ResearchCitationsAltmetricHealth system measurement: Harnessing machine learning to advance global health
Leslie HH, Zhou X, Spiegelman D, Kruk ME. Health system measurement: Harnessing machine learning to advance global health. PLOS ONE 2018, 13: e0204958. PMID: 30289935, PMCID: PMC6173424, DOI: 10.1371/journal.pone.0204958.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsFacility surveyHealth facility surveyService Provision Assessment surveyKappa statisticsHigh-quality careWorld Health OrganizationSequential backward selectionMiddle-income countriesPatient outcomesHealth facilitiesService readinessGlobal health expertsFull indexUnsupervised machineComplex burdenHealth OrganizationPopulation healthHealth expertsA maximum likelihood approach to power calculations for stepped wedge designs of binary outcomes
Zhou X, Liao X, Kunz LM, Normand ST, Wang M, Spiegelman D. A maximum likelihood approach to power calculations for stepped wedge designs of binary outcomes. Biostatistics 2018, 21: 102-121. PMID: 30084949, PMCID: PMC7410259, DOI: 10.1093/biostatistics/kxy031.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsVariable cluster sizesMaximum likelihood approachLikelihood approachCluster sizeLeast squares approachStatistical theoryCluster random effectsBinary outcomesNumber of clustersNumerical methodParameter spaceRobustness of powerAsymptotic powerSquares approachIntra-cluster correlation coefficientRandom effectsParallel clusterLarge-scale intervention programmesPower calculationNew methodAvailable methodsWedge designSequential rolloutTheoryClustersEvaluating Public Health Interventions: 8. Causal Inference for Time-Invariant Interventions.
Spiegelman D, Zhou X. Evaluating Public Health Interventions: 8. Causal Inference for Time-Invariant Interventions. American Journal Of Public Health 2018, 108: 1187-1190. PMID: 30024804, PMCID: PMC6085031, DOI: 10.2105/ajph.2018.304530.Peer-Reviewed Original ResearchCitationsAltmetric
2017
Service readiness of health facilities in Bangladesh, Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Uganda and the United Republic of Tanzania
Leslie HH, Spiegelman D, Zhou X, Kruk ME. Service readiness of health facilities in Bangladesh, Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Uganda and the United Republic of Tanzania. Bulletin Of The World Health Organization 2017, 95: 738-748. PMID: 29147054, PMCID: PMC5677617, DOI: 10.2471/blt.17.191916.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsHealth centers/clinicsCenters/clinicsHealth facilitiesService readinessBasic clinical careFacility-level characteristicsHealth system capacityMost health facilitiesService Provision AssessmentWorld Health OrganizationClinical careDiagnostic capacityHealth systemHealth OrganizationCountry inequitiesUnited RepublicHealth careHospitalClinicHealth financingUniversal coverageStudy countriesCareWeak correlationIndexSurvival Analysis with Functions of Mismeasured Covariate Histories: The Case of Chronic Air Pollution Exposure in Relation to Mortality in the Nurses’ Health Study
Liao X, Zhou X, Wang M, Hart JE, Laden F, Spiegelman D. Survival Analysis with Functions of Mismeasured Covariate Histories: The Case of Chronic Air Pollution Exposure in Relation to Mortality in the Nurses’ Health Study. Journal Of The Royal Statistical Society Series C (Applied Statistics) 2017, 67: 307-327. PMID: 29430064, PMCID: PMC5801717, DOI: 10.1111/rssc.12229.Peer-Reviewed Original ResearchCitationsAltmetricConceptsHealth StudyCox modelChronic air pollution exposureNurses' Health StudyChronic disease incidenceExposure historyAir pollution exposureExposure measurementsCause mortalityIndividual exposure measurementsLong-term exposureSurvival analysisFine particulate matter componentsPollution exposureMortalityEffects of functionParticulate matter componentsEnvironmental epidemiologistsExposureExtended riskDisease incidenceRegression calibration methodIncidenceNursesStudy
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News
- August 29, 2023
$4 Million Grant Will Help YSPH Team Implement New LGBTQ Mental Health Therapy
- August 08, 2022
Colleen Chan, Yale Department of Statistics and Data Science PhD student, receives the Florence Nightingale Award at the 31st International Biometric Conference
- August 30, 2021
Researchers at the Yale Center for Methods in Implementation and Prevention Science Develop New Software for Power Calculations in Stepped Wedge Cluster Randomized Trials
- July 27, 2020
YSPH Researchers Find that Vitamin D Supplementation Does Not Lower Children’s Risk of TB Infection
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