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The Integrated Biostatistics and Outcome Research (IBOR) Lab has a dual mission. Firstly, in partnership with the School of Health and Rehabilitation Sciences (SHRS) Data Center, we offer comprehensive and collaborative biostatistical support to health researchers at the University of Pittsburgh. By integrating our research and statistical design experts directly into the Principal Investigator’s team, we enhance grant application efficiency and competitiveness while advancing scientific research. Secondly, we conduct independent research focused on health outcomes, contributing to the broader fields of biostatistics and epidemiology.

Pre-award, our collaboration includes:

  • Consultation on Study Design: We offer expert guidance on various aspects of study design, including biomedical experimental design, clinical trials, and public health research. Our goal is to ensure that studies are methodologically sound and capable of producing robust and reliable results.
  • Advising on Outcomes Selection: We assist researchers in selecting the most appropriate and meaningful outcomes for their studies, ensuring that the chosen metrics are both relevant and measurable.
  • Justifying Sample Size and Statistical Power: We provide statistical expertise to determine or justify the sample size needed to achieve sufficient power for detecting meaningful effects, thereby enhancing the validity of the study findings.
  • Designing and Writing Statistical Analysis/Modeling Sections: Our team collaborates with researchers to design and write comprehensive statistical analysis and modeling sections for grant proposals, ensuring that these sections are clear, accurate, and aligned with the overall study design.
  • Grant Writing on Relevant Sections: We contribute to grant writing by preparing sections related to biostatistics, study design, and data analysis, leveraging our expertise to strengthen the overall proposal.
  • Advising on the Use of National Data Registries and Large-Scale Data Systems: We guide researchers on the effective use of national data registries, health system data, and other large-scale data systems, enabling them to harness these valuable resources for their studies.

Post-award, we will support:

  • Database Management: We manage research databases, ensuring that data is collected, stored, and maintained in a secure and organized manner.
  • Implementing Randomization Schemes: We design and implement various randomization schemes, including blind and double-blind methods, to minimize bias and enhance the validity of study results.
  • Conducting Final Statistical Analyses/Modeling: We perform the final planned statistical analyses and modeling, providing researchers with accurate and insightful interpretations of their data.
  • Supporting Interim Reports: We assist in the preparation of interim reports, offering statistical insights and updates on study progress.
  • Contributing as Co-Authors: We collaborate as co-authors on scientific presentations and publications, ensuring that the biostatistical components are accurately represented and contributing to the overall quality of the research output.

Collaboration on new grant proposals and pilot work is free of charge for all SHRS faculty. We will help you determine how much funding to write into your grant for our collaboration. Contact email:

About the Director:

Dr. Xingyu Mark Zhang is an Associate Professor specializing in Biostatistics and Epidemiology within the School of Health and Rehabilitation Sciences at the University of Pittsburgh. He is a member of the American Statistical Association (ASA). Before joining the University of Pittsburgh, he served as a Research Assistant Professor at the University of Michigan and gained valuable experience as a postdoctoral research fellow in biostatistics at Emory University. His research contributions include over 80 coauthored peer-reviewed journal articles, covering both biostatistical methods and clinical research.

Independent Research Focus:

In addition to our collaborative biostatistical support, the Integrated Biostatistics and Outcome Research Lab focuses on advancing health outcomes and epidemiological research. Our dedicated team conducts cutting-edge research across several key areas:

  • Utilizing Electronic Health Record Data for Research: We delve into the vast potential of electronic health record (EHR) data to extract valuable insights into patient health and healthcare delivery. By harnessing EHR data, we aim to identify trends, patterns, and correlations that can inform clinical practice, policy-making, and health interventions. Our research includes developing methods for data integration, ensuring data quality, and addressing privacy concerns to maximize the utility of EHR data in improving patient outcomes.
  • Applying Predictive and Machine Learning Techniques in Healthcare: We investigate the application of advanced predictive analytics and machine learning algorithms to enhance healthcare outcomes and optimize healthcare services. Our work involves developing and validating predictive models that can forecast patient trajectories, identify at-risk populations, and personalize treatment plans. By integrating machine learning into healthcare, we strive to support clinical decision-making, improve diagnostic accuracy, and streamline healthcare operations.
  • Investigating Health Outcomes and Healthcare Services: Our lab conducts comprehensive studies on health outcomes and healthcare services, with a particular focus on transplantation, emergency medicine, and rehabilitation. We aim to identify factors that influence patient outcomes, such as socioeconomic determinants, healthcare access, and clinical practices. Our research seeks to uncover disparities in health outcomes, evaluate the effectiveness of interventions, and propose strategies to enhance healthcare delivery and patient care.
  • Exploring Medical Imaging Biomarkers: We explore the use of medical imaging biomarkers to advance the diagnosis, treatment, and monitoring of various health conditions. Our research involves developing and validating imaging techniques that can detect early signs of disease, track disease progression, and assess treatment responses. By integrating imaging biomarkers into clinical practice, we aim to improve the precision of diagnoses, tailor treatments to individual patients, and monitor therapeutic outcomes more effectively.


Our lab is committed to educational outreach and provides unique educational opportunities for PhD students at the School of Health and Rehabilitation Sciences. We offer mentorship and consultation in biostatistics, study design, and data analysis, preparing the next generation of researchers to excel in their scientific endeavors.