ABOUT US

The Quantitative Sciences Unit (QSU) is a collaborative statistics unit in the Biomedical Informatics Research (BMIR) Division in the Department of Medicine (DOM).

Our Mission:

The mission of the QSU is to facilitate cutting-edge scientific studies initiated by Stanford investigators by providing expertise in biostatistics and informatics, to mentor and educate clinical investigators in research methods, and to mentor data scientists so that they can reach their full potential.  The QSU achieves its mission through an interdisciplinary collaborative approach where QSU members become fully integrated into individual research teams.  

More About Us:  

The QSU was created in response to an increasing demand for statistical support and data coordination. QSU members are statistical scientists with expertise in missing data, prediction modeling, statistical computing, database creation, and software development. The QSU currently collaborates on 30 large-scale scientific projects. We believe that to further science, it is important to facilitate the flow of data to investigators as efficiently as possible. We are also committed to providing sound analyses in a timely fashion. Finally, we believe that interdisciplinary research is best achived by full integration of all investigators. Our members become an integral part of each research team in which we are involved.

Our specific goals are to:

  • Design studies that optimize the ease of interpreting results
  • Provide high quality data analysis using modern statistical techniques
  • Develop new or adapt old methods for optimal analysis as the need arises
  • Securely house and track data in a HIPAA-compliant and IRB-compliant manner
  • Create user-friendly publicly available software for recommended methods
  • Interpret results
  • Disseminate findings
  • Mentor clinical investigators in research methods

Stanford has a rich history of doing high quality science. We are excited to be part of that process.

Featured Paper

Desai M, Joyce V, Bendavid E, Olshen RA, Hlatky M, Chow A, Holodniy M, Barnett P, Owens DK (2015) 

Risk of cardiovascular events associated with current exposure to HIV antiretroviral therapies in a US veteran population. Clinical Infectious Diseases, 2015 Aug 1

Full Text Here: 

 

Kunz SN, Zupancic JAF, Rigdon J, Phibbs CS, Lee HC, Gould JB, Leskovec J, Profit J (2017)

Network analysis: a novel method for mapping neonatal acute transport patterns in California. Journal of Perinatology (2017) 00, 1-7

Full Tex Here:

 

THE QSU IS HIRING!

QSU RESEARCH METHODS SEMINARS

Seminar Location: 
1070 Arastradero Road 
Rm. 109 
Time:
4-5pm first Tuesday of the month (unless otherwise stated)  
Refreshments served
Free parking

 

Upcoming Seminar


Location:
 1070 Arastradero Road, Room 109, Palo Alto, CA 94304

Time: April 4, 2017

Speaker: Trevor Hastie, Professor of Statistics and of Biomedical Data Science, Stanford University

Title:  Statiscial Learning with Sparsity

Featured Paper

Desai M, Joyce V, Bendavid E, Olshen RA, Hlatky M, Chow A, Holodniy M, Barnett P, Owens DK (2015) 

Risk of cardiovascular events associated with current exposure to HIV antiretroviral therapies in a US veteran population. Clinical Infectious Diseases, 2015 Aug 1

Full Text Here: