Request CTRI Services

Assistance is available for the following:

  • Statistical design of experiments including statistical analysis plans and power calculations
  • Scientific computing for data analysis and graphics
  • Efficient database design, performed in conjunction with Biomedical Informatics
  • Preparation of manuscripts and grant applications
  • Advice on the use of statistical software

All requests must be submitted using the "Request CTRI Services" link. Investigators are encouraged to become CTRI members before submitting the requests. Up to 4 hours of assistance are available to CTRI members for grant preparation without recharge. All investigators receiving biostatistics assistance during grant preparation are required to include biostatistics costs in the budgets for their grant proposals (a practice that usually strengthens the applications).

Considerations of co-authorship should be based on intellectual and research contributions, which include design, analysis, and interpretation, regardless of compensation. For more on authorship guidelines, see International Committee of Medical Journal Editors uniform requirements for manuscripts.

Timelines: Since we usually work on multiple projects at a time, advance notice is strongly encouraged.

  • For grant submissions that do not involve preliminary data analysis, at least 1 month advance notice is required.
  • For grant submissions involving preliminary data analysis as well as for abstract submissions, at least 2 months advance notice is required. It is CTRI policy that a statistical analysis plan be formally approved by our co-investigators before analysis is carried out.
  • Free walk-in biostatistics consultation is available every Wednesday from 1:00 to 5:00 PM in the East Campus Office Building, room 1-056, Phone: 858-657-5149.

Recharge Rates

Biostatistics recharge rates are ~ $70/hour.  Non-UCSD funded users are charged slightly more.

Some Useful Links

For clinical and translational research (including educational materials)

For sample size calculation

For organizing data

Importance of reproducible research