Research Collaboration Program

The S-SPIRE team is happy to receive collaboration requests related to health services research projects. Collaboration consists of an initial in-person meeting at S-SPIRE Center to discuss short- and long-term quantitative, qualitative, and mixed methods research projects and follow-up assistance with research design, instrument development, analysis, interpretation, and write-up of methods/analysis for papers and grant proposals. Please plan for availability at least two weeks out. 

Timeline for Initial Collaboration Request

Please note, initial collaboration requires two weeks for scheduling. Please plan accordingly. Ample lead time will result in much higher quality assistance from our team.

Conference Abstract Deadlines

The initial collaboration should occur with a minimum 4 weeks lead time with your data ready for analysis. 

Special issue or meeting paper deadlines

The initial collaboration should occur with a minimum 6 weeks lead time with your data ready for analysis. Depending on the complexity of the analysis proposed, longer lead times may be necessary.

Grant application deadlines

The initial collaboration should occur with a minimum 8-12 weeks lead time with your data ready for analysis. The statistical tests you would like to conduct are tied to the research questions and design; therefore, earlier statistical collaboration will inform the development of your grant. 

Preparing for your collaboration

Did you submit a collaboration request form

1) Ensure that you have IRB approval for your project and appropriate approvals for data use if applicable prior to placing collaboration (see IRB Permissions below).

2) The study PI must be present for the first in-person meeting and participate in periodic study team meetings, as well as respond to emails.

3) For analyses, please bring your research question (per collaboration request), data collection instruments, data collection strategies and population, cleaned datasets (see Preparing Your Data for Analysis below), and relevant literature and guiding conceptual frameworks.

For power analysis, please bring the estimated effect size.

• Here is a brief explanation of effect sizes (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3444174/ ).

• Here is a brief explanation of how to calculate the effect size from prior studies

a) https://stats.idre.ucla.edu/stata/dae/two-independent-proportions-power-analysis/

b) https://stats.idre.ucla.edu/stata/dae/logistic-regression-power-analysis/

c) http://med.stanford.edu/s-spire/research/S_SPIRE_Monthly_WIP/S_SPIRE_June4-18.html

• If there are no prior studies, you can estimate your effect size based on your clinical expertise.

4) If students or trainees are involved with projects, they will create the initial shell tables for team review and populate the final shell tables with data output.