Research Infrastructure Core
The Research Infrastructure Core offers research support to faculty, postgrads, and graduate students conducting health disparities community engaged research.
We aim to build interdisciplinary research in health disparities, and this includes engaging investigators that are new to the field that can include biomedical researchers with no clinical research backgrounds, and social science researchers with experience in to qualitative or survey-based research.
If you are interested in obtaining any of the services described below, please submit a consultation request form. Responses vary from 7-10 days.
Advance Statistics Series
As part of the statistical support available through the RIC, we have developed the Advance Statistics Series which includes micro lectures on various quantitative research methods.
See the series website to learn more.
Human Subjects Protocol Navigator
Individuals who are new to community-based research will also receive support to through the IRB process. We will provide feedback to researchers writing human subjects protocols and guide them through the IRB approval process.
Note: the UCR Office of Research and Economic Development (RED) is the home of the campus Institutional Review Board (IRB), for social sciences and clinical research, as well as online training through CITI, in-person seminars, and online human subjects protocol forms.
Biomedical Statistical Support (Study Design and analysis)
We aim to assist faculty, graduate, and postgraduate researchers in setting up well-designed studies in both basic biomedical science and clinical research. We provide consulting services in pre-proposal research study design, as well as ongoing support for database management and data analysis.
Social Science Statistical Support
We offer support across various stages of research projects for faculty, graduate, and postgraduate researchers engaging in social science research. Prior to data collection, we can consult on study design, survey development, and measurement invariance. Post data collection, we provide support with data analysis, code troubleshooting, and output interpretation.
If you have any questions about obtaining support in these areas, please contact Samantha Ying at samantha.ying@ucr.edu