University of Michigan-Flint faculty have traditionally relied on CSCAR (Consulting for Statistics, Computing & Analytics Research) at UM – Ann Arbor to assist with their statistical analysis and research design needs. The Office of Research at UM-Flints maintains a consulting budget for requests that require extensive support, beyond the usual first hour of free consultation at CSCAR. These services remains available to UM-Flint faculty. In recent years, the training workshops provided by CSCAR have shifted towards more advanced data science. Many of CSCAR’s offerings are focused on programming-heavy languages like Python, C++, Matlab, R, and Julia. This shift towards data science also reflects a shrinking demand for in-person introductory statistics training.
CSCAR has experienced less demand for instructor-led training because more introductory statistical learning has moved online. For instance, the University of Michigan Human Resources now makes a large set of offerings available to faculty and staff through its Organizational Learning unit. Online modules on statistical software and analysis in SAS, STATA, SPSS, R, Python and many other statistical packages (commercial and open source) are available at no cost to faculty and staff via the University of Michigan’s subscription to LinkedIn Learning. Another valuable resource, for tutorials and coding examples, is the publicly available learning modules of UCLA’s Office of Advanced Research Computing (OARC) Statistical Consulting unit. The UCLA website is a valuable resource for intermediate users, with many annotated examples of how to code common statistical methods (ie., power analysis, logistic regression, count models, mixed effect models, latent class analysis) in a wide variety of statistical software.
In spite of the growth of online resources, we recognize that it remains valuable to consult with colleagues, especially those with extensive experience in statistical methods. This fall the UM-Flint Office of Research will pilot a Methods Core program on campus to better support faculty needs for statistical consulting. The service will begin in September, 2022, and will initially consist of the provision of peer consulting services. UM-Flint tenure track faculty with advanced methods training will be available for peer consultation during the academic year. Statistical workshops will also be offered during the study breaks in the fall and winter terms.
Dr. Woojong Kim from SEHS and Dr. Michelle Sahli from CHS will be offering peer consulting hours in winter 2023. Dr. Kim has an expertise on data analysis using SPSS and Mplus and survey design. Dr. Sahli is available for consultation on study design and conduct, analysis, interpretation and communication of study findings.
Faculty and students can book a consultation using the following link to Dr. KIm’s Schedule or link to Dr. Sahli’s Schedule. The link interfaces with UM Google Calendar using the new Appointment Block feature (and looks similar to applications like Calendly). Faculty can book a consultation 12 hours in advance of the available times. Dr. Sahli will offer a half-day introductory workshop during the winter study break on February 27.
The following is a list (in alphabetical order) of faculty bios for the inaugural Methods Core faculty who have agreed to serve in this capacity as their schedules allow, with a brief description of their areas of expertise and interest.
Associate Professor, Sociology
Dr. Drummond-Lewis is a quantitative sociologist whose research interests include intersections of race/ethnicity, gender, culture, health, and migration. Her research examines the health and well-being of Caribbean people while accounting for cross-national and international variations. She explores health disparities among Black and Afro-Caribbean adults and Afro-Caribbean women and girls and examines broad issues of well-being for underrepresented groups of adolescent immigrants, with the expressed goal of highlighting their unique health-related concerns and socio-cultural contributions.
- Drummond-Lewis, Sasha. 2022. Female adolescents’ weight perceptions and weight control behaviors: A comparison of Trinidadian and Guyanese Students. Caribbean Quarterly 68 (1): 90-104. doi.org/10.1080/00086495.2022.2037244
- Lacey, Krim K., Regina Parnell, Sasha R. Drummond-Lewis, Maxine Wood and Karen Powell Sears. 2021. Physical intimate partner violence, childhood physical abuse and mental health of U.S. Caribbean Women: The Interrelationship of Social, Contextual, and Migratory Influences. International Journal of Environmental Research and Public Health 19 (150): 1-13. DOI: 10.3390/ijerph19010150
Assistant Professor, Social Work
Dr. Kim’s scholarship focuses on the association between individual life experiences and health status, influenced by differences in socioeconomic status and environment, and the design of comprehensive culturally relevant interventions. The research ranges from the use of nationally representative data to community-based research. The topics have included the impacts of intimate partner violence (IPV) on survivors’ health and recent work has included examinations of health status among Flint residents with limited mobility and financial resources. She is working with several community organizations to help them evaluate the effectiveness of their services and activities. Her training has included immersion in comprehensive research projects which include designing assessment tools, collecting data, creating analysis plans, and writing research papers and reports for community organizations. Her skills include both quantitative and qualitative research, secondary data analysis, data collection from local settings, and focus group research.
- Kim, W., & Groden, S. R. (2022). Stress and health status among members of a disadvantaged community in Flint, Michigan in the early phase of the COVID-19 pandemic. Journal of community health, 1–8. Advance online publication. https://doi.org/10.1007/s10900-022-01120-5
- Kim, W., Cho, H., Hong, S., Nelson, A., & Allen, J. (in press). Concurrent intimate partner violence: survivors’ health and help-seeking. Violence Against Women.
Associate Professor, Education
Dr. Oshio’s professional preparation is in developmental psychology and she has substantial training in statistical analysis. Her primary research interest is in the socio-emotional development of children and youth, and her research interests include both biological and environmental factors that relate to child and youth development. She has worked on various national datasets including: High School Longitudinal Study, Project on Human Development in Chicago Neighborhoods, Early Head Start Research and Evaluation Project, and Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) and Kindergarten (ECLS-K). She is proficient in statistical analysis of longitudinal data sets using multilevel and multivariate analyses such as structural equation modeling, hierarchical linear modeling, and growth curve modeling. She is skilled at various statistical software including SPSS, Mplus, and HLM, and is efficient with R and SAS.
- Oshio, T., Kupperman, J. The Problem Behind the Problem: Applying Human-Centered Design to Child Care in Flint. Early Childhood Educ J (2021). https://doi.org/10.1007/s10643-021-01263-5
- Nienhusser, H. K. and T. Oshio (2020). “Postsecondary Education Access (Im)Possibilities for Undocu/DACAmented Youth Living With the Potential Elimination of DACA.” Educational Studies 56(4): 366-388. https://doi.org/10.1080/00131946.2020.1757448
Clinical Assistant Professor, Public Health
Dr. Sahli is an epidemiologist by training and an assistant clinical professor in the Department of Public Health and Health Sciences. Her research has largely focused on nutrition and vision but, as an epidemiologist, by definition, she is trained in studying and analyzing the distribution, patterns, and determinants of health-related conditions in populations (although the same methods can often be applied to non-human studies as well). She has worked on large cohort study data sets including those from the Women’s Health Initiative and the Atherosclerosis Risk in Communities Study. Some of the statistical methods Dr. Sahli uses in her research include linear regression, logistic regression, principal component regression, reduced rank regression and partial least squares regression. She is proficient in SAS and SPSS software and has a working knowledge of R and Python. She is always interested in learning other methods and software and is currently working on learning MaxQDA software for qualitative and mixed methods data.
As part of the methods core, Dr. Sahli would be happy to assist researchers at any stage in their research, but ideally her assistance would begin with helping to formulate study questions and ensuring that the study design and statistical analysis plan being used is capable of answering those questions. She can continue to assist researchers with conducting the statistical analyses (including troubleshooting if needed), interpreting the results of these analyses and reporting of these results in an appropriate manner (written, tables, graphs etc.).
- Trojanowski, S., C. M. Vos, L. M. Smith, M. W. Sahli, A. Yorke and C. Turkelson (2022). “An interprofessional community-based program for diabetes education and exercise self-management.” Journal of Interprofessional Education & Practice 27: 100508. DOI: https://doi.org/10.1016/j.xjep.2022.100508
- Sahli, M. W., H. M. Ochs-Balcom, S. M. Moeller, W. E. Brady, T. W. Tolford and A. E. Millen (2020). “Findings from Optometrists’ Practices in Advising about Lifestyle Study.” Optometry and Vision Science 97(8). doi: 10.1097/OPX.0000000000001555