Consulting for Statistics, Computing and Analytics Research (CSCAR) provides individualized support and training to University of Michigan researchers in a variety of areas relating to the management, collection, and analysis of data. CSCAR also supports the use of technical software and advanced computing in research. Researchers from nearly all disciplines at U-M have made effective use of our services.

Our scope is broad, including formal statistical analysis, management of large data sets, development and optimization of computing code, data visualization, predictive modeling, geographic information systems, and text analysis, among other areas.  See our areas of expertise page for more details.

Many of our services are free to the U-M research community.  Contact us at cscar@umich.edu with administrative questions.  Technical questions can be sent to the email addresses listed on our contacts page.

The CSCAR Team

Chris Andrews

CSCAR Consultant

Expertise: Statistical modeling, particularly survival analysis, all forms of regression, programming in R and SAS; applications to clinical trials, administrative claims data, and some “omics” areas.

Jesse Cordoba

CSCAR Administrative Assistant

Expertise: Coordinating communications, organizing documents, streamlining office operations, and supporting team efficiency.

Josh Errickson

CSCAR Consultant

Expertise: Statistical modeling and computation; causal inference, data imputation, basic to advanced regression analysis, resampling approaches, multivariate analysis, complex surveys, programming in Stata and R.

Brenda Gillespie

CSCAR Director, Research Associate Professor of Biostatistics

Expertise: Survival analysis, including interval/left-censored data, designed experiments; generalized linear models; mixed and multilevel models; multiple imputation; applications to clinical trials, programming in SAS and R.

Abner Heredia Bustos

CSCAR Consultant

Expertise: Basic to advanced regression, multivariate methods, Bayesian modelling and inference, time series analysis, dimension reduction techniques, and machine learning methods for classification. Programming in R and Python.

Carol Janney

CSCAR Consultant

Expertise: Epidemiology; research design, analysis, interpretation, and presentation of findings; basic to intermediate applied biostatistics; programming in SAS and SPSS; writing of research methods and results for publications, presentations, grants, and proposal development; clinical trials; statistical modeling (linear, logistic, survival, longitudinal); formulation of hypotheses and specific aims; and experience with national public datasets (NHANES, SEER).

Hyungjin Myra Kim

CSCAR Research Scientist, Adjunct Professor of Biostatistics

Expertise: Advanced biostatistics, clinical trials, basic to advanced regression, multilevel modeling, marginal structure modeling, missing data methods, longitudinal data, causal inference, programming in Stata, R, and SAS; applications to administrative claims data, pharmaco-epidemiology.

Corey Powell

CSCAR Consultant

Expertise: Basic to intermediate statistics, all forms of regression analysis, multivariate methods, programming in R, SAS, and Perl; applications to biostatistics and bioinformatics.