Strengthen your research with statistical expertise, establish collaborative relationships, and receive consultations on your study design and data analysis. Our team includes biostatisticians from the Department of Biostatistics and Informatics in the Colorado School of Public Health and graduate students in the biostatistics programs.
Diana Abbott, PhD - Research Instructor
Expertise: Statistical genetics analyses—including linkage, genomewide association studies, and heredity with a specific interest in developing new methods for identifying modifier genes. Experience with clinical trials design, survival analysis, and applications of biostatistics methods to cancer data.
Background: Earned a PhD in statistical genetics from University of Iowa and a MS in biostatistics from Oklahoma University Health Sciences Center. Prior to joining CU, she worked as research faculty in genetic epidemiology at the University of Utah and managed the Biostatistics Core at Duke University.
Nichole Carlson, PhD - Associate Professor, CIDA Director
Role: Her goal as CIDA director is to create a welcoming collaborative research environment that results in new scientific partnerships through significant biostatistics contributions. Her philosophy is that biostatistics is a pillar of sound research and should be easily accessible to all AMC researchers.
Background: Associate Professor of Biostatistics and Informatics at the Colorado School of Public Health. Over 15 years experience as a collaborative biostatistician. Prior to becoming the director, she co-directed a General Clinical Research Center biostatistics core and has been a consulting faculty member in the CIDA. A leader in statistical approaches for analyzing hormone data and an expert in Bayesian methods. Received NIH funding for developing Bayesian methods for analyzing pulsatile hormones. Director of the Biostatistics, Epidemiology, and Research Design Core of the Colorado Clinical and Translational Science Institute. Received her doctorate in Biostatistics from the University of Michigan.
Debashis Ghosh, PhD - Professor
Expertise: Genomics, data integration, machine learning and causal modelling.
Background: Worked on various aspects of design and analysis of biomedical studies, and collaborations have ranged from obesity to diabetes to cancer research.
Alex Kaizer, PhD - Assistant Professor
Expertise: Adaptive clinical trial designs, methods to incorporate supplemental/historic information, biomarker validation and evaluation, Bayesian hierarchical modeling
Background: Earned a PhD in biostatistics from the University of Minnesota-Twin Cities with a graduate minor in demography (population studies) from the Minnesota Population Center. While in graduate school at Minnesota, he worked as a collaborative biostatistician on projects across the Academic Health Center, but had special focuses collaborating with the pediatric obesity working group and the Department of Anesthesiology. His past collaborative experiences have used data ranging from well-designed trials to observational databases (e.g., NHANES, NIS, rare disease data registries). Prior methods research has focused on approaches to incorporating supplemental or historic information into the analysis of a primary source and biomarker validation study design.
Miranda Kroehl, PhD - Assistant Director, Research Instructor
Role: Meet with researchers to develop biostatistics Scopes of Work Agreements for their projects, and estimate costs associated with study design, power/sample size calculations, data analysis and/or manuscript preparation.
Expertise: Microbiome and high-dimensional research, and development of statistical methods to identify direct and indirect effects (e.g. mediation, causal modeling).
Background: Earned her MS and PhD in Biostatistics from the University of Colorado Anschutz Medical Campus. Years of experience analyzing large cohort studies using survival and longitudinal analyses to identify risk factors associated with development of disease. Prior research includes the application of restricted cubic spline functions to identify and model time-varying hazard ratios in survival models, and evaluation of statistical tests for indirect effects with binary outcome variables.
Dominik Reinhold, PhD - Assistant Professor
Expertise: Stochastic processes, differential gene expression analysis, proteomics data, and statistical consulting.
Background: Doctorate in Statistics from the University of North Carolina
Sarah Schmiege, PhD - Assistant Professor
Expertise: Statistical consulting, structural equation modeling, longitudinal and multilevel data analysis, health psychology.
Background: Consults with the College of Nursing and a variety of other medical researchers. Received her PhD from Arizona State University in Quantitative Psychology in 2005.
David Weitzenkamp, PhD - Research Instructor
Expertise: Observational studies, longitudinal analysis, small studies, and rehabilitation outcomes.
Background: A co-author on several papers and taught BIOS 6612 – Biostatistical Methods II. Received his PhD in Biostatistics from the University of Colorado Denver in 2002.
Yeonjoo Yi, PhD - Research Associate
Expertise: Longitudinal data analysis,
missing data, and applied statistics.
Background: Received her PhD in Biostatistics from the Tulane University in 2008.
MS and MPH Biostatisticians
Andy Hammes, MS - Research Instructor
Expertise: Experience with a wide variety of analysis methods, including spline models and simulation power analysis, as well as working with big data.
Background: Andy received his MS from the University of Colorado Denver in 2016, and worked at the CIDA as a Research Assistant as a student while getting his degree.
Caroline Ledbetter, MPH - Senior Professional Research Assistant
Expertise: Large data sets, complex surveys designs, and reproducible research.
Background: Caroline received her MPH in Applied Biostatistics and Epidemiology from the Colorado School of Public Health in 2017, and her BA in Biochemistry from the University of Colorado Boulder in 2015.
Bryan McNair, MS - Research Instructor
Expertise: Mixed effect survival models for discrete and continuous time.
Background: Bryan was a teaching assistant for BIOS 6601: Introduction to Applied Biostatistics and BIOS 6602: Applied Biostatistics II, and has presented a number of seminars on various biostatistical topics. Received his MS from the University of Colorado Denver in 2011, and been involved with CIDA research consultations since his student days.
Matt Mulvahill, MS
- Research Instructor
Expertise: Statistical software and R package development, reproducible research practices, hierarchical modeling, machine learning, bridging disparate data sources.
Background: Matt received his MS in Biostatistics from the University of Colorado Denver in 2016, and his BS in Sociology from the University of Wisconsin - Madison in 2008.
Harry Smith, MPH - Sr. Professional Research Assistant
Expertise: Statistical analysis and bioinformatics in the context of "-omics" data, specializing in RNA-Sequencing and network analysis.
Background: Harry is a biostatistician and senior Professional Research Assistant (PRA) in the Department of Biostatistics and Informatics at the Colorado School of Public Health. He is skilled in many statistical methods including regression, mixed models, prediction modeling, and survival analysis. Proficient in R for statistical computing, SAS, and familiar with Python. He is most interested and specialize in "–omics" data, which can include genomics, transcriptomics, metabolomics, lipidomics, and proteomics. Specifically, with regards to transcriptomics, he is familiar with microarray data and RNA-Seq data. Received his MPH in applied biostatistics from the Colorado School of Public Health, and his Capstone project focused on examining the genetic influences of RNA expression on the metabolic functions in brown adipose tissue using a recombinant inbred rat panel.
Lauren Vanderlinden, MS - Research Instructor
Expertise: Extensive experience with micro array data and currently expanding to methylation data, among other areas of expertise. Extensive experience with micro array data and currently expanding to methylation data, among other areas of expertise.
Kayla Williamson, MS - Research Instructor
Expertise: Statistical analysis in the context of "-omics" data specifically microbiomics.
Background: Received her Master of Science in Biostatistics from the University of Colorado Denver and her Bachelors of Science in Statistics from the University of Wyoming.
Candidate for MS degree
|Research Assistant |
Email Rachel J.
Email Rachel W.