The UC Davis MIND Institute IDDRC Biostatistics, Bioinformatics, and Research Design (BBRD) Core provides comprehensive statistical support to assist the IDDRC investigators and their projects at all stages of the research process. The BBRD Core is a new resource for the MIND Institute and UC Davis researchers studying IDD. BBRD faculty and staff have extensive experience on a broad range of IDD-related clinical and laboratory studies, assisting with study design, protocol and proposal development, data analysis, and publication of results. The BBRD Core also assists with the planning and development of research-related data management systems. The BBRD Core services are matched to the special needs of each of the IDDRC clinical, laboratory and population-based studies and cover a full range of services from routine analysis support to innovative methods developed specifically to enhance the research efforts of the IDDRC interdisciplinary team. The core also collaborates with other IDDRC cores, notably on informatics infrastructure and database development. Basic consulting services are generally provided free of charge to the IDDRC members. Members requiring extensive assistance for long-term projects are expected to provide regular salary support to a Core statistician.
The Core provides the following services:
- Study Design
- Provide advice on all aspects of statistical design and analysis planning
- Support protocol development and grant applications with design recommendations and power/sample size calculations
- Data Collection and Database
- Assist in the design of the data abstraction, including identifying variables to collect and defining variable fields
- Advice on database structure and data safety monitoring
- Monitor clinical trials for adverse events and data quality
- Data Analysis and Reporting
- Evaluate and conduct statistical analysis for clinical and laboratory studies
- As needed, the core works to develop and refine statistical methods and software
- Summarize and interpret the results of the statistical analyses in relation to the research objective or hypothesis.
- Collaborate on abstract and manuscript preparation
- Education and Training
- Contribute to the training and mentoring of predoctoral students, postdoctoral scholars, and IDDRC investigators in the areas of biostatistics and research design
- Provide IDDRC-wide workshops on a quarterly basis on a range of topics pertinent to IDDRC research.
BBRD On-Line Request
Click here to submit a BBRD on-line request for statistical support
BBRD Workshop Series
The IDDRC Biostatistics and Research Design (BBRD) Core offers quarterly workshops on biostatistics that provide an understanding of the principles, methodological strategies and applied aspects of IDDRC research and practice. Please click on the link for each of the previous BBRD workshop series.
March 12, 2015, 1-2:30pm
Speakers: Blythe P Durbin-Johnson, Ph.D.
Title: Gene expression analysis for complex study designs
This workshop will provide an overview of gene expression studies in translational research. Gene expression profiling (by RNA sequencing or microarrays) has become an important research tool. However, many analysis tools for these data are limited to two-group comparisons, and do not allow for covariate adjustment, which is very essential for clinical studies in human. This talk focuses on two Bioconductor tools, edgeR and limma-voom, that can fit any linear model to gene expression data. We will give a brief overview of statistical models used for gene expression data, discuss the relative merits of the above packages, and provide a brief tutorial on use of these packages for a model with multiple covariates, including syntax for model specification, setting up the design matrix, testing for effects of interest, and interpreting the results. Slides (PDF)
Wednesday, October 22, 2014, 1:30-3pm
Speakers: Irva Hertz-Picciotto, Ph.D. and Chin-Shang Li, Ph.D.
Title: Study designs for clinical trials or intervention studies
This workshop will discuss design options both for observational studies, in which the investigator does not control the exposure or treatment received, and clinical trials, in which the investigator assigns individuals to exposure or treatment group. For observational studies, approaches to cohort (usually prospective) and case-control studies will be discussed, including sampling designs, repeated measures, principles of control selection (case-control) and specific sampling strategies. For clinical trials, the presentation will include an overview of crossover designs, statistical methods for analyses of data from the designs, and power analyses. Examples will be provided. Slide (PDF)
Wednesday, April 23, 2014, 1-3pm
Speakers: Danielle Harvey, Ph.D. and Sandy Taylor, Ph.D.
Title: Introduction to Repeated Measures and Longitudinal Data
This first workshop the IDDRC Biostatistics, Bioinformatics and Research Design (BBRD) Core will deliver is an introduction to repeated measures and longitudinal data analysis commonly used for a broad range of IDD-related clinical and laboratory studies, April 23, 1-3pm, holding at the MIND Boardroom. In this workshop, we will start with examples of repeated measures and longitudinal data, and discuss why standard methods such as linear regression or analysis of variance are not appropriate for these data types. We will then give an overview of commonly used analytic methods including the key assumptions of the methods and interpretation of the results. Finally, we will discuss approaches to handling missing data and drop-out, and strategies for baseline adjustment as these are common challenges with analyzing longitudinal data. The workshop assumes no prior knowledge of these methods and so will be appropriate for researchers at all levels, from students through faculty. General familiarity with statistics will be helpful but not essential. The goal of the workshop is to help researchers recognize repeated measures and longitudinal data, understand the analytical approaches required for these data types, and to know what information and decisions are needed for appropriate analysis of the data. Slides (PDF) Part 1, Part 2
Irva Hertz-Picciotto, Ph.D., Core Director
Kyoungmi Kim, Ph.D., Co- Director
Blythe Durbin-Johnson, Ph.D., Staff Statistician
Ana Maria Iosif, Ph.D., Faculty Statistician
Danielle Harvey, Ph.D., Faculty Statistician
Chin-Shang Li, Ph.D., Faculty Statistician
Sandra Taylor, Core Manager