Statistical Design and Analysis
Our statisticians possess expert knowledge and skill in many facets of statistical design and analysis. We apply a variety of innovative statistical methodologies to diverse programs in health and environmental studies, as well as to both government- and private-based program evaluations.
Center of Excellence for Complex Data Analysis
The Center of Excellence for Complex Data Analysis, or CoDA Center, was formed at RTI to respond to the need for complex data analysis across public and private sectors. The CoDA Center is designed to help government agencies, private businesses, and other organizations make informed policy and program decisions based on analyses of complex data sets. Read more about the CoDA Center, its scholars, and programs.
Complex, multisite studies; interdisciplinary studies with multiple data types; randomized clinical trials; disease surveillance; prospective cohort studies; population genetics studies
- Environmental statistics
Environmental sampling design; geostatistics, spatial, and spatio-temporal models; exposure studies; toxicology studies; risk assessment
- Program evaluation
Community-based interventions; multi-site intervention trials and demonstration projects; chronic disease prevention and management programs, such as diabetes and asthma; social and behavioral research with HIV and STD prevention projects; tobacco control programs and policies; cancer control programs and interventions; obesity, nutrition and physical activity programs and interventions
- Statistical genetics and bioinformatics
Clinical trials; natural history studies of disease progression; epidemiological research on incidence, prevalence, risk factors, and causes of diseases; research on genetic contributions to complex biological processes; environmental toxins; analyses of proteomic data
- Experimental design
Blocking or stratification; randomizing experimental units to treatments; randomizing treatment order in cross-over clinical trials; confounding and aliasing higher-order effects; applying specialized methods of analysis for a variety of designs
- Longitudinal analysis and multilevel modeling
Account for survey design, sampling units, stratification; adjust for clustering or stratification of participants; account for repeated measures on the same subject; control for randomization of groups instead of individuals; adjust for repeated tests or observations
- Modeling and simulation
Chronic diseases; infectious and emerging diseases, biothreats; environmental exposure and health risks; cost-effectiveness of medical and public health interventions; epidemic response and containment; resource allocation modeling; forecasting of personnel turnover; predictive models of morbidity and mortality
Scale and test development and validation; improvement on existing instruments; incorporating measurement models in analysis for correct inference; understanding sources of measurement error
- Qualitative analysis
Focus groups and triads; key informant interviews; site observations; case studies; document reviews; ethnography; rapid assessment procedure; cognitive/think-aloud interviews
Survey-design-sensitive implementation of Taylor series linearization (GEE for regression models), jackknife (with or without user-specified replicate weights), and balanced repeated replication methods of measuring standard errors and conducting statistical tests
RTI International has selected Alan Karr, Ph.D., as director of the Center of Excellence for Complex Data Analysis.
In this position, Karr will be responsible for a number of activities related to complex data analysis across RTI including: statistical training, the Center’s visiting scholar program and the Triangle Census Research Data Center.Read more