The BERD KCA Training Unit collaborates and integrates with the OSCTR Clinical Research Education, Mentoring and Career Development KCA to enhance training in epidemiology and biostatistics related to clinical and translational research.
BERD Education Online Request form
Curricular materials : Link to Seminar Series
Printed materials (in .pdf format)
- Statistical tests
- Sensitivity and specificity, predictive values, likelihood ratio statistics, and Bayes theorem applied to diagnostic and prognostic tests
- Receiver operating characteristic (ROC) curves
- What is logistic regression
- Assessing an ordinal outcome - proportional odds analysis (New: added on 9-6-2016)
- Analyzing outcomes measured as a “time to event”
- Agreement between measurements - Bland Altman plots
- Standardized Mortality Ratios (SMR)
Videostreamed tutorial (Mediasite)
- Power and Sample Size 1
- Power and Sample Size 2
- Statistical thinking: Quantifying certainty and uncertainty
- Statistical significance: Alternatives to the p value
- Analyzing outcomes measured as "time to event"
- Quantifying benefit and harm: An example from research in the OUHSC Dept. of Pediatrics
- Toward a common language for discussing effect modification, effect measure modification and biological interaction in additive and multiplicative statistical models
- Additional Material for Effect modification lecture from above (EM.zip File)
This 8-part video series will prepare you to understand and apply principles and methods in biostatistics and epidemiology that are used in medical research. Topics addressed include development of a research question;research design principles; statistical and epidemiologic measures of disease burden,distribution, and association; and methods of statistical inference and hypothesis testing.
The Training Unit of the Biostatistics, Epidemiology, and Research Design (BERD) Key Component Activity of the Oklahoma Shared Clinical and Translational Resources (OSCTR) is hosting an R Short Course. R is a language and environment for statistical computing and graphics. It is free and compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. R can be extended via user-contributed packages. Packages are available through the CRAN family of Internet sites covering a very wide range of modern statistics (https://www.r-project.org/ ).