The Biostatistics Shared Resource provides statistical consultation and collaboration on the design, conduct, analysis and interpretation of clinical investigators' research activities at Winship Cancer Institute of Emory University.
The purpose of the Biostatistics Shared Resource at Winship Cancer Institute of Emory University is to provide a comprehensive, multi-disciplinary collaboration in the design and analysis of clinical, preclinical and epidemiologic investigations as well as experiments that involve data from high throughput technologies.
Biostatistics support is critical to most all of the peer-reviewed funded investigators at Winship, and both fields play a fundamental role in pre- and post-funding award stages of cancer research studies.
Our shared resource is recognized as an essential element of research infrastructure at Winship by way of collaboration and consultation with investigators in the design, conduct and analysis of cancer-related clinical, preclinical and epidemiological investigations. These collaborations lead to the application and development of innovative statistical methodology and summarization of results to address cancer research.
Services include:
Collaborations within Winship and in the larger university community are supported by collaborative grants.
We offer software for various phase I clinical trial designs including escalation with overdose control, isotonic design using normalized equivalent toxicity score and escalation with overdose control using normalized equivalent toxicity score.
Select below to download the EWOC software available in ZIP file with text file instructions.
We also offer biostatistics application tools developed for cancer research and intended to equip investigators with tools to enable efficient data mining that will help in formulating a specific research question to then engage resources and others on how best to address it.
Our SAS® macros can be used throughout the entire analysis process from start to finish, including descriptive statistics, bivariate statistics, unadjusted regression, and multiple regression. The macros generate professional looking analysis reports with the goal of condensing the relevant information from a statistical analysis into an understandable format for investigators.
Select below to download the desired SAS® macros available in ZIP file with text file instructions.
| DESCRIPTIVE FINDCUT LINREG SEL LOGREG SEL MPLOT MULTIPLE GENMOD MULTIPLE LINREG MULTIPLE LOGREG |
MULTIPLE PHREG PHREG SEL UNI CAT UNI GENMOD UNI LOGREG UNI NUM UNI PHREG |
The National Cancer Institute requires that publications acknowledge the Winship Cancer Institute Cancer Center Support Grant (CCSG), and it is tracking compliance. If a Winship Cancer Institute CCSG-supported Shared Resource provided data, designed the study, performed analyses, provided results used in your publication, and/or provided any systems or services that were used for the work that resulted in your publication, please include the following statement in the acknowledgment section of your publication(s):
Research reported in this publication was supported in part by the Biostatistics Shared Resource of Winship Cancer Institute of Emory University and NIH/NCI under award number P30CA138292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Winship Cancer Institute of Emory University
Dr. Switchenko collaborates on clinical and genomic study design and analysis, and seeks to apply Bayesian methodology to a wide variety of cancer research projects ranging from cancer prevention and control to genomic studies.
