Enhanced Clinical Data Analysis & Reporting Using S-PLUS 6.2
Presented: November 19, 2003
Speaker: Dr. Michael O'Connell, Director, BioPharmaceutical
Solutions, Insightful Corporation
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Abstract
Data management and analysis of clinical and pre-clinical
studies involves an enormous effort on the part of biostatisticians,
S-PLUS and SAS programmers. There are many FDA-required
studies; and efficient trial design, rigorous statistical
analysis and sound clinical inference are required at all
stages. In addition, substantive regulatory pressures mandate
a validated data management and analysis environment. This
must be maintained in parallel to a creative statistical
and graphical analysis sand-box, that is needed to understand
and demonstrate clinical effects throughout the project
teams. This seminar describes clinical data analysis and
presentation using S-PLUS including:
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Validated analysis. Batch analysis
jobs and scripted error checking of verbose log files.
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Tabular and Graphical Reporting.
Automated analysis and reporting for pre-clinical
(and clinical) studies.
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Advanced Statistical Analysis.
Regression, survival and advanced analysis of clinical
data.
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Improved Clinical Trial Design.
Group sequential clinical design methods.
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Complementing SAS. Providing seamless
statistical analysis and visualization for data managed
and transformed using SAS.
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Knowledge Sharing/Deployment. Advanced
visualization with S+Graphlets and Web-based deployment
through StatServer for improved collaboration and
information sharing between project teams and key
decision-makers.
Learn about the exciting new features in S-PLUS 6.2
for clinical data analysis and reporting.
Michael O'Connell, Ph.D., is director of Biopharmaceutical
Solutions at Insightful Corp. He has more than 15 years experience
in clinical informatics and the health-care statistics arena,
having published more than 30 papers on statistics, data mining
and health-care applications. This has included statistical
methods work in the areas of non-parametric regression, experimental
design, calibration and (generalized linear) mixed models.
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