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This document is a tutorial on using the SAS hash object, outlining its advantages over traditional methods like DATA step merges and SQL joins. It introduces key concepts, methods for creating and
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How to fill out PharmaSUG 2010- Paper TU02

01
Start by gathering all necessary data and materials related to your analysis.
02
Review the guidelines provided by PharmaSUG for submitting papers.
03
Outline the main sections of your paper, including introduction, methodology, results, and conclusion.
04
Write the introduction, stating the objectives and importance of your analysis.
05
Detail your methodology in a clear and concise manner, including statistical methods and software used.
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Present your results with appropriate visuals like graphs and tables to enhance understanding.
07
Interpret your results and discuss their implications in the conclusion section.
08
Follow the formatting requirements as specified by PharmaSUG, including citation style.
09
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Submit your paper through the designated submission portal before the deadline.

Who needs PharmaSUG 2010- Paper TU02?

01
Data scientists and statisticians working in the pharmaceutical industry.
02
Researchers looking to present their findings at PharmaSUG conferences.
03
Professionals seeking to enhance their knowledge in SAS programming.
04
Students studying related fields who want to learn about data analysis and presentation.
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PharmaSUG 2010- Paper TU02 is a presentation from the PharmaSUG 2010 conference that discusses statistical programming topics relevant to the pharmaceutical industry.
Individuals involved in statistical programming, clinical data management, and regulatory submissions within the pharmaceutical industry may be interested in the content of Paper TU02.
The paper provides guidance on statistical programming best practices and methodologies; specific instructions for filing are typically not provided as it is a presentation material.
The purpose of Paper TU02 is to share insights, methodologies, and innovations related to statistical programming that can enhance the work of professionals in the pharmaceutical sector.
The paper discusses various topics including statistical analyses, programming techniques, and regulatory compliance information, relevant to clinical trial data.
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