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This paper presents a simple approach for determining significant decimal places for continuous data collected in mixed form and reporting the appropriate significant decimal places across all data types. PharmaSUG 2012 - Paper CC34 Determining and Reporting Significant Decimal Places for Continuous Data in Mixed Form Gary E. Moore Moore Computing Services Inc. Little Rock Arkansas ABSTRACT Data of mixed precision is common in clinical trials.
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Who needs PharmaSUG 2012 - Paper CC34?
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Pharmaceutical researchers looking for statistical analysis techniques.
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Clinical data managers seeking to improve their reporting methods.
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Statisticians in the Pharma industry interested in industry best practices.
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Students and academics researching pharmaceutical statistics.
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What is PharmaSUG 2012 - Paper CC34?
PharmaSUG 2012 - Paper CC34 is a presentation or paper that was presented at the Pharmaceutical Industry SAS Users Group (PharmaSUG) conference in 2012, focusing on specific methodologies or practices within the pharmaceutical industry, particularly involving SAS programming.
Who is required to file PharmaSUG 2012 - Paper CC34?
Participants or contributors who wish to present their findings or methodologies related to pharmaceutical data analysis using SAS at the PharmaSUG 2012 conference are required to file Paper CC34.
How to fill out PharmaSUG 2012 - Paper CC34?
To fill out PharmaSUG 2012 - Paper CC34, authors need to follow the submission guidelines provided by the conference organizers, which typically include formatting, structure, and content requirements for the paper.
What is the purpose of PharmaSUG 2012 - Paper CC34?
The purpose of PharmaSUG 2012 - Paper CC34 is to share insights, methodologies, and best practices in pharmaceutical data analysis, fostering collaboration and knowledge exchange among professionals in the industry.
What information must be reported on PharmaSUG 2012 - Paper CC34?
Information that must be reported on PharmaSUG 2012 - Paper CC34 includes the authors' names, affiliations, abstract, methodology details, results, and conclusions related to the presented research or application in pharmaceutical data analysis.
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