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Using R Programming for Clinical Trial Data Analysis
by Clinical Programming Team
publish date icon October 27, 2020

Using R Programming for Clinical Trial Data Analysis

Create Tables, Listings and Figures (TFLs) using R Programming in your clinical trial data analysis, not as a replacement for, but rather as an alternative option to SAS.

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The History and Development of Pinnacle 21
by Clinical Programming Team
publish date icon October 16, 2020

The History and Development of Pinnacle 21

Pinnacle 21 has evolved and knowledge of its software has become an indispensable skill of every statistical programmer who works with CDISC standards.

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Big SAS Code: How to Handle Large Programs
by Clinical Programming Team
publish date icon December 11, 2019

Big SAS Code: How to Handle Large Programs

Quanticate explores how a big SAS code can be made straightforward and easy to understand, with techniques and best practices to achieve this in your SAS programs.

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Subject: Sending Emails using VBA and SAS
by Clinical Programming Team
publish date icon July 22, 2019

Subject: Sending Emails using VBA and SAS

Quanticate provide a step-by-step guide on how to send emails using SAS and Visual Basic for Applications (VBA), as well as a combination of both.

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Creating your own interactive dashboards in SAS
by Clinical Programming Team
publish date icon June 17, 2019

Creating your own interactive dashboards in SAS

Can you easily create your own interactive dashboards in SAS? In this blog, Quanticate will explore whether SAS 4GL is all you need!

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WARNING: Transposing Data using PROC SQL
by Clinical Programming Team
publish date icon June 13, 2019

WARNING: Transposing Data using PROC SQL

Quanticate outlines the in-depth problems of transposing data using PROC SQL and how tree traversal can be understood and implemented in SAS.

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Machine Learning in the Pharmaceutical Industry
by Clinical Programming Team
publish date icon May 21, 2019

Machine Learning in the Pharmaceutical Industry

Quanticate explores what Machine Learning is and the three types of Machine Learning and real-life examples from the pharmaceutical industry.

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