About Data management module

Background

Model-based analyses aim to establish quantitative relationships between different entities. These relationships are inherently data-driven, meaning they can only be as accurate and reliable as the underlying data allows. Consequently, a thorough evaluation of the data is essential before initiating any modeling efforts. Furthermore, data used in these analyses can come in various shapes and forms, following CDISC, software-specific or company-specific standards. Thus, a modeler should be equipped with a tool to perform convenient transitions from one type of data standard to another, visualize different types of data, and scan the data for potential errors and outliers.

Objectives

• CDISC-compliant semi-automatic data processing.
• Visualization of all types of data in different shapes and forms.
• Quality check of the data.

Sections of the module

• Data
• Data quality check
• Continuous data
• Covariates
• Dosing events
• Tables