Clinical SAS Online Training | SDTM subclass of Qualifier Variables

 Qualifier variables describe the results of an observation with text or numeric values.it is divided into 5 subclass which are listed below

1.Grouping Qualifiers—These are used to group together a collection of observations within the same domain.

2. Synonym Qualifier—- It specify the alternative name of a particular variables.

3. Result qualifier— It describes the specific result associated with the topic variable for a finding.it is the answer to the question raised by the topic variable.

4. Variable qualifier– These are used to further modify or describe a specific variable within an observation and it only meaningful in the context of the variable if they qualify.

5. Record qualifier-it defines the additional attributes of the observations.



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  1. Durga Online SAS Course, Power BI Trainer India29 February 2024 at 19:03


    What are the main differences between SQL and other programming languages used in data analysis and data science?
    SQL (Structured Query Language) is a specialised language designed for maintaining and querying relational databases. It distinguishes itself from general-purpose programming languages like Python or R, which are often used in data analysis and data science, in numerous ways:

    SQL is declarative, indicating which data to access or manipulate, whereas Python and R are procedural, indicating how to carry out tasks.
    SQL is focused on database operations (such as SELECT, INSERT, and UPDATE), but Python and R provide a broader variety of data manipulation, analysis, and visualisation capabilities.

    SQL is designed for working with structured data, particularly in relational databases, but Python and R are more adaptable and can handle a wide range of data types and structures.
    SQL is domain-specific and designed for database administration, whereas Python and R are general-purpose.

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