Clinical SAS Course in Ahmedabad

• Essentials

▪ the SAS programming process

▪ using SAS programming tools

▪ understanding SAS syntax

• Accessing Data

▪ understanding SAS data

▪ accessing data through libraries

▪ importing data into SAS

• Exploring and Validating Data

▪ exploring data

▪ filtering rows

▪ formatting columns

▪ sorting data and removing duplicates

• Preparing Data

▪ reading and filtering data

▪ computing new columns

▪ conditional processing

• Analyzing and Reporting on Data

▪ enhancing reports with titles, footnotes, and labels

▪ creating frequency reports

▪ creating summary statistics reports

• Exporting Results

▪ exporting data

▪ exporting reports

• Using SQL in SAS

▪ using Structured Query Language in SAS

▪ joining tables using SQL in SAS

• Controlling DATA Step Processing

▪ setting up for this course

▪ understanding DATA step processing

▪ directing DATA step output

• Summarizing Data

▪ creating an accumulating column

▪ processing data in groups

• Manipulating Data with Functions

▪ understanding SAS functions and CALL routines

▪ using numeric and date functions

▪ using character functions

▪ using special functions to convert column type

• Creating Custom Formats

▪ creating and using custom formats

▪ creating custom formats from tables

• Combining Tables

▪ concatenating tables

▪ merging tables

▪ identifying matching and nonmatching rows

• Processing Repetitive Code

▪ using iterative DO loops

▪ using conditional DO loops

• Restructuring Tables

▪ restructuring data with the DATA step

▪ restructuring data with the TRANSPOSE procedure

• Array Processing in Data Step

▪ Introduction to table Lookup Techniques

▪ One-Dimensional Arrays

▪ Multidimensional Arrays

▪ Loading a Multidimensional Array from a SAS Data set

▪ Environment and Guiding Principles

▪ Preparing Clinical Trial Data

▪ Classifying Clinical Trial Data

▪ Introduction to Clinical Data Interchange Standards Consortium (CDISC)

▪ Fundamentals of the Study Data Tabulation Model (SDTM)

• The General Observations Class

▪ Interventions Class

▪ Events Class

▪ Findings Class

• Datasets Other than General Observation

Models for Special-Purpose Domains

Trial Design Model (TDM) Datasets

Relationship Datasets

Study Reference Datasets

• Assumptions for Domain Models

• Base SAS Programs for SDTM Conversions

• Building SDTM Datasets

▪ Building the Special-Purpose DM and SUPPDM Domains

▪ Building the AE Events Domain

▪ Building the LB Finding Domain

▪ Fundamentals of ADaM

▪ Subject-Level Analysis Dataset (ADSL)

▪ Basic Data Structure (BDS)

▪ Building the Subject-Level Analysis Dataset (ADSL)

▪ Building the Adverse Events Analysis Dataset (ADAE)

• Introduction

▪ overview of SAS Foundation

▪ course logistics

▪ course data files

▪ introducing the Structured Query Language

• Basic Queries

▪ overview of the SQL procedure

▪ specifying columns

▪ specifying rows

• Displaying Query Results

▪ presenting data

▪ summarizing data

• SQL Joins

▪ introduction to SQL joins

▪ inner joins

▪ outer joins

▪ complex SQL joins

• Subqueries

▪ noncorrelated subqueries

▪ in-line views

• Set Operators

▪ introduction to set operators

▪ the UNION operator

▪ the OUTER UNION operator

▪ the EXCEPT operator

▪ the INTERSECT operator

• Creating Tables and Views

▪ creating tables with the SQL procedure

▪ creating views with the SQL procedure

• Advanced PROC SQL Features

▪ using SQL procedure options

▪ interfacing PROC SQL with the macro language

• Learning More

▪ SAS resources

▪ beyond this course

• Introduction

▪ course logistics

▪ purpose of the macro facility

▪ program flow

• Macro Variables

▪ introduction to macro variables

▪ automatic macro variables

▪ macro variable references

▪ user-defined macro variables

▪ delimiting macro variable references

▪ macro functions

• Macro Definitions

▪ defining and calling a macro

▪ macro parameters

• DATA Step and SQL Interfaces

▪ creating macro variables in the DATA step

▪ indirect references to macro variables

▪ creating macro variables in SQL

• Macro Programs

▪ conditional processing

▪ parameter validation

▪ iterative processing

▪ global and local symbol tables

• Learning More

▪ SAS resources

▪ beyond this course

• Supplemental Materials

▪ program flow

• Use SQL Procedure to create Data sets

▪ Use CREATE TABLE query to create Study Tabulations and Analysis Datasets

▪ Use Join and Union clauses to combine multiple tables

• Use Macro Programming to automate tasks

▪ Create a macro to derive ISO8601 date string from SAS date or datetime component variables

▪ Create a macro to derive SDTM study day variable

▪ Create a macro to calculate change from baseline

• Introduction to Reporting and ODS

▪ Course logistics

▪ Introduction to reporting.

▪ Introduction to ODS.

▪ ODS with the SAS interfaces.

▪ Creating reports with the PRINT procedure

• Getting Started with the TABULATE Procedure

▪ Introduction to the TABULATE procedure.

▪ Creating the structure of the table.

▪ Adding overall summarizations.

▪ Adding additional statistics.

• Doing More with the TABULATE Procedure

▪ Enhancing with labels and formats.

▪ Enhancing with options.

▪ Adding trafficlighting.

▪ Adding additional style attributes.

• Getting Started with the REPORT Procedure

▪ Introduction to the REPORT procedure.

▪ Creating a detail report.

▪ Creating a summary report with the GROUP usage.

▪ Creating a summary report with the ACROSS usage.

▪ Computing an additional column.

• Doing More with the REPORT Procedure

▪ Adding summary lines.

▪ Customizing break lines.

▪ Adding trafficlighting and style attributes.

▪ Using the CALL DEFINE statement.

• Doing More with the REPORT Procedure

▪ Adding summary lines

▪ Customizing break lines.

▪ Adding trafficlighting and style attributes.

▪ Using the CALL DEFINE statement.

• Using ODS Destinations

▪ Introduction to ODS destinations

▪ PRINTER and RTF destinations

▪ CSV and HTML destinations.

▪ Excel and other destinations.

▪ SAS destinations.

• Doing More with ODS

▪ Using ODS options and statements.

▪ Using ODSESCAPECHAR.

▪ Controlling bookmarks and the table of contents.

▪ Using ODS layout

• Introduction to SG Procedures

▪ Introduction to ODS Graphics.

▪ Using the SG procedures.

• Getting Started

▪ Setting up for this course

▪ Data visualization with SAS programming overview.

▪ Layers of a graph.

• SGPLOT Procedure

▪ Introduction

▪ Bar charts.

▪ Dot, line, scatter, and series plots.

▪ Additional basic plots.

▪ Distribution plots.

▪ Fit and confidence plots

• Enhancing Visualization Appearance

▪ Style templates, colors, and fonts.

▪ Group attributes.

▪ Reference lines and text boxes.

▪ Axis appearance.

▪ Legend appearance

▪ User-defined style templates.

▪ Additional statements and examples

• Multi-cell Procedures

▪ Introduction.

▪ SGPANEL procedure

▪ SGSCATTER procedure.

• Additional Procedures

▪ SGPIE procedure.

▪ SGMAP procedure.

• Customizing Visualizations

▪ Introduction to SG annotation.

▪ Drawing space.

▪ LINE and ARROW functions.

▪ TEXT and TEXTCONT functions

▪ SG attribute maps

• More with ODS Graphics

▪ ODS GRAPHICS and destination statements.

▪ ODS layout.

▪ Statistical procedures.

• Graph Template Language

▪ Introduction.

▪ Graph Template Language syntax

▪ Dynamic and macro variables.

▪ Creating Tables

▪ Creating Listings

▪ Output Appearance Options

▪ Common Clinical Trial Graphs

▪ Exporting Data

▪ Define.XML for CDISC SDTM

▪ Define.XML for CDISC ADaM

▪ Programming Considerations

▪ Reviewing Programming Log

▪ Using SAS Programming Procedures for Data Validation

▪ Generate descriptive statistics and explore data with graphs.

▪ Perform analysis of variance and apply multiple comparison techniques

▪ Perform linear regression and assess the assumptions.

▪ Use regression model selection techniques to aid in the choice of predictor variables in multiple regression.

▪ Use diagnostic statistics to assess statistical assumptions and identify potential outliers in multiple regression.

▪ Use chi-square statistics to detect associations among categorical variables.

▪ Fit a multiple logistic regression model.

▪ Score new data using developed models.

This course is mapped to TWO credentials as below:

1. SAS Certified Specialist: Base Programming Using SAS 9.4

2. SAS Certified Professional: Clinical Trials Programming Using SAS 9.4

Participants will be awarded SAS certified digital badges for these on clearing respective SAS exams

Besides participants will also be awarded participation certificate & Learn SAS digital badges for –

1. SAS Programming 1: Essentials

2. SAS Programming 2: Data Manipulation Techniques

3. SAS SQL1: Essentials

4. SAS Macro Language 1: Essentials

5. SAS Report Writing

6. Data Visualization Using SAS ODS Graphics

7. SAS Programming for Clinical Trials

8. Data Analysis and Reporting for Clinical Trials