Training clinical trial sas

BASE SAS MODULES Day 1: Introduction to the SAS System Components of Base SAS Software Output Produced by the SAS System Ways to Run SAS Programs Running Programs in the SAS Windowing Environment Introduction to DATA Step Processing The SAS Data Set introduction How the DATA Step Works: A Basic Introduction Supplying Information to Create a SAS Data Set Introduction to Raw Data Examine the Structure of the Raw Data: Factors to Consider Reading Unaligned Data Reading Data That Is Aligned in Columns Reading Data That Requires Special Instructions Reading Unaligned Data with More Flexibility Mixing Styles of Input Day 2: Introduction to Beyond the Basics with Raw Data Using INFILE statement and various options. Testing a Condition before Creating an Observation Creating Multiple Observations from a Single Record Reading Multiple Records to Create a Single Observation Problem Solving: When an Input Record Unexpectedly Does Not have enough values Day 3: Introduction to Starting with SAS Data Sets Understanding the Basics Input SAS Data Set for Examples Reading Selected Observations Reading Selected Variables Creating More Than One Data Set in a Single DATA Step Using the DROP=, KEEP= and WHERE= Data Set Options for Efficiency Introduction to DATA Step Processing Input SAS Data Set for Examples Adding Information to a SAS Data Set Defining Enough Storage Space for Variables Conditionally Deleting an Observation Day 4: Introduction to Working with Numeric Variables About Numeric Variables in SAS Input SAS Data Set for Examples Calculating with Numeric Variables Comparing Numeric Variables Storing Numeric Variables Efficiently Numeric Functions. Day 5: Introduction to Working with Character Variables Input SAS Data Set for Examples Identifying Character Variables and Expressing Character Values Handling Missing Values Creating New Character Values Saving Storage Space by Treating Numbers as Characters Character Functions Day 6: Introduction to Acting on Selected Observations Input SAS Data Set for Examples Selecting Observations Constructing Conditions Comparing Characters Introduction to Creating Subsets of Observations Input SAS Data Set for Examples Selecting Observations for a New SAS Data Set Conditionally Writing Observations to One or More SAS Data Sets Day 7: Introduction to Working with Grouped or Sorted Observations Input SAS Data Set for Examples Working with Grouped Data Working with Sorted Data Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Day 8: Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Introduction to Working with Dates Understanding How SAS Handles Dates Input File and SAS Data Set for Examples Entering Dates Displaying Dates Using Dates in Calculations Using SAS Date Functions Comparing Durations and SAS Date Values Day 9: Introduction to Combining SAS Data Sets Definition of Concatenating Definition of Interleaving Definition of Merging Definition of Updating Definition of Modifying 237 Comparing Modifying, Merging, and Updating Data Sets Day 10: Introduction to Concatenating SAS Data Sets Concatenating Data Sets with the SET Statement Concatenating Data Sets Using the APPEND Procedure Choosing between the SET Statement and the APPEND Procedure. Introduction to Interleaving SAS Data Sets Understanding BY-Group Processing Concepts Interleaving Data Sets Day 11: Introduction to Merging SAS Data Sets Understanding the MERGE Statement One-to-One Merging Match-Merging Choosing between One-to-One Merging and Match-Merging Introduction to Updating SAS Data Sets Understanding the UPDATE Statement Understanding How to Select BY Variables Updating a Data Set Updating with Incremental Values Understanding the Differences between Updating and Merging Handling Missing Values Day 12: Input SAS Data Set for Examples Modifying a SAS Data Set: The Simplest Case Modifying a Master Data Set with Observations from a Transaction Data Set Understanding How Duplicate BY Variables Affect File Update Handling Missing Values Introduction to Conditional Processing from Multiple SAS Data Sets Input SAS Data Sets for Examples Determining Which Data Set Contributed the Observation Combining Selected Observations from Multiple Data Sets Performing a Calculation Based on the Last Observation Day 13: Introduction to Analysing Your SAS Session with the SAS Log Understanding the SAS Log Locating the SAS Log Understanding the Log Structure Writing to the SAS Log Suppressing Information to the SAS Log Changing the Log’s Appearance Introduction to Directing SAS Output and the SAS Log Input File and SAS Data Set for Examples Routing the Output and the SAS Log with PROC PRINTTO Storing the Output and the SAS Log in the SAS Windowing Environment Redefining the Default Destination in a Batch or Non interactive Environment Introduction to Diagnosing and Avoiding Errors Understanding How the SAS Supervisor Checks a Job Understanding How SAS Processes Errors Distinguishing Types of Errors Diagnosing Errors Using a Quality Control Checklist Day 14: Introduction to Creating Detail and Summary Reports with the REPORT Procedure Understanding How to Construct a Report Input File and SAS Data Set for Examples Creating Simple Reports Creating More Sophisticated Reports Day 15: Introduction to Proc means Deriving descriptive statistics Introduction to Proc univariate and various options Day 16: Introduction to Proc freq Calculating counts using Freq Outputting the counts into a dataset Proc Transpose introduction Using VAR, ID and BY statement efficiently in transpose Reshaping the data with required variables Day 17: Introduction to Producing Charts to Summarize Variables Understanding the Charting Tools Input File and SAS Data Set for Examples Charting Frequencies with the CHART Procedure Customizing Frequency Charts Creating High-Resolution Histograms Day 18: Introduction to Writing Lines to the SAS Log or to an Output File Understanding the PUT Statement Writing Output without Creating a Data Set Writing Simple Text Introduction to the Basics of Understanding and Customizing SAS Output Understanding Output Input SAS Data Set for Examples Locating Procedure Output Making Output Informative Controlling Output Appearance Controlling the Appearance of Pages Representing Missing Values Day 19: Introduction to Customizing SAS Output by Using the Output Delivery System Input Data Set for Examples Understanding ODS Output Formats and Destinations Selecting an Output Format Creating Formatted Output Day 20: Proc Format introduction Creating format catalogue Converting catalogue to dataset Storing formats permanently and finding out formats in a library Accessing a Permanent SAS Data Set with User-Defined Formats ADVANCED SAS MODULES Day 21: Getting Started with the Macro Facility Replacing Text Strings Using Macro Variables Generating SAS Code Using Macros More Advanced Macro Techniques Other Features of the Macro Language Introduction to SAS Programs and Macro Processing How SAS Processes Statements without Macro Activity How SAS Processes Statements with Macro Activity Introduction to Macro Variables Macro Variables Defined by SAS Macro Variables Defined by Users Using Macro Variables Displaying Macro Variable Values Referencing Macro Variables Indirectly Manipulating Macro Variable Values with Macro Functions Introduction to Macro Processing Defining and Calling Macros How the Macro Processor Compiles a Macro Definition How the Macro Processor Executes a Compiled Macro Summary of Macro Processing Day 22: Introduction to the Scopes of Macro Variables Global Macro Variables Local Macro Variables Writing the Contents of Symbol Tables to the SAS Log How Macro Variables Are Assigned and Resolved Introduction to Macro Expressions Defining Arithmetic and Logical Expressions How the Macro Processor Evaluates Arithmetic Expressions Day 23: Introduction to Macro Quoting Deciding When to Use a Macro Quoting Function and Which Function to Use Using Various Macro Functions %STR and %NRSTR Functions etc Using the %BQUOTE and %NRBQUOTE Functions Referring to Already Quoted Variables Deciding How Much Text to Mask with a Macro Quoting Function Using %SUPERQ Summary of Macro Quoting Functions and the Characters They Mask Unquoting Text How Macro Quoting Works Other Functions That Perform Macro Quoting Day 24: Introduction to Storing and Reusing Macros Saving Macros in an Auto call Library Saving Macros Using the Stored Compiled Macro Facility General Macro Debugging Information Troubleshooting Your Macros Debugging Techniques Introduction to Writing Efficient and Portable Macros Keeping Efficiency in Perspective Writing Efficient Macros Writing Portable Macros PROJECT CONTENT COVERED Day Creation of Efficacy tables. Creation of Standard and safety tables. Day 28 Creation of listings Day Creation of Graphs a)Bar Charts b)Scatter plot c)Line plot d)Box plot Day 31 Creation of Analysis datasets/derived datasets Day 32 Introduction to SDTM CRF Annotation (ONLY BASICS) Introduction to mapping specification (ONLY BASICS) Introduction to SDTM dataset Creation (ONLY BASICS) Validation in Open CDISC (ONLY BASICS) Day 33 Introduction to ADAM Standards (ONLY BASICS) Mock interview and providing assistance for interview preparation Contact:

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Clinical SAS: Basics of Clinical Research ICH GCP Guidelines Good programming Practices Use of SAS in Clinical Research Demo project for Clinical trial study

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COVALENT:- Covalent is a group of company which has services and operations in Clinical, Information Technology, Energy, consumer products, Power and Infrastructure. Training @ Covalent We arededicated to establish ourselves as ''A values-driven organization''. These values will continue to direct our growth and organization?s operation. ?Covalent? values supporting the way like ?Kreative?. Clinical SAS (Statistical Analysis Software):- SAS Fundamentals: Getting Started with SAS Working with SAS syntax Getting Familiar with SAS dataset Reading SAS datasets Reading SAS datasets Reading Excel worksheets Reading Delimited Raw data files Validating and cleaning data Manipulating data Combining SAS Datasets Enhancing Report (ODS systems) Summary Reports Controlling Input and Output Summarizing Data Reading Raw Data Files Data Transformations Processing Data iteratively Restructuring a Data set TRANSPOSE Procedure SQL Procedure: Introduction to SQL procedure Basic Queries Displaying Query Results Sub queries SQL Joins Set Operators Creating Tables and views Interfacing SQL with Macro Language Managing Tables Use of SQL in Clinical Trials Macro language (SAS Macro) Macro Variables Macro definitions Data Step and SQL Procedure Macro Programs Use of Macro language in Clinical Research SAS Enterprise Guide Introduction Reading Data from Files Creating Reports Working with Data in the Query Builder Joining Two Data Files Together Training Duration (Classroom/Online): 3-Months/2-Months Training Fee: 20K/25k

COVALENT:- Covalent is a group of company which has services and operations in Clinical, Information Technology, Energy, consumer products, Power and Infrastructure. Training @ Covalent We arededicated to establish ourselves as ''A values-driven organization''. These values will continue to direct our growth and organization’s operation. “Covalent” values supporting the way like “Kreative”. Clinical SAS (Statistical Analysis Software):- SAS Fundamentals: Getting Started with SAS Working with SAS syntax Getting Familiar with SAS dataset Reading SAS datasets Reading SAS datasets Reading Excel worksheets Reading Delimited Raw data files Validating and cleaning data Manipulating data Combining SAS Datasets Enhancing Report (ODS systems) Summary Reports Controlling Input and Output Summarizing Data Reading Raw Data Files Data Transformations Processing Data iteratively Restructuring a Data set TRANSPOSE Procedure SQL Procedure: Introduction to SQL procedure Basic Queries Displaying Query Results Sub queries SQL Joins Set Operators Creating Tables and views Interfacing SQL with Macro Language Managing Tables Use of SQL in Clinical Trials Macro language (SAS Macro) Macro Variables Macro definitions Data Step and SQL Procedure Macro Programs Use of Macro language in Clinical Research SAS Enterprise Guide Introduction Reading Data from Files Creating Reports Working with Data in the Query Builder Joining Two Data Files Together Training Duration (Classroom/Online): 3-Months/2-Months Training Fee: 20K/25k + Taxes Mobile: Website:http://covalentech.com/sas_training.html

COVALENT:- Covalent is a group of company which has services and operations in Clinical, Information Technology, Energy, consumer products, Power and Infrastructure. Training We arededicated to establish ourselves as ''A values-driven organization''. These values will continue to direct our growth and organization’s operation. “Covalent” values supporting the way like “Kreative”. Clinical SAS (Statistical Analysis Software):- SAS Fundamentals: Getting Started with SAS Working with SAS syntax Getting Familiar with SAS dataset Reading SAS datasets Reading SAS datasets Reading Excel worksheets Reading Delimited Raw data files Validating and cleaning data Manipulating data Combining SAS Datasets Enhancing Report (ODS systems) Summary Reports Controlling Input and Output Summarizing Data Reading Raw Data Files Data Transformations Processing Data iteratively Restructuring a Data set TRANSPOSE Procedure SQL Procedure: Introduction to SQL procedure Basic Queries Displaying Query Results Sub queries SQL Joins Set Operators Creating Tables and views Interfacing SQL with Macro Language Managing Tables Use of SQL in Clinical Trials Macro language (SAS Macro) Macro Variables Macro definitions Data Step and SQL Procedure Macro Programs Use of Macro language in Clinical Research SAS Enterprise Guide Introduction Reading Data from Files Creating Reports Working with Data in the Query Builder Joining Two Data Files Together Training Duration (Classroom/Online): 3-Months/2-Months Training Fee: 20K/25k