Course content

Overview:

SAS (Statistical Analysis System) is the statistical and information system that performs data management and statistical analysis. The system’s analysis tools range from simple descriptive statistics Level to advanced statistical design. It is made up of a number of modules with specialized procedures for analysis relating to various disciplines. The main functionalities of its components are intended to be accessed via application programming interfaces, in the form of statements and procedures.

Training Objectives of SAS:

SAS is one of the premier data analysis software in the market. It utilizes a specialized data set table proprietary to SAS, however it’s System has modules to be able to read and write to many other data base products like Oracle and ODBC compliant products like MS-SQL Server or PROGRESS. The data presentation capabilities range from simple lists and tables to multi dimensional plots and high-resolution graphics.

Target Students / Prerequisites:

Students must be belonging to Technical Background and familiar with Programming Skills.

  • INTRODUCTION
  • NEED FOR SAS
  • WHO USES SAS
  • WHAT IS SAS?
  • OVERVIEW OF BASE SAS SOFTWARE
  • DATA MANAGEMENT FACILITY
  • STRUCTURE OF SAS DATASET
  • SAS PROGRAM
  • PROGRAMMING LANGUAGE
  • ELEMENTS OF THE SAS LANGUAGE
  • RULES FOR SAS STATEMENTS
  • RULES FOR MOST SAS NAMES
  • SPECIAL RULES FOR VARIABLE NAMES
  • TYPES OF VARIABLES
  • DATA ANALYSIS AND REPORTING UTILITIES
  • TRADITIONAL OUTPUT
  • WAYS TO RUN SAS PROGRAMS
  • SAS WINDOWING ENVIRONMENT
  • NONINTERACTIVE MODE
  • BATCH MODE
  • INTERACTIVE LINE MODE
  • RUNNING PROGRAMS IN THE SAS WINDOWING ENVIRONMENT
  • WRITING YOUR FIRST SAS PROGRAM
  • A SIMPLE PROGRAM TO READ RAW DATA AND PRODUCE A REPORT
  • ENHANCING THE PROGRAM
  • MORE ON COMMENT STATEMENTS
  • INTERNAL PROCESSING IN SAS
  • HOW SAS WORKS
  • THE COMPILATION PHASE
  • THE EXECUTION PHASE
  • PROCESSING A DATA STEP: A WALKTHROUGH
  • CREATING THE INPUT BUFFER AND THE PROGRAM DATA VECTOR
  • WRITING AN OBSERVATION TO THE SAS DATA SET
  • FOUR TYPES OF SAS LIBRARIES
  • SAS LIBRARIES
  • WORK LIBRARY
  • SASHELP LIBRARY
  • SASUSER LIBRARY
  • WHAT IS RAW DATA
  • DEFINITIONS
  • DATA VALUES
  • NUMERIC VALUE
  • CHARACTER VALUE
  • STANDARD DATA
  • NONSTANDARD DATA
  • NUMERIC DATA
  • CHARACTER DATA
  • CHOOSING AN INPUT STYLE
  • LIST INPUT
  • MODIFIED LIST INPUT
  • COLUMN INPUT
  • FORMATTED INPUT
  • NAMED INPUT
  • INSTREAM DATA
  • CREATING MULTIPLE RECORDS FROM SINGLE INPUT ROW
  • READING DATA FROM EXTERNAL FILES
  • READING BLANK SEPARATED VALUES (LIST OR FREE FORM DATA):
  • READING RAW DATA SEPARATED BY COMMAS (.CSV FILES):
  • READING IN RAW DATA SEPARATED BY TABS (.TXT FILES):
  • USING INFORMATS WITH LIST INPUT
  • SUPPLYING AN INFORMAT STATEMENT WITH LIST INPUT
  • USING LIST INPUT WITH EMBEDDED DELIMITERS
  • READING RAW DATA THAT ARE ALIGNED IN COLUMNS:
  • METHOD 1: COLUMN INPUT
  • METHOD 2: FORMATTED INPUT
  • USING MORE THAN ONE INPUT STATEMENT: THE SINGLE TRAILING @
  • READING COLUMN DATA THAT IS ON MORE THAN ONE LINE
  • MIXED-STYLE INPUT:
  • INFILE OPTIONS FOR SPECIAL SITUATIONS
  • FLOWOVER
  • MISSOVER
  • TRUNCOVER
  • PAD
  • USING LRECL TO READ VERY LONG LINES OF RAW DATA
  • CHECKING YOUR DATA AFTER IT HAS BEEN READ INTO SAS
  • INTRODUCTION
  • SET STATEMENT OVERVIEW
  • AUTOMATIC VARIABLES IN SAS
  • INTERLEAVE MULTIPLE SAS DATA SETS
  • COMBINE MULTIPLE SAS DATA SETS
  • CREATING & MODIFYING VARIABLES
  • CREATING MULTIPLE DATASETS IN A SINGLE DATA-STEP
  • SUBSETTING OBSERVATIONS
  • CONDITIONAL SAS STATEMENTS
  • LOGICAL AND SPECIAL OPERATORS
  • THE SAS SUPERVISOR AND THE SET STATEMENT
  • EFFICIENCY AND THE SET STATEMENT
  • KNOW YOUR DATA
  • SET STATEMENT DATA SET OPTIONS
  • DROP AND KEEP OPTIONS
  • RENAME OPTION
  • FIRSTOBS AND OBS OPTIONS
  • IN OPTION –
  • WHERE OPTION –
  • OTHER SET STATEMENT OPTIONS
  • END OPTION
  • NOBS OPTION
  • POINT OPTION
  • DO LOOPS AND THE SET STATEMENT
  • INTRODUCTION TO RETAIN STATEMENT
  • CARRY OVER VALUES FROM ONE OBSERVATION TO ANOTHER
  • COMPARE VALUES ACROSS OBSERVATIONS
  • ASSIGN INITIAL VALUES
  • DETERMINING COLUMN ORDER IN OUTPUT DATASET
  • SAS SYSTEM OPTIONS
  • INPUT SAS DATA SET FOR EXAMPLE
  • SELECTING OBSERVATIONS FOR A NEW SAS DATA SET
  • DELETING OBSERVATIONS BASED ON A CONDITION
  • ACCEPTING OBSERVATIONS BASED ON A CONDITION
  • COMPARING THE DELETE AND SUBSETTING IF STATEMENTS
  • METHODS OF CREATING NEW DATA SETS WITH A SUBSET
  • SUBSETTING RECORDS FROM AN EXTERNAL FILE WITH A SUBSETTING IF STATEMENT
  • SUBSETTING OBSERVATIONS IN A DATA STEP WITH A WHERE STATEMENT
  • SUBSETTING OBSERVATIONS IN A PROC STEP WITH A WHERE STATEMENT
  • SUBSETTING OBSERVATIONS IN PROC SQL
  • DIFFERENCE BETWEEN IF AND WHERE
  • OVERVIEW
  • USING SAS INFORMATS
  • INPUT STATEMENT
  • INPUT FUNCTION
  • INPUTN AND INPUTC FUNCTIONS
  • ATTRIB AND INFORMAT STATEMENTS
  • USING SAS FORMATS
  • FORMAT STATEMENT IN PROCEDURES
  • PUT STATEMENT
  • PUT FUNCTION
  • PUTN AND PUTC FUNCTIONS
  • Format
  • ADDITIONAL COMMENTS
  • CATEGORIES OF FUNCTIONS
  • SAS CHARACTER FUNCTIONS
  • FUNCTIONS THAT CHANGE THE CASE OF CHARACTERS
  • UPCASE
  • LOWCASE
  • PROPCASE
  • FUNCTIONS THAT REMOVE CHARACTERS FROM STRINGS
  • FUNCTION: COMPBL
  • FUNCTION: COMPRESS
  • FUNCTIONS THAT SEARCH FOR CHARACTERS
  • FUNCTION: ANYALNUM
  • FUNCTION: ANYALPHA
  • FUNCTION: ANYDIGIT
  • FUNCTION: ANYPUNCT
  • FUNCTION: ANYSPACE
  • FUNCTION: NOTALNUM
  • FUNCTION: NOTALPHA
  • FUNCTION: NOTDIGIT
  • FUNCTION: NOTUPPER
  • FUNCTIONS THAT SEARCH STRINGS
  • FIND AND FINDC
  • INDEX, INDEXC, AND INDEXW
  • FUNCTIONS TO VERIFY DATA
  • FUNCTION VERIFY
  • FUNCTIONS THAT EXTRACT PARTS OF STRINGS
  • FUNCTION: SUBSTR (ON THE LEFT-HAND SIDE OF THE EQUAL SIGN)
  • FUNCTION: SUBSTRN
  • FUNCTIONS THAT JOIN TWO OR MORE STRINGS TOGETHER
  • FUNCTION: CAT
  • FUNCTION: CATS
  • FUNCTION: CATT
  • FUNCTION: CATX
  • FUNCTIONS THAT REMOVE BLANKS FROM STRINGS
  • FUNCTION: LEFT
  • FUNCTION: RIGHT
  • FUNCTION: TRIM
  • FUNCTION: TRIMN
  • FUNCTION: STRIP
  • FUNCTIONS THAT COMPARE STRINGS
  • FUNCTION: COMPARE
  • FUNCTIONS THAT DIVIDE STRINGS INTO “WORDS”
  • FUNCTION: SCAN
  • FUNCTION: SCANQ
  • FUNCTIONS THAT SUBSTITUTE LETTERS OR WORDS IN STRINGS
  • FUNCTION: TRANSLATE
  • FUNCTION: TRANWRD
  • FUNCTIONS THAT COMPUTE THE LENGTH OF STRINGS
  • FUNCTION: LENGTH
  • FUNCTION: LENGTHC
  • FUNCTION: LENGTHM
  • FUNCTION: LENGTHN
  • FUNCTIONS THAT COUNT THE NUMBER OF LETTERS OR SUBSTRINGS IN A STRING
  • FUNCTION: COUNT
  • FUNCTION: COUNTC
  • MISCELLANEOUS STRING FUNCTIONS
  • FUNCTION: MISSING
  • FUNCTION: REPEAT
  • FUNCTION: REVERSE
  • SAS DATE AND TIME FUNCTIONS
  • INTRODUCTION
  • WHAT IS A SAS DATE AND TIME LITERAL?
  • DATE AND TIME FUNCTIONS
  • FUNCTINS TO CREATE DATE AND TIME VALUES
  • FUNCTIONS TO TAKIE DATETIME VALUES APART
  • FUNCTIONS TO GET QUARTER ,YEAR OR DAY OF THE DATE
  • FUNCTIONS THAT WORK WITH INTERVALS
  • USING FORMATS FOR DATE AND TIME
  • SYSTEM OPTIONS FORDATE AND TIME
  • WHY DO WE NEED ARRAYS?
  • BASIC ARRAY CONCEPTS
  • ARRAY STATEMENT
  • ARRAY REFERENCES
  • VARIABLE NAME ARRAY REFERENCE
  • USING ARRAY INDEXES
  • ONE DIMENSION ARRAYS
  • MULTI-DIMENSION ARRAYS
  • TEMPORARY ARRAYS
  • SORTING ARRAYS
  • Determining Array Bounds: LBOUND and HBOUND Functions
  • WHEN TO USE ARRAYS
  • COMMON ERRORS AND MISUNDERSTANDINGS
  • INVALID INDEX RANGE
  • FUNCTION NAME AS AN ARRAY NAME
  • ARRAY REFERENCED IN MULTIPLE DATA STEPS, BUT DEFINED IN ONLY ONE
  • DEFINITIONS FOR BY-GROUP PROCESSING
  • BY-GROUP PROCESSING
  • BY VALUE
  • BY GROUP
  • VARIABLE AND LAST.VARIABLE
  • MODIFYING SAS DATA SETS: EXAMPLES.
  • INVOKING BY-GROUP PROCESSING
  • PREPROCESSING INPUT DATA FOR BY-GROUP PROCESSING
  • SORTING OBSERVATIONS FOR BY-GROUP PROCESSING
  • INDEXING FOR BY-GROUP PROCESSING
  • HOW THE DATA STEP IDENTIFIES BY GROUPS
  • PROCESSING OBSERVATIONS IN A BY GROUP
  • HOW SAS DETERMINES FIRST.VARIABLE AND LAST.VARIABLE
  • PROCESSING BY-GROUPS IN THE DATA STEP
  • OVERVIEW
  • PROCESSING BY-GROUPS CONDITIONALLY
  • DATA NOT IN ALPHABETIC OR NUMERIC ORDER
  • DATA GROUPED BY FORMATTED VALUES
  • DEFINITIONS
  • CONCATENATING
  • INTERLEAVING
  • ONE-TO- ONE READING OR ONE-TO-ONE MERGING
  • MATCH-MERGING
  • UPDATING
  • MODIFYING
  • DEFINITIONS FOR READING, COMBINING, AND MODIFYING SAS DATA SETS
  • READING A SAS DATA SET
  • COMBINING SAS DATA SETS
  • MODIFYING SAS DATA SETS
  • OVERVIEW OF TOOLS
  • READING SAS DATA SETS
  • READING A SINGLE SAS DATA SET
  • READING FROM MULTIPLE SAS DATA SETS
  • COMBINING SAS DATA SETS: BASIC CONCEPTS
  • ONE-TO-ONE
  • ONE-TO-MANY AND MANY-TO-ONE
  • MANY-TO-MANY
  • ACCESS METHODS: SEQUENTIAL VERSUS DIRECT
  • SEQUENTIAL ACCESS
  • DIRECT ACCESS
  • ONE-TO-ONE READING
  • DATA STEP PROCESSING DURING A ONE-TO-ONE READING
  • ONE-TO-ONE MERGING
  • MATCH-MERGING
  • UPDATING WITH THE UPDATE AND THE MODIFY STATEMENTS :
  • DEFINITIONS
  • SYNTAX OF THE UPDATE STATEMENT
  • SYNTAX OF THE MODIFY STATEMENT –
  • UPDATING WITH NONMATCHED OBSERVATIONS, MISSING VALUES, AND NEW VARIABLES –
  • USING AN INDEX WITH THE MODIFY STATEMENT
  • INTRODUCTION
  • THE ANATOMY OF A PROC
  • THE PROC STATEMENT
  • TITLE AND FOOTNOTE STATEMENTS
  • BY STATEMENT
  • LABEL STATEMENT
  • FORMAT STATEMENT
  • RUN OR QUIT STATEMENT
  • DESCRIPTION OF DATA USED IN REPORTS
  • SAS REPORTING PROCEDURES
  • PROCS FOR ALL THAT DETAIL
  • USING PROC PRINT
  • USING PROC SQL
  • PROC REPORT
  • PROCS THAT SUMMARIZE
  • USING PROC CHART
  • USING PROC FREQ
  • USING PROC MEANS
  • USING PROC UNIVARIATE
  • INTRODUCTION TO PROC TABULATE
  • DATA MANIPULATION AND MANAGEMENT PROCEDURE
  • PROC SORT
  • PROC DATASETS
  • PROC FORMAT
  • PROC CONTENTS
  • OTHER IMPORTANT PROCS
  • PROC TRANSPOSE
  • DEFINITIONS
  • PROC PRINTTO
  • COMPARE PROCEDURE
  • PROC APPEND
  • HOW TO IMPORT AN EXCEL FILE INTO SAS
  • INTRODUCTION
  • WHY LEARN PROC SQL?
  • SELECT STATEMENT
  • THE SELECT STATEMENT SYNTAX
  • A SIMPLE PROC SQL
  • A COMPLEX PROC SQL
  • LIMITING INFORMATION ON THE SELECT
  • CREATING NEW VARIABLES
  • THE CALCULATED OPTION ON THE SELECT
  • USING LABELS AND FORMATS
  • THE CASE EXPRESSION ON THE SELECT
  • ADDITIONAL SELECT STATEMENT CLAUSES
  • REMERGING
  • REMERGING FOR TOTALS
  • CALCULATING PERCENTAGE
  • SORTING THE DATA IN PROC SQL
  • SORT ON NEW COLUMN
  • SUBSETTING USING THE WHERE
  • INCORRECT WHERE CLAUSE
  • WHERE ON COMPUTED COLUMN
  • SELECTION ON GROUP COLUMN
  • USE HAVING CLAUSE
  • CREATING NEW TABLES
  • JOINING DATASETS USING PROC SQL
  • INNER JOIN
  • JOINING THREE OR MORE TABLES
  • OUTER JOINS
  • INCLUDING NONMATCHING ROWS WITH THE RIGHT OUTER JOIN
  • SELECTING ALL ROWS WITH THE FULL OUTER JOIN
  • CONCATENATING QUERY RESULTS
  • INTRODUCTION
  • SAS MACRO OVERVIEW
  • TRADITIONAL SAS PROGRAMMING
  • THE SAS MACRO LANGUAGE
  • MACRO LANGUAGE COMPONENTS
  • MACRO VARIABLES
  • MACRO STATEMENTS
  • MACRO PROCESSOR FLOW
  • AUTOMATIC MACRO VARIABLES
  • MACRO DEBUGGING OPTIONS
  • WHAT IS A MACRO?
  • DEFINING AND USING MACROS
  • POSITIONAL MACRO PARAMETERS
  • KEYWORD MACRO PARAMETERS
  • CONDITIONAL MACRO COMPILATION
  • THE %DO STATEMENT
  • SAS DATA STEP INTERFACES
  • INTRODUCTION
  • CREATING VARIOUS TYPES OF REPORTS LISTING OUTPUT
  • OTHER DESTINATIONS
  • HTML
  • PDF AND POSTSCRIPT
  • RTF FILES
  • MICROSOFT EXCEL
  • ADDING STYLE TO YOUR REPORTS
  • LOCATE EXISTING STYLES
  • ODS STYLE= OPTION
  • CUSTOMIZE YOUR REPORTS
  • ODS SELECT; AND ODS EXCLUDE;
  • OTHER CUSTOMIZATIONS
  • ODS PROCLABEL= ;
  • ODS PROCTITLE; AND ODS NOPROCTITLE;
  • ADVANCED TECHNIQUES
  • ODS DOCUMENT
  • PROC TEMPLATE
  • INTRODUCTION
  • UNDERSTANDING HOW THE SAS SUPERVISOR CHECKS A JOB
  • UNDERSTANDING HOW SAS PROCESSES ERRORS
  • DISTINGUISHING TYPES OF ERRORS .SAS RECOGNIZES FOUR KINDS OF ERRORS:
  • SYNTAX ERRORS
  • EXECUTION-TIME ERRORS
  • DATA ERRORS
  • SEMANTIC ERRORS
  • DIAGNOSING ERRORS
  • DIAGNOSING SYNTAX ERRORS
  • DIAGNOSING DATA ERRORS
  • USING A QUALITY CONTROL CHECKLIST
  • SAS role in Clinical Research
  • Project Management in Clinical Research
  • What is Clinical Research
  • What is Protocol and role of Protocol in Clinical Research?
  • What is randomization and non randomization?
  • Which is playing main role in Clinical Research?
  • What is SOP (Standard Operating Procedure)
  • Importance of CDM systems for data loading
  • What is SAP (Statistical Analysis Plan)?
  • Role of SAP in Clinical Research
  • SAS Work Flow in Clinical Research
  • Relation between SAS and DBMS
  • Interaction between SAS with CDMs for data access
  • Various report generation in Clinical Research
  • INTRODUCTION TO CLINICAL DOMAIN
  • DATA ACCESSING
  • DATA VALIDATION
  • DATA CLEANSING
  • PREPARING ANALYSIS DATASETS
  • DATA ANALYSIS
  • DATA PRESENTATION
  • REPORT VALIDATION
  • PRACTICAL APPLICATION WITH PROJECT

Mode of Training

Online

Total duration of the course

5 to 7 weeks

Training duration per day

50 mins - 90 mins

Communication Mode

Go to meeting, WEB-EX

Software access:

Software will be installed/Server access will be provided, whichever is possible

Material

Soft copy of the material will be provided during the training.

Training

Both weekdays and weekends

Training Fee

 $500