SAS Online Training: Course contents: Agenda:

Transcription

1 SAS Online Training: Course contents: Agenda: (1) Base SAS (6) Clinical SAS Online Training with Real time Projects (2) Advance SAS (7) Financial SAS Training Real time Projects (3) SQL (8) CV preparation (4) Macros (9) Interview Assistance (5) Clinical SAS(CDISC) (10) SAS Certification Table of Contents: (I) Base SAS: Day 1: Day 2: 1. Introduction to SAS software 1.2 Getting Started With SAS SAS Windows SAS Program Steps Work flow / Project Life Cycle 1.3 SAS Files Dataset Catalogs 2A SAS Libraries 2.1 Exploring SAS Libraries 2.2 Creating and deleting SAS Libraries 2.3 Naming convention SAS Libraries naming Rules SAS files/ dataset naming One & Two level naming 2B Sas programs 2.4 Running a SAS Program 2.5 Canceling Submitted Statements 2.6 Naming Convention SAS dataset naming Rules SAS variable naming Rules 2.7 SAS Data types Character characteristics Numeric (Std & Non Std) characteristics 2.8 SAS Program layout

2 Day 3: Day 4: Day 5: Day6: Day 7: Day 8: 3 Data access 3.1 Creating SAS Datasets Input, Datalines / Cards Entering data directly Input methods List/ Adv_List Input Column input Named input Formatted input Output method 4.1 Infile options - Dealing with missing data 4.2 Reading delimited files/data 4.3 Importing data Infile statement 4.4 Creating Null datasets 4.5 Reading Multiple Records per Observation Single trailing method 4.6 Multiple Observations per Record Double trailing method 5 Formats & Informats Standard and Non standard data 5.1 Date Functions SAS date value Formats and Informats Julian date 5.2 Time Functions SAS Time value Formats and Informats 5.3 DateTime Functions SAS DateTime value Formats and Informats 5.4 Currency/Amount Values SAS Amount values (Normal & Decimal) Formats and Informats 5.5 Formats and Informats Tips 6 User defined formats Creating own format & Informat names 6.1 proc format Value statement Invalue statement 7 Global options Managing the SAS window Environment (Output, Log, Explorer windows) 8 Dataset options 8.1 Set statement

3 8.2 Dataset options Managing the variables and observations Day 9: 9 How SAS works 9.1 Data step processing Compilation Phase Execution Phase Program Data Vector -PDV Automatic Variables in SAS 9.2 Getting Familiar with SAS Datasets Descriptor Portion of a Dataset (Proc Contents) Data Portion of a SAS Dataset Day 10: 10 Import & Export procedures 10.1 Proc Import and Proc Export 10.2 Import Wizard and Export Wizard Importing the data from various kinds of files like notepad, excel, CSV, Access etc into SAS and Exporting the data to various files like notepad, excel, CSV, Access etc Day 11: 11 Character functions Manipulating the character data 11.1 Change the Case of Characters 11.2 Remove Characters from Strings 11.3 Search for Characters 11.4 Extract Parts of Strings 11.5 Join Two or More Strings Together 11.6 Remove Blanks from Strings 11.7 Divide Strings into "Words" 11.8 Compute the Length of Strings 11.9 Count the Number of Letters or Substrings in a String Substitute Letters or Words in Strings Compare Strings Day 12: 12 Numeric functions Manipulating Numeric, Date & Time values Functions like INT, Round, SQRT, LOG, INTCK, PUT, INPUT etc. Extracting date part & time part Day 13: Day 14: 13 Proc Print and Proc Sort 13.1 Print- statements (Var, Label, Id, etc.,) 13.2 Print- Options (Noobs, Double, width, etc.,) 13.3 Sort Sorting the data, removing the duplicates etc., 14 Combining the datasets 14.1 Stacking the datasets 14.2 Interleaving the datasets

4 14.3 Appending the datasets 14.4 Updating the datasets 14.5 Modifying the datasets Day 15: Day 16: Day 17: Day 18: Day 19: 15 Combining the datasets 15.1 Merging One-to-one Merge One-to-many Merge Many-to-one Merge Many-to-Many Merge 15.2 IN Operator Controlling SAS merge 16 Conditional statements & Operators 16.1 Operators Arithmetic Conditional Logical 16.2 Statements Where IF-THEN/ELSE IF-THEN/ELSE- DO 16.3 Creating & Modifying Variables 16.4 Subsetting Data 16.5 Creating Multiple Datasets in A Single Data-step 17 LOOP PROCESSING 17.1 DO Loop-construction 17.2 Nested DO Loops 17.3 Conditional Iterative Processing DO While DO Until 18 Transpose procedure 18.1 Normalization procedure 18.2 Denormalization procedure 18.3 Special options 19 Arrays 19.1 Defining an array and it s process 19.2 Types of Arrays 19.3 Rules for creating the variable and array names 19.4 Creating Variables with Arrays 19.5 Assigning Initial Values

5 19.6 Performing Repetitive Calculations 19.7 Various special functions Day 20: Day 21: Day 22: Day 23: Day 24: Day 25: 20 Proc Freq and proc corr 20.1 Freq: Calculating frequencies & percentages for multiple variables 20.2 Corr: Calculating correlations among variables 21 Proc Means, Proc Summary Calculating descriptive Statistics for multiple variables. 22 Proc Tabulate Creating variety of tabular reports which displays frequencies, percentages & descriptive statistics. 23 Proc Report and Proc Printto Generating reports, creates new variables, applying formats, managing the output. Saving the output window & log window 24 Proc SQL: Introduction to SQL Terminology, Syntax, Statements 24.1 Statements (Create, Select, From, Where, Group by, Having, Order By etc.,) 24.2 Options/ Clauses (*, Feedback, calculated, count, keep, drop etc.,) 24.3 Conditional operators (Contains, Between-and, case, like etc.,) 24.4 set operators (Union, Union all, Intersect, Except) 25 SQL Joins Combing tables and reports the data SIMPLE Join 25.2 CROSS/CARTESIAN Join 25.3 INNER Join 25.4 OUTER Join 25.5 LEFT Join 25.6 RIGHT Join 25.7 FULL Join 25.8 NATURAL Join 25.9 COALESCE Function Comparing SQL and Data step

6 Day 26, 27, 28:Macros 26.1 Creating Macro variables & different types of macro variables 26.2 Creating Macro catalogs using keyword, positional Parameters 26.3 Using multiple procedures in same macro catalog 26.4 Macro programming: %if..%then..%else and %do..%end 26.5 Using loops in macro catalog 26.6 Data interface functions 26.7 Macro interface functions, Debugging macros, Auto call Macros Day 31: Day 32: Day 33: Day 34: Day 35 40: Creating Listings Generating tables Generating tables using Macros ODS (Output delivery system) and Graphs/Figures 34.1 Creating HTML output 34.2 Creating an RTF file 34.3 Creating PDF file 34.4 Creating Excel file 34.5 Proc Template 34.6 Graphs(Gchart, Gplot, SGplot) CDISC standards(sdtm/adam): Overview of the Study Data Tabulation Model (SDTM) Why SDTM? Domain level metadata SDTM classes and Domains Special-purpose datasets The general observation classes Findings about class Trial domains Suppquals Custom domains Variable level metadata Variables and different types of variables Identifier Topic Timing

7 Qualifier Grouping Qualifiers Result Qualifiers Synonym Qualifiers Record Qualifiers Variable Qualifiers Rule Observations ADaM: Types of ADaM datasets