SAS Clinical Master Program

·       Lecture-1 Generate detail reports in SQL

·       Use PROC SQL to perform SQL queries.

·       Select columns in a table with a SELECT statement and FROM clause.

·       Create a table from a query result set.

·       Create new calculated columns.

·       Assign an alias with the AS keyword.

·       Use case logic to select values for a column.

·       Retrieve rows that satisfy a condition with a WHERE clause.

·       Subset data by calculated columns.

·       Join tables - inner joins, full joins (coalesce function), right joins, left joins.

·       Combine tables using set operators - union, outer union, except, intersect.

·       Sort data with an ORDER BY clause.

·       Assign labels and formats to columns.

·       Lecture-2 Generate summary reports in the SQL.

·       Summarize data across and down columns using summary functions (AVG, COUNT, MAX, MIN, SUM).

·       Group data using GROUP BY clause.

·       Filter grouped data using HAVING clause.

·       Eliminate duplicate values with the DISTINCT keyword.

·       Lecture-3 Construct sub-queries and in-line views.

·       Subset data by using non-correlated subqueries.

·       Reference an in-line view with other views or tables (multiple tables).

·       Lecture-4 Use SAS SQL procedure enhancements.

·       Use SAS data set options with PROC SQL (KEEP=, DROP=, RENAME=, OBS=).

·       Use PROC SQL invocation options (INOBS=, OUTOBS=. NOPRINT, NUMBER)

·       Use SAS functions (SCAN, SUBSTR, LENGTH).

·       Access SAS system information by using DICTIONARY tables (members, tables, columns)

·       Use the CALCULATED keyword.

·       Lecture-5 Uuse user-defined and automatic macro variables

·       Use macro variable name delimiter. (.)

·       Use INTO clause of the SELECT statement in SQL to create a single variable or a list of variables.

·       Use the SYMPUTX routine in a DATA Step to create a single variable or a list of variables.

·       Control variable scope

·       Lecture-6 Automate programs by defining and calling macros.

·       Define a macro using the %MACRO and %MEND statements.

·       Calling a macro with and without parameters.

·       Document macro functionality with comments

·       Generate SAS Code conditionally by using the %IF-%THEN-%ELSE macro statements or iterative %DO statements.

·       Use the SAS AUTOCALL facility to permanently store and call macros.

·       Lecture-7 Use macro functions.

·       Use macro functions. (%SCAN, %SUBSTR, %UPCASE)

·       Use macro quoting functions. (%NRSTR, %STR)

·       Use macro evaluation functions. (%SYSEVALF)

·       Use %SYSFUNC to execute DATA step functions within the SAS Macro Language.

·       Lecture-8 Debug macros.

·       Trace the flow of execution with the MLOGIC option.

·       Examine the generated SAS statements with the MPRINT option.

·       Examine macro variable resolution with the SYMBOLGEN option.

·       Use the %PUT statement to print information to the log.

·       Lecture-9 Data-driven programs using SAS Macro Language.

·       Create a series of macro variables.

·       Use indirect reference to macro variables. (&&, etc.)

·       Incorporate DICTONARY tables in data driven macros.

·       Generate repetitive macro calls.

·       Lecture-10 Process data using 1 and 2 dimensional arrays.

·       Define and use character arrays.

·       Define and use numeric arrays.

·       Create variables with arrays.

·       Reference arrays within a DO loop.

·       Specify the array dimension with the DIM function.

·       Define arrays as temporary arrays.

·       Load initial values for an array from a SAS data set.

·       Lecture-11 Process data using hash objects.

·       Declare hash and hash iterator objects

·       Dataset argument

·       Ordered argument

·       Multidata argument

·       Use hash object methods

·       definekey()

·       definedata()

·       definedone()

·       find()

·       add()

·       output()

·       Use hash iterator object methods

·       first()

·       next()

·       last()

·       prev()

·       Use hash objects as lookup tables.

·       Use hash objects to create sorted data sets.

·       Use hash iterator objects to access data in forward or reverse key order.

·       Lecture-12 Use SAS utility procedures.

·       Specify a template using the PICTURE statement within the FORMAT Procedure*

·       Specify templates for date, time, and datetime values using directives.

·       Specify templates for numeric values using digit selectors.

·       PICTURE statement options: round, default, datatype, multiplier, prefix

·       Create custom functions with the FCMP procedure

·       Create character and numeric custom functions with single or multiple arguments.

·       Create custom functions based on conditional processing.

·       Use custom functions with the global option CMPLIB=.

·       Lecture-13 Use advanced functions.

·       Finding strings or words with the FINDC/FINDW functions.

·       Counting strings or words with the COUNT/COUNTC/COUNTW functions.

·       Retrieve previous values with the LAG function.

·       Regular expression pattern matching with PRX functions

·       Lecture-1 Fundamentals of Trial Design

·       Randomized Clinical Trials

·       Uncontrolled Trials

·       Protocol Development

·       Endpoints

·       Patient Selection

·       Source and Control of Bias

·       Randomization

·       Blinding

·       Sample Size and Power

·       Practical Exercise

·       Lecture-2 Alternative Trial Designs

·       Crossover Trials

·       Factorial Design

·       Equivalence Trials

·       Bioequivalence Trials

·       Noninferiority Trials

·       Cluster Randomized Trials

·       Multicenter Trials

·       Practical Exercise

·       Lecture-3 Basics of Statistical Analysis

·       Types of Data and Normal Distribution

·       Significance Tests and Confidence Intervals

·       Comparison of Means

·       Comparison of Proportions

·       Analysis of Survival Data  235

·       Practical Exercise

·       Lecture-4 Special Trial Issues In Data Analysis

·       Intention-to-Treat Analysis

·       Subgroup Analysis

·       Regression Analysis

·       Adjustment for Covariates

·       Confounding

·       Interaction

·       Repeated Measurements

·       Multiplicity

·       Missing Data

·       Interim Monitoring and Stopping Rules

·       Practical Exercise

·       Lecture-5 Reporting of Trials

·       Overview of Reporting

·       Trial Profile

·       Presenting Baseline Data

·       Use of Tables

·       Use of Figures

·       Critical Appraisal of a Report

·       Meta-Analysis

·       Practical Exercise

·       Lecture-6 Environment and Guiding Principles

·       Preparing and Classifying Clinical

·       Importing Data

·       Transforming Data and Creating Analysis

·       Creating Tables and Listings

·       Creating Tables

·       General Approach to Creating Tables

·       Using PROC TABULATE to Create Clinical Trial Tables

·       Using PROC REPORT to Create Clinical Trial Tables

·       Creating Continuous/Categorical Summary Tables

·       Creating Adverse Event Summaries

·       Creating Concomitant or Prior Medication Tables

·       Creating a Laboratory Shift Table

·       Practical Exercise

·       Lecture-7 Creating Clinical Trial Graphs

·       Common Clinical Trial Graphs

·       Scatter Plot

·       Line Plot

·       Bar Chart

·       Box Plot

·       Odds Ratio Plot

·       Kaplan-Meier Survival Estimates Plot

·       Practical Exercise

·       Lecture-8 Performing Common Analyses and Obtaining

·       Statistics

·       Obtaining Descriptive Statistics

·       Using PROC FREQ to Export Descriptive Statistics

·       Using PROC UNIVARIATE to Export Descriptive Statistics

·       Obtaining Inferential Statistics from Categorical Data Analysis

·       Performing a 2x2 Test for Association

·       Performing an NxP Test for Association

·       Performing a Stratified NxP Test for Association

·       Performing Logistic Regression

·       Obtaining Inferential Statistics from Continuous Data Analysis

·       Performing a One-Sample Test of the Mean

·       Performing a Two-Sample Test of the Means

·       Performing an N-Sample Test of the Means

·       Obtaining Time-to-Event Analysis Statistics

·       Obtaining Correlation Coefficients

·       General Approach to Obtaining Statistics

·       Practical Exercise

·       Lecture -9 Exporting Data- The Future of SAS Programming in Clinical Trials

·       Changes in the Business Environment

·       Changes in Technology

·       Changes in Regulations

·       Changes in Standards

·       Use of SAS Software in the Clinical Trial Industry

·       Practical Exercise

·       Lecture-10 Analysis of Stratified Data

·       Introduction

·       Continuous Endpoints

·       Categorical Endpoints

·       Time-to-Event Endpoints

·       Tests for Qualitative Interactions

·       Practical Exercise

·       Lecture-11 Multiple Comparisons and Multiple Endpoints

·       Introduction

·       Single-Step Tests

·       Closed Testing Methods

·       Fixed-Sequence Testing Methods

·       Resampling-Based Testing Methods

·       Testing Procedures for Multiple Endpoints

·       Gatekeeping Strategies

·       Practical Exercise

·       Lecture-12 Analysis of Safety and Diagnostic Data

·       Introduction

·       Reference Intervals for Safety and Diagnostic Measures

·       Analysis of Shift Tables

·       Practical Exercise

·       Lecture-13 Interim Data Monitoring

·       Introduction

·       Repeated Significance Tests

·       Stochastic Curtailment Tests

·       Analysis of Incomplete Data

·       Introduction

·       Case Studies

·       Data Setting and Modeling Framework

·       Analysis of Complete Growth Data

·       Simple Methods and MCAR

·       Available Case Methods

·       Likelihood-Based Ignorable Analyses

·       Multiple Imputations

·       The EM Algorithm

·       Categorical Data

·       MNAR and Sensitivity Analysis

·       Practical Exercise