SAS Clinical course Curriculum
Our course curriculum is designed by the industry experts who behold professionalism in different Clinical SAS technologies and aspects. Here are the topics that the curriculum covers in detail:
• Clinical Trial designs
This module discusses crossover trials, equivalence trials, factorial design, bio equivalence trials, noninferiority trials, multicenter trials, and cluster randomized trials.
• Statistical analysis basics
The session covers topics like data types, normal distribution, mean comparison, proportions comparison, significance tests, confidence intervals, and survival data analysis.
• Data Analysis trial
This section teaches you about intention to treat analysis, confounding, subgroup analysis, regression analysis, interaction, covariates adjustment, multiplicity, repeated measurements, missing data, stopping rules, and interim monitoring.
• Trials Reporting
The module gives you insights on reporting, trial profile, use of tables and figures, presenting the baseline data, critical reports appraisal, and meta analysis.
• Tables and listings
In this section, you will learn about preparation and classification, data importing, data transformation, analysis creation, creating tables and listings, clinical trial tables creation, categorical summary tables, medication tables, laboratory shift tables, and adverse event summaries.
• Clinical trial graphs
You can learn about the common trial graphs, line plot, scatter plot, bar chart, box plot, odds ratio plot, and Kaplan- Meier Survival Estimates plot.
• Statistical analyses
This module teaches you about statistics, descriptive statistics, inferential statistics, association test, logistic regression, continuous data analysis, mean sample test, time to event analysis, correlation coefficients, and obtaining statistics
• Data exporting
The section discusses cchanges in the business environment, technology, regulations, and standards. You will learn about the uses of SAS software for the clinical trial.
• Stratified data analysis
You can learn continuous endpoints, categorical endpoints, tome to events endpoints, qualitative interaction tests, etc.
• Multiple comparison & endpoints
In this module, you will learn about single-step methods, closed testing methods, resampling testing methods, sequence testing methods, testing processes of multiple endpoints, and gatekeeping strategies.
• Safety and diagnostics data analysis
The module gives and overview about the safety analysis, brief on the Reference Intervals for Diagnostic and safety Measures, and the analysis of Shift Tables
• Interim data monitoring
In this module, you will learn data monitoring Introduction, Repeated Significance Tests, and Stochastic Curtailment Tests.