Home > Product Details

R Programming for SAS Programmers

Welcome to “R Programming for SAS programmers” class. Below are the topics that we will cover in our training. It will take atleast 3 months to finish this training. I know you are in hurry to finish this training and start using R at your work so we will meet twice a week to get it done as soon as possible. There will be quizzes and excercies at end of each session. Solutions to the exercises will be provided.

START DATE: 07NOV2022

Meet every Monday and Friday: 7pm EST (Meeting URL will be available after course is purchased.)

Before your first class, do following

  1. Download and install R https://cran.r-project.org/bin/windows/base/
  2. Download and install R Studio Desktop (FREE) https://www.rstudio.com/products/rstudio/download/

TOPICS COVERED

  1. Getting Started with R
    1. Overview
    2. History of R
    3. Rstudio Tour
    4. R Resource Tour
  2. R Language Foundation Part 1
    1. Introduction
    2. Names, Assignment and Vectors
    3. Operators
    4. Vectors
    5. Factors and Lists
    6. Data Frames
    7. Capstone
  3. R Language Foundation Part 2
    1. Introduction
    2. Conditions and Loops
    3. Functions
    4. String Operations
    5. Dates and Times
    6. Missing Values
    7. Formatting Data
    8. Capstone
  4. Tidyverse Data Manipulation
    1. Introduction
    2. Tibbles
    3. Data Import
    4. Subsetting and Sorting
    5. Creating Variables
    6. Summaries
    7. Group Operations
    8. Joins
    9. Pivots
    10. Capstone – Cheat Sheets
  5. Supplemental Tools/Packages
    1. Introduction
    2. Tidyverse Strin gOperations
    3. Tidyverse Date Operation
    4. Tables with Janitor Package
    5. Tidyverse Graphics 1
    6. Tidyverse Graphics 2
    7. Tidyverse Factor Operations
    8. Formatting with fmtr packages
    9. Reporting
  6. Statistical Computing
    1. Introduction
    2. Chi-square, T-Tests, Correlation
    3. ANOVA
    4. Sampling and Regression
    5. Survival Analysis
  7. Creating SDTM dataset
    1. Introduction
    2. Data Quality Checks
    3. SDTM Dataset Builds
      1. DM
      1. VS
      2. AE
      3. LB
      4. EX
  2. Creating ADaM dataset
    1. Introduction
    2. ADaM dataset Builds
      1. ADSL
      1. ADVS
      2. ADAE
      3. ADLB
      4. ADEX
  2. Creating Tables, Listings and Figures
    1. Introduction
    2. Listings
    3. Demographics
    4. Adverse Events
    5. Vitals Change from Baseline
    6. Labs Change from Baseline
    7. Basic Figures
    8. Survival