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Clinical Trial Data Analysis Using R 

Begins May 14th  2013

Aim of Course: This 3-week course is intended to cover the fundamentals in clinical trial data analysis using R. The course will start with a review of R in relation to the clinical trial design and analysis and then use R to analyze clinical trials in treatment comparison, treatment comparison with covariates, time-to-event endpoints and longitudinal structures.

 

Who Should Take This Course: Anyone who encounters design and analysis of clinical trial data in their work and wishes to learn clinical trial methods and step-by-step implementation of these methods in R.

Instructor: Din Chen received his Ph.D. in Statistics from the University of Guelph (Canada) in 1995 and is now a professor in biostatistics at the University of Rochester Medical Center.  Professor Chen was the Karl E. Peace endowed eminent scholar chair and Professor in biostatistics for the Jiann-Ping Hsu College of Public Health at the Georgia Southern University. He consults on a regular basis for biopharmaceutical firms and government agencies and has extensive expertise in clinical trials, bioinformatics and statistics applications. More than 80 refereed professional publications of his are in print. He is co-author of "Clinical Trial Methodology" and "Clinical Trial Data Analysis Using R" published by CRC in 2010

 

Prerequisite: Course participants should have a basic understanding of R (equivalent to "Introduction to R"), though, regardless, the instructor will guide you in the learning process. Basics in statistics, estimation and hypothesis testing are also expected.

Organization of the Course: The course takes place over the Internet. Course participants will be given access to a private bulletin board, on which they will receive course materials. The board will also serve as a forum for discussion of ideas and problem solving. R software can be downloaded free from www.r-project.org and you'll be given step-by-step instructions in its use. 

Text Book: Din Chen and Karl E. Peace (2010). Clinical Trial Data Analysis Using R. Chapman & Hall / CRC Biostatistics Series.  

Course Program: The course is structured as follows

Session 1  - Treatment Comparisons (Review Chapters 1 to 4)

  • - R Review associated with clinical trials (Chapter 1)

  • - A simple simulated clinical trial (Chapters 1 and 2)

  • - Statistical models for treatment comparisons (Chapter 3)

  • - Incorporating covariates (Chapter 4)

 

Session - Clinical Trials with Time-to-Event Endpoints (Chapter 5)

  • - Time-to-event data structures: breast cancer trial (Section 5.1)

  • - Review of statistical models for survival data (Section 5.2)

  • - Analysis of right-censored data with Kaplan-Meier and Cox-regression (Section 5.3)

  • - Analysis of interval-censored data with Turnbull and "IntCox" (Section 5.4)

  • - Step-by-step implementations in R for the methods and data analysis in R

 

Session 3: Analysis of Data from Longitudinal Clinical Trials (Chapter 6)

  • - Longitudinal clinical trial data structure with real examples

  • - Review of statistical models (linear mixed models, generalized linear mixed model and GEE)

  • - Data analysis: step-by-step implementation in R

 

Cost: $299 per participant.  ($259 for each additional person at the same firm, institution or government office.) An additional discount may apply for early registration.

Immediately after your payment is credited, you will receive an email giving you sign up instructions, and the web address (URL) of the course material.  Note that you will not be able to access this address until the start date of the course.  We recognize that most course participants have full time jobs. A charge of $55 is made for refunds up until one week prior to the start of the course.  While no refunds are given after this date, participants may retake the course without charge the next time the course is offered

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