The online course 'Biostatistics in R: Clinical Trial Applications' teaches statistical procedures for clinical trials using R software, focusing on treatment comparisons, survival analysis, longitudinal data, and bioequivalence trials. It is suitable for analysts and statisticians in the pharmaceutical and health research sectors who have some familiarity with R. The course runs for four weeks online, requiring approximately 15 hours of participation per week, and includes access to instructors and a discussion board for interaction.

1. Online course
Biostatistics in R: Clinical Trial Applications
Taught by Prof. Din Chen and Prof. Karl Peace
(http://www.statistics.com/Clinical-Trials-R/)
Aim of Course:
This course covers the implementation in R of statistical procedures important for the
clinical trial statistician. Students completing the course will learn how to use R to
compare treatments, incorporate covariates into the analysis, analyze survival (time-to-
event) trials, model longitudinal data, and analysis of bioequivalence trials.
Who Should Take This Course:
Analysts and statisticians at pharmaceutical companies and other health research
organizations who need or want to become involved in the design, monitoring or
analysis of clinical trials and who are familiar with R software and considering its use in
clinical trials.
Course Program:
Course outline: The course is structured as follows
SESSION 1: Treatment Comparisons
 R fundamentals associated with clinical trials
 A simple simulated clinical trial
 Statistical models for treatment comparisons
 Incorporating covariates
SESSION 2: Survival Analysis
 Time-to-event data structure
 Statistical models for survival data
 Right-censored data analysis
 Interval-censored data analysis
SESSION 3: Analysis of Data from Longitudinal Clinical Trials
 Trial designs and data structure
 Statistical models and analysis
SESSION 4: Analysis of Bioequivalence Clinical Trials
 Data from bioequivalence clinical trials
 Bioequivalence clinical trial endpoints
 Statistical methods to analyze bioequivalence

2. Homework:
Homework in this course consists of short answer questions to test concepts, guided
data analysis problems using software, and guided data modeling problems using
software.
Software:
You must have a copy of R for the course.
Instructor:
Prof. Din Chen, Univ. University of Rochester Medical Center, co-author of "Clinical Trial
Methodology" and "Clinical Trial Data Analysis Using R," and the author or co-author of
80 refereed articles in scholarly journals.
Prof. Karl E. Peace, Jiann-Ping Hsu College of Public Health at Georgia Southern
University, Georgia Cancer Coalition Distinguished Cancer Scholar, founding director of
the Center for Biostatistics, and the founder of Biopharmaceutical Research Consultants,
Inc. (BRCI), and is Founder and Chair of the Biopharmaceutical Applied Statistics
Symposium (BASS). He has contributed heavily to the medical, scientific and statistical
literature by authoring or co-authoring over 150 articles and six books.
This course takes place over the internet at the Institute for 4 weeks. During each course
week, you participate at times of your own choosing - there are no set times when you
must be online. The course typically requires 15 hours per week. Course participants will
be given access to a private discussion board so that they will be able to ask questions
and exchange comments with instructor, Prof. Din Chen and Prof. Karl Peace. The class
discussions led by the instructor, you can post questions, seek clarification, and interact
with your fellow students and the instructor.
For Indian participants statistics.com accepts registration for its courses at reduced
prices in Indian Rupees through us, the Center for eLearning and Training (C-eLT), Pune.
For India Registration and pricing, please visit us at www.india.statistics.com.
Email: info@c-elt.com
Call: +91 020 66009116
Websites:
www.india.statistics.com
www.c-elt.com