Would you like to learn how to use R to
compare treatments, incorporate covariates into the analysis, analyse survival
(time-to-event) trials, model longitudinal data, and analysis of bioequivalence
trials.
Would you like to learn the implementation in
R of statistical procedures important for the clinical trial statistician?
Learn all this and more in Prof. Din Chen and Prof.
Karl Peace’s online course Biostatistics in R: Clinical Trial Applications
at Statistics.com.
Course Program:
Course outline: The course
is structured as follows
WEEK 1: Treatment Comparisons
·
R fundamentals associated with clinical trials
·
A simple simulated clinical trial
·
Statistical models for treatment comparisons
·
Incorporating covariates
WEEK 2: Survival Analysis
·
Time-to-event data structure
·
Statistical models for survival data
·
Right-censored data analysis
·
Interval-censored data analysis
WEEK 3: Analysis of Data from Longitudinal Clinical Trials
·
Trial designs and data structure
·
Statistical models and analysis
WEEK 4: Analysis of Bioequivalence Clinical Trials
·
Data from bioequivalence clinical trials
·
Bioequivalence clinical trial endpoints
·
Statistical methods to analyze bioequivalence
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.
In addition to assigned readings, this course
also has an end of course data modeling project, example software files, and
supplemental readings available online.
Instructors: 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.
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.
You will be able to ask questions
and exchange comments with the instructors via a private discussion board
throughout the course. The courses take place online at
statistics.com in a series of 4 weekly lessons and assignments, and require
about 15 hours/week. Participate at your own convenience; there are no
set times when you must be online. You have the flexibility to work a bit every
day, if that is your preference, or concentrate your work in just a couple of
days.
We, the Center for eLearning and Training
(C-eLT), Pune, partner with Statistics.com and offer these courses to Indian
participants at special prices payable in INR.
Call: 020 6680 0300 / 322
Websites:
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