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Meta-Analysis Using R 

Begins July 10th 2015

Aim of Course: This 3-week course is intended to cover the fundamental techniques in combining data from multiple studies using R. The course will cover the methods of fixed-effects and random-effects meta-analysis models as well as the techniques in identifying publication bias. R packages "rmeta" and "meta" will be introduced for the step-by-step implementation with "forest" and "funnel" plots.

Who Should Take This Course: Anyone who wishes to conduct meta-analysis methodology and step-by-step implementation of these methods in R. Class participants are encouraged to bring their own datasets and ongoing projects into the class to be used as examples.

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 100 refereed professional publications of his are in print. He is co-author of "Clinical Trial Methodology (2010)", "Clinical Trial Data Analysis Using R (2010)", "Interval-Censored Time-to-Event Data: Methods and Applications (2012)", "Applied Meta-Analysis Using R (2013)" and "Clinical Trial Biostatistics and Biopharmaceutical Applications (2014)" published by Chapman and Hall/CRC.

 

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 and you'll be given step-by-step instructions in its use. 

Text Book: Ding-Geng (Din) Chen and Karl E. Peace (2013). Applied Meta-Analysis Using R. Chapman & Hall / CRC Biostatistics Series.

Reference Book: Ding-Geng (Din) Chen and Karl E. Peace (2010). Clinical Trial Data Analysis Using R. Chapman & Hall / CRC Biostatistics Series. (Chapters 1 and 8)

Course Program: The course is structured as follows

Session 1 - Fixed-Effects Meta-Analysis

  • Data structure for meta-analysis (Section 3.1)
  • Fixed-effects and Random-effects in meta-analysis (Section 3.2)
  • Step-by-step meta-analysis using R packages "rmeta" and "meta" (Section 3.3)

Session 2 - Meta-Analysis with Binary Data

  • Datasets from Statin clinical trials and studies on lamotrigine for treatment of bipolar depression (Section 4.1)
  • Meta-analysis methods with risk-difference, risk-ratio and odds-ratios (Woolf's method, Mantel-Haenszel and Peto's methods) (Section 4.2)
  • Meta-analysis using R (Section 4.3)

Session 3 - Meta-Analysis with Continuous Data

  • Two real datasets (Section 5.1)
  • Meta-analysis methods with mean difference and standardized mean difference (Section 5.2)
  • Step-by-step meta-analysis using R (Section 5.3)

Cost: $299 per participant. Early-bird discount may apply. Students, faculty and research workers at academic institutions are eligible for a further discount. Just send an email from your academic or institutional email account to courses@statcourse.com to receive a discount coupon worth $35 toward the cost of the course. 

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 $50 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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