Lawrence Joseph
Bayesian statistics


Please Note: Prof. Joseph has retired.
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Research interests
Courses taught
Previous courses taught
EPIB-607 Principles of Inferential Statistics in Medicine
EPIB-613 Introduction to Statistical Software
EPIB-621 Data Analysis in the Health Sciences
EPIB-651 Bayesian Analysis in Medicine
EPIB-668 Introduction to Bayesian Analysis in the Health Sciences
EPIB-669 Intermediate Bayesian Analysis for the Health Sciences
EPIB-675 Bayesian Analysis in the Health Sciences
EPIB-682 Introduction to Bayesian Analysis in the Health Sciences
EPIB-683 Intermediate Bayesian Analysis for the Health Sciences
Publications
Methodological publications
Bayesian Sample Size
Change-point methods and applications
Diagnostic testing
Meta analysis
Other topics
Medical publications
Allergy and immunology
Asthma
Cardiology
Gastroenterology
Osteoporosis
Quality of Life
Rheumatology
Other
Book
Bayesian software
Bayesian Sample Size
Change-point methods and applications
Diagnostic testing
Diagnostic testing in Genetics
Links
EPIB-621 Data Analysis in the Health Sciences
Basic information
Instructor Lawrence Joseph
Credits 4
Course Objectives and Topics CoveredUnivariate and multivariate statistical techniques for continuous and dichotomous outcomes. Focus is on multiple linear and logistic regression models. Additional topics will include adjusting for missing data, measurement error, and hierarchical (random effects) models. All material will be taught from both Bayesian and frequentist viewpoints. R and WinBUGS software will be used throughout the course.
Place and TimeJanuary 7 to April 10, 2019. Time: Mondays and Wednesdays, 11:30 AM to 1:30 PM. Room: McIntyre Medical Building, Room 1034.
AssessmentAssignments = 5 * 4% (each) = 20%, Midterm Exam = 30%, Final Exam = 50%.
Some suggested Textbooks (none required)Michael H. Kutner, John Neter, Christopher J. Nachtsheim, William Li. Applied Linear Statistical Models, 4th Edition, McGraw-Hill, 2004.
David W. Hosmer and Stanley Lemeshow, Applied Logistic Regression, 2nd (or more recent) Edition Wiley, 2000.
George G. Woodworth. Biostatistics: A Bayesian Introduction. Wiley, New York, 2004.
Andrew Gelman, John Carlin, Hal Stern and Donald. Rubin, Bayesian Data Analysis, 2nd (or more recent) Edition, Chapman and Hall, 2003.
PrerequisitesPrevious courses in differential and integral calculus, and EPIB 607 or equivalent.