Lawrence Joseph
Bayesian statistics


Please Note: Prof. Joseph has retired.
These pages are left up in case they prove
useful, but the pages and software will
no longer be updated. All material and
software is "as is" with no guarantees
of functionality or correctness.
Complete CV
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
My global research interest is Bayesian biostatistical modeling. I am currently focussing on three particular topics:


Diagnostic tests in the absence of a gold standard It is common in population screening surveys or in the investigation of new diagnostic tests to have results from one or more tests investigating the same disease, but none of which can be considered perfectly error-free. Despite these limitations, it is important for clinical and public health practice to have the best possible estimates of disease prevalence and the properties of diagnostic tests, such as the sensitivity and specificity. Methodology for both design and analysis of diagnostic test data have been developed. Current research involves analyses for continuous tests and ROC curves.
Bayesian methods for study design and sample size determination Consideration of the optimal number of subjects and other design aspects is required in any study. Early research covered sample size methods for standard binomial, normal, and differences between two binomial or normal sampling situations. Current research investigates more complex univariate and multivariate situations, including design for diagnostic studies investigation of novel sample size criteria for prior robustness.
Biostatistical Consulting and Collaboration In addition to methodologic research, I also serve as the collaborating biostatistician on many projects in various areas of medical research. Among others, I am currently participating in projects investigating gastroenterological disorders, lupus nephritis, and cardiovascular diseases.
Software development New biostatistical methods cannot reach their full potential without the distribution of the software necessary for their implementation. User-friendly programs have been created for all of the above methodologies, and have been made freely available to other researchers through this web page.
Bayesian Sample Size
Change-point methods and applications
Diagnostic testing
Diagnostic testing in Genetics