Abstract Details
Activity Number:
|
291
|
Type:
|
Contributed
|
Date/Time:
|
Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Statistics Without Borders
|
Abstract #311879
|
|
Title:
|
Innovative Statistical Approaches in Clinical Microbiology Research
|
Author(s):
|
Jayawant Mandrekar*+
|
Companies:
|
Mayo Clinic
|
Keywords:
|
Inverse prediction ;
Deming's regression ;
Bayesian latent class models
|
Abstract:
|
Academic medical centers offer opportunities to consult on clinical projects that involve novel applications of statistical methods. The focus of this presentation is to provide brief illustrative examples of projects from infectious diseases and clinical microbiology. Specifically, statistical approaches including; 1) use of inverse prediction to estimate the true known concentration on the basis of the value obtained from real-time PCR, 2) use of Deming's regression to compare the performance of different assays in clinical microbiology studies, and 3) use of Bayesian latent class models to estimate the performance of diagnostic tests (sensitivity, specificity, negative predictive value and positive predictive value) when there is no gold standard. Findings from these studies directly impact patient care and/or offer cost savings with improved efficiency.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.