The
Biostatistics Journal Club
will meet on
Tuesday, May 1, 2012
COPH 2280 12:00p.m. – 1:00p.m.
The topic of discussion will be
presented by
Josh Callaway, MPH
Health Program Analyst
Arkansas Department of Health
Development of Dynamic
Real-Time Robust Multivariable Monitoring Tool for Neonatology Data
Abstract
As real-time monitoring of salient variables has become
increasingly important in many realms of statistics, use has not reached its
full implementation in neonatal data. Premature infants constitute a population
in which monitoring particular associations between certain variables serves a
preventative need. Using R, we have developed a demonstration of how three
crucial variables may be modeled through a real-time monitoring algorithm to
produce the autoregulation index, a statistic which displays a vital physiologic
status. Not only may the successful implementation of this tool save costs in
the medical and health arenas, but it has potential for great flexibility. Any
relationship in life that requires instantaneous measurement association between
two continuous variables at given levels of a third categorical variable can be
computed through this model. Due to its utilization through R’s open-source
nature, the tool may pervade areas where real-time monitoring using more
expensive and established software deems implementation uneconomical.
Keywords:
-
Loess
Regression
-
Dynamic
Graphics
-
Real Time
Analysis
-
Multivariable Analysis
-
Autoregulation Index
-
R