In the industrial, medical, and other industries, it might
be difficult to track the incidence rate of an event of interest when the
baseline probability of the event is low. There aren't many statistical
techniques available for use in formal approaches to the challenge of
researching unusual health incidents. Except for the original quality control
chart developed by Shewhart, the most well-known surveillance techniques are
built on the CUSUM approach, which was used to identify minute changes in the
process. However, when the event's baseline probability is very low, this graph
fails to depict a rise in rate. Other approaches to solving this problem
include the Sets technique, the CUSCORE (Cumulative Score) method, and the
CUSUM (Cumulative Sum) method, both of which are based on the Bernoulli
distribution. With the aid of preceding literature, a thorough analysis of these
three methodologies in the context of health science is examined, as well as
the significance of these methods in the same field.
Author(s) Details:
Sasikumar Ramaraj,
Department of Statistics, Manonmaniam Sundaranar University, Tirunelveli,
Tamil Nadu, India.
Bangusha Devi Subramanian,
Department of Mathematics, JP College of Engineering, Tenkasi, Tamil Nadu,
India.
Please see the link here: https://stm.bookpi.org/CODHR-V2/article/view/7749
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