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.
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
Keywords: Sets method, CUSCORE method, Bernoulli CUSUM, steady state average run length (ARL), rare health event