Open AccessLogit Model of High Blood Pressure
Author(s) -
Evelyn Nkiruka Okeke,
Joseph Uchenna Okeke
Publication year - 2017
Publication title -
european journal of engineering and technology research
Language(s) - English
Resource type - Journals
ISSN - 2506-8016
DOI - 10.24018/ejers.2017.2.12.429
Subject(s) - logistic regression , blood pressure , heartbeat , logit , statistics , binary logit model , medicine , econometrics , mathematics , computer science , computer security
This paper is focused on the logit model of high blood pressure. We discussed logit model in detail and applied it to a real life data of high blood and normal blood pressure of 126 individuals. The analysis generated a model for finding the probability of having high blood pressure and revealed that heartbeat rate followed by weight and then age are factors affecting high blood pressure with a concordant percentage of 95.4.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom