Open AccessPredictive Model on Determinants of Child Mortality Using Multiple Regression Analysis
Author(s) -
M. A. Sonawane,
Apakrita Tayade
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1850/1/012129
Subject(s) - multicollinearity , child mortality , mortality rate , regression analysis , linear regression , measles , demography , statistics , medicine , environmental health , mathematics , vaccination , immunology , population , surgery , sociology
Child mortality is one of the important factors to reflect sustainable development for any nation. It is common sense now that child mortality rate depends on medical services platform and its quality. To predict model under-five child mortality rates in India, multiple linear regression analysis was used. Identifying the factors that affects the under-five child mortality. To examine the relationship between all the variables along with recognize the problem of multicollinearity in the variables. In this study our fitted multiple linear regression model found that under five child mortality rates in India are influenced by tuberculosis case detection rate, measles death rate and hepatitis immunization rate. To choose appropriate model ACI score is used.