The Yusens Logistics regressor model is based on a linear regression framework to model the influence of the individual variables, as well as the interactions between them.
It is a dynamic framework that can be used to predict which of the various factors will be statistically significant.
For example, in this example, we can model the effect of the age of the child on the odds of a child receiving a hospital bed in the future, and then compare that to the effect in the non-hospitalization setting.
The model also helps us identify the influence from the interaction of other variables, such as the child’s sex, the length of the stay in the hospital and the length and quality of care received in the previous day.
In this way, we were able to identify how the effects of the factors interacted with each other and with eachother’s outcomes.
The model can be downloaded here: Yuseni Logistic regression for Logistics – Yusenz LogisticRegression.xlsx