Logistic Regression Model Parameter
A Logistic Regression Model Parameter is a Parameter of a Logistic Function that is fitted to data.
- AKA: Logistic Regression Variable, Logistic Regression Coefficient, Logistic Regression Parameter, ...
- Context:
- It can be estimated by a Maximum Likelihood Algorithm.
- See: Linear Regression Model Parameter.
References
2000
- (Hosmer & Lemeshow, 2000) ⇒ David W. Hosmer, and Stanley Lemeshow. (2000). “Applied Logistic Regression, 2nd Edition." Wiley. ISBN:0471356328
- QUOTE: ... We begin our consideration of the interpretation of logistic regression coefficients with the situation where the independent variable is nominal scale and dichotomous (i.e., measured at to levels). This case provide the conceptual foundation for the other situations. ...
... In summary, the interpretation of the estimated coefficient for a continuous variable is similar to that of nominal scale variables: an estimated log odds ratio. The primary difference is that a meaningful change must be defined for the continuous variable. ...
... In the previous section in this chapter we discussed the interpretation of an estimated logistic regression coefficient in the case when there is a single variable in the fitted model. Fitting a serious of univariate models rarely provides an adequate analysis of the data in a study since the independent variables are usually associated with one another ...
- QUOTE: ... We begin our consideration of the interpretation of logistic regression coefficients with the situation where the independent variable is nominal scale and dichotomous (i.e., measured at to levels). This case provide the conceptual foundation for the other situations. ...