Delta-p statistics is an easier means of communicating results to a non-technical audience than the plain coefficients of a logistic regression model. In this article, authors Maarit Widmann and ...

A semi-parametric generalization of the proportional hazards regression model is defined, whereby the hazard functions can cross for different values of the covariates. In the two-sample comparison, ...

Information for evaluating the statistical significance of stepwise regression models developed with a forward selection procedure is presented. Cumulative distributions of the adjusted coefficient of ...

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...

By creating a new column of data corresponding to the product of the interacting variables, we can estimate the coefficients of the new model via regression analysis. The regression results can then ...

Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.