Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

Model the data as a log-linear model with (the Poisson variance function) and where Yij= number of epileptic seizures in interval j tij= length of interval j The correlations between the counts are ...

Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.

As the title “Practical Regression” suggests, these notes are a guide to performing regression in practice. This note explains how to choose between log and linear specification. The note emphasizes ...

We present a novel semiparametric survival model with a log-linear median regression function. As a useful alternative to existing semiparametric models, our large model class has many important ...

One Population The usual log-linear model analysis has one population, which means that all of the variables are dependent variables. For example, the statements proc catmod; weight wt; model ...

Learn how to build a multivariate linear regression model step by step—no libraries, just pure C++ logic!

In the example below, I use an e-commerce data set to build a regression model. I also explain how to determine if the model reveals anything statistically significant, as well as how outliers may ...

For the parameters of a multinomial logistic regression, it is shown how to obtain the bias-reducing penalized maximum likelihood estimator by using the equivalent Poisson log-linear model. The ...