Linear regression models the relationship between a dependent and independent variable(s). A linear regression essentially estimates a line of best fit among all variables in the model. Regression ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...

This course will introduce linear, generalized linear and time-to-event regression models that are commonly used in epidemiologic research, community needs assessment and public health program/policy ...

Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...