The lm function name stands for "linear model." Linear regression is a subset of techniques called general linear models. Interpreting the Results The summary command displays just the basic results ...

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

In model.ks, we could start by removing fine aggregates because its p-value is 0.95748. We then re-run the model and determine if we still have any non-significant coefficients. This iterative process ...

R is a free computing and graphical software/environment for statistical analysis. Part III of this short course consists of 3 sections: Section 5 introduces the concept of generalized linear models.

Duration: 12h. In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial ...

Multiple regression and regression diagnostics. Generalised linear models; the exponential family, the linear predictor, link functions, analysis of deviance, parameter estimation, deviance residuals.

Stephen G. Walker, Bani K. Mallick, Hierarchical Generalized Linear Models and Frailty Models with Bayesian Nonparametric Mixing, Journal of the Royal Statistical Society. Series B (Methodological), ...