Francis L. Huang, Multilevel Modeling and Ordinary Least Squares Regression, The Journal of Experimental Education, Vol. 86, No. 2 (2018), pp. 265-281 ...

Zheng Yuan, Yuhong Yang, Combining Linear Regression Models: When and How?, Journal of the American Statistical Association, Vol. 100, No. 472 (Dec., 2005), pp. 1202-1214 ...

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

Parametric versus Semi/nonparametric Regression Models Course Topics Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the ...

Multiple linear regression (MLR) is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...