Now that you've got a good sense of how to 'speak' R, let's use it with linear regression to make distinctive predictions.

For example, you might use regression analysis to find out how well you can predict a child's weight if you know that child's height. The following data are from a study of nineteen children. Height ...

This is where regression comes in. By using the regression function `svyglm ()` in R, we can conduct a regression analysis that includes party differences in the same model as race. Using `svyglm ()` ...

The authors show how to test the goodness-of-fit of a linear regression model when there are missing data in the response variable. Their statistics are based on the L₂ distance between nonparametric ...

To promote the use of regression modeling in the presence of competing risk events, we illustrate how to perform a multivariable regression analysis using the semiparametric proportional hazards ...

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 ...

A supremum-type statistic, based on partial sums of residuals, is proposed to test the validity of the mean function of the response variable in a generalized linear model. The proposed test does not ...