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

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 ...

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 ()` ...

In this article we propose a class of estimation functions for the vector of regression parameters in the Cox proportional hazards model with possibly time-dependent covariates by incorporating the ...

Nonlinear regression is a form of regression analysis in which data is fit to a model and then expressed as a mathematical function. Simple linear regression relates two variables (X and Y) with a ...

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

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 ...

To overcome this shortcoming, standardized LM tests are suggested. Monte Carlo results show that the new tests possess good finite sample properties. An important observation made throughout this ...