Regression with qualitative variables is different from analysis of variance and analysis of covariance. Analysis of variance uses qualitative independent variables only. Analysis of covariance uses ...

Multivariate regression enables you to relate one dependent variable to multiple independent variables you've derived from surveys or measurements. This type of data analysis helps you search for ...

The first command means, "Store into an object named mymodel the results of a linear regression analysis using the data in the data frame table named myt, where Income is the dependent variable and ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

Input Variables and Regression with ARMA Errors . In addition to past values of the response series and past errors, you can also model the response series using the current and past values of other ...

Multivariable analysis is a widely used statistical methodology for investigating associations amongst clinical variables. However, the problems of collinearity and multicollinearity, which can ...

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()` from the survey package (rather than ...