Are the regression coefficients interpreted the same way as a traditional linear model (i.e., a one unit increase in a predictor X, increases outcome Y by the beta coefficient value)?
It is common practice in model building to remove the intercept by adding zero to the formula. However, if one does that in the example given here the correlation between the residuals increases (0.5 to 0.7). Can anyone where explain what causes that?
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Are the regression coefficients interpreted the same way as a traditional linear model (i.e., a one unit increase in a predictor X, increases outcome Y by the beta coefficient value)?
Do you know a method to plot my estimates of the gls modele using ggplot
It is common practice in model building to remove the intercept by adding zero to the formula. However, if one does that in the example given here the correlation between the residuals increases (0.5 to 0.7). Can anyone where explain what causes that?
Thanks a lot for your video, can you share the dataset of this video? I need such data to understand more about GLS. Thanks
get it from the package "faraway" she mentioned in r