| ... | ... | @@ -132,7 +132,15 @@ When constructing a generalized linear model, three major decisions must be made |
|
|
|
|
|
|
|
2. **Specifying the Systematic Component (Linear Predictor):**
|
|
|
|
A linear combination of predictor variables should be constructed as the linear
|
|
|
|
predictor of the model.
|
|
|
|
predictor of the model. This component is the fixed structural part of the model that
|
|
|
|
will be used to explain systematic variability between means. If we have Q+1 predictors
|
|
|
|
in our model, the linear predictor would be:
|
|
|
|
|
|
|
|
<a href="https://www.codecogs.com/eqnedit.php
|
|
|
|
latex=\eta=\beta_0+\beta_1x_1+\beta_2x_2+&space;...+&space;\beta_Qx_Q" target="_blank"><img src="https://latex.codecogs.com/svg.latex?\eta=\beta_0+\beta_1x_1+\beta_2x_2+&space;...+&space;\beta_Qx_Q" title="\eta=\beta_0+\beta_1x_1+\beta_2x_2+ ...+ \beta_Qx_Q" /></a>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3. **Choosing a Link Function:**
|
|
|
|
An appropriate function must be chosen which maps the mean of the response variable
|
|
|
|
onto the linear predictor. This function should be chosen in such a way to ensure that
|
| ... | ... | |
| ... | ... | |