Binary Logit
| Related Online Training modules | |
|---|---|
| Regression | |
| Generally it is best to access online training from within Q by selecting Help > Online Training |
Binary Logit, also known as Logistic Regression is estimated in Q when the Dependent question is a Pick One question and it contains only two categories.
See:
- Regression for a description of how to run a regression in Q.
- Regression Outputs for a description of the standard outputs.
Additional outputs
With ordered logit, additional parameters are shown at the beginning of the output which relate to the thresholds for the categories. An understanding of the working of these thresholds is most readily obtained by checking the option for Construct variable(s) containing predictions and reviewing the JavaScript of the created variables (alternatively, review the first of the references provided in Regression Outputs.
Additional Properties
When using this feature you can obtain additional information that is stored by the R code which produces the output.
- To do so, select Create > R Output.
- In the R CODE, paste: item = YourReferenceName
- Replace YourReferenceName with the reference name of your item. Find this in the Report tree or by selecting the item and then going to Properties > General > Name from the object inspector on the right.
- Below the first line of code, you can paste in snippets from below or type in str(item) to see a list of available information.
For a more in depth discussion on extracting information from objects in R, checkout our blog post here.
Properties which may be of interest are:
- Summary outputs from the regression model:
- item$summary$coefficients # summary regression outputs
Further reading: Market Segmentation Software