Timeline for Understanding the intercept value in a multiple linear regression with categorical values
Current License: CC BY-SA 3.0
6 events
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| Dec 30, 2019 at 11:57 | comment | added | gui11aume | @Marouen no it is not. If the predictors are correlated and you fit an additive model without interaction term, the intercept may be different from the mean response in this category. | |
| Dec 23, 2019 at 22:34 | comment | added | Marouen |
Hi @gui11aume. Can you please explain In the additive model, the intercept is the estimated value of the response variable for the first modalities of each factor under the assumption of additivity ? Is it the mean of the response variable in the additive model?
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| Oct 12, 2016 at 20:23 | comment | added | gui11aume |
@Boby I think you cannot. If you want to know the values, you will have to remove the call to anova().
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| Oct 12, 2016 at 11:26 | comment | added | user134432 | Thanks for the nice explanation. I have one question how do you calculate here the woolB:tensionM and woolB:tensionH from the aggregate output here? | |
| Jul 29, 2012 at 19:23 | vote | accept | jcazevedo | ||
| Jul 27, 2012 at 20:08 | history | answered | gui11aume | CC BY-SA 3.0 |