Dear all, I believe this should be a simple question but after trying and reading I still have no solutions.

Basically what I want to do is to run a linear model in R fixing the intercept to a specific value (which in my case is 0.69, i.e. ln(2)).

Specifically, I would like to generate a linear model with interaction, but fixing the intercept in order to have the same intercept for the different groups:

lm(y ~ day*group, data = d.df)

When I fit the data, fixing the intercept using the approaches I will soon explain, I expect to see changes in the slope coefficients between the groups but I do not: In R, I've tried using the I() as well as offset approaches and the ne library(restriktor) but when I call the summary() of the model I am still seeing intercept and slope estimates consistent with the model without fixing intercepts.

This means that the I() is not fixing the intercept as I wish.

Do you have any other solutions I might follow? Thank you very much in advance.

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