Step back a minute: normality is NOT required for predictors in a
multiple regression model, though the sqrt(x) transformation may
also make the relationship more nearly linear, and linearity IS
assumed when you fit a simple model such as y ~ x + w + z.
(Normality is only required for the residu
Before going to stackexchange you should consider if a square root
transformation is appropriate for the model that you are trying to
estimate. If you do so, you may be able to interpret the coefficients
yourself. If no explanation is obvious you probably should not be using a
square root transform
Hello,
R-Help answers questions on R code, your question is about statistics.
You should try posting the question to
https://stats.stackexchange.com/
Hope this helps,
Rui Barradas
Em 23-10-2017 18:54, kende jan via R-help escreveu:
Dear all, I am trying to fit a multiple linear regression
Dear all, I am trying to fit a multiple linear regression model with a
transformed dependant variable (the normality assumption was not verified...).
I have realised a sqrt(variable) transformation... The results are great, but I
don't know how to interprete the beta coefficients... Is it possib
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