I am trying to reuse a multiple linear regression formula, where I have a set of predictors and set of coefficient values.
This is how they look like (in real example there is ~10 of predictors):
alpha = 7.601 weight = 2213.940 length = -0.032 height = -0.629 size = 0.345
I know that my multiple linear regression should be constructed like this, i.e. sum of alpha (
b0), and multiplication of predictors (
xn) with their coefficients (
y = b0 + b1*x1 + b2*x2 + b3*x3 + b4*x4 +b5*x5
I want to reuse the formula, but I have data only describing
length, so have no data about predictors
The question is, can I just skip parameters that I don't have data for? I.e. instead of using full sum of
parameters*coefficient I will just use the ones I have?
I would guess that this is likely not a correct approach. Also, I don't have information about the proportion of explained variability by each predictor, or their significance, to guide me which predictors are
more important that others. Thank you for your advises.