I know that we have previously discussed how the use of standardized coefficients may obfuscate results rather than shedding more light. I completely agree!
However, I am curious to really understand how one can use these coefficients, if one had to. Consider we run an OLS on standardized y and x, which yields the standardized coefficient beta.
std(y) = 0.191 std(x)
One may interpret this as 1SD change in X is associated with 0.191SD change in y. Consider the s.d of the unstandardized variables are sd(Y) = 27.37 and sd(X) = 0.094. In this case, would it be reasonable to infer that 1SD change in X (sd=0.094) is associated with 1.8% change in Y (0.094*0.191)?
Thanks in advance!
Related Posts with Interpretation of standardized coefficients
Identify a number which is not present in a numbers' listHello everyone, I have a variable called stratum which is supposed to carry numbers from 1 to 10. S…
R squared after fixed effects estimation with mi estimate, post:Dear all, I’m using a multiple imputation with the command mi estimate, post: xtreg wage $xlist , fe…
Hausman Endogenity TestHi, I have a reverse causation system. Y1 = f(Y2, X) and Y2 =g(Y1, Z). Using IV both reverse casuat…
Parameter constraints in MLE estimation for SFAHello, I'm using the following commands after which I would like to set up constraints for the param…
Generalized Difference-in-Differences with a moderator variable - repeated time values within panelHello Statalists! I'm currently calculating a generalized DiD model and I'm unsure if my approach is…
Subscribe to:
Post Comments (Atom)
0 Response to Interpretation of standardized coefficients
Post a Comment