How to interpret standardized beta coefficients with log?
Verfasst: Mi 17. Aug 2022, 13:32I carried out a multiple linear regression analysis with three dependent variables. Two of them are measures as a logarithm, one of them is measured on a range from [0,1]. The dependent variable is also a logarithm. In order to make them comparable, I used the stdBeta command in Stata to obtain the standardized coefficients, i.e., the beta weights.
However, I am unsure how to interpret these values. For the normal regression output I would do the following interpretation:
Log-Log: For a 1% increase in X, there is a x % increase in Y.
Lin-Log: For a 1-unit increase in X, there is a 100x % increase in Y. (at least for small values).
How does the interpretation for the standardized coefficients work? Is it the following?
Log-Log: For a 1% increase in the standard deviation in X, there is a x % increase in the standard deviation in Y.
Lin-Log: For a 1-standard-deviation increase in X, there is a 100x % increase in the standard deviation in Y?
I really appreciate your help!
However, I am unsure how to interpret these values. For the normal regression output I would do the following interpretation:
Log-Log: For a 1% increase in X, there is a x % increase in Y.
Lin-Log: For a 1-unit increase in X, there is a 100x % increase in Y. (at least for small values).
How does the interpretation for the standardized coefficients work? Is it the following?
Log-Log: For a 1% increase in the standard deviation in X, there is a x % increase in the standard deviation in Y.
Lin-Log: For a 1-standard-deviation increase in X, there is a 100x % increase in the standard deviation in Y?
I really appreciate your help!