How to interpret standardized beta coefficients with log?

Regressionsmodelle aller Art mit Stata.

How to interpret standardized beta coefficients with log?

Beitragvon Michaela_1 » Mi 17. Aug 2022, 13:32

I 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!
Zuletzt geändert von Michaela_1 am Mo 22. Aug 2022, 18:03, insgesamt 1-mal geändert.
Michaela_1
 
Beiträge: 1
Registriert: Mi 17. Aug 2022, 13:24
Danke gegeben: 0
Danke bekommen: 0 mal in 0 Post

Re: How to interpret beta weights with a log-log and lin-log

Beitragvon Staxa » Mi 17. Aug 2022, 18:11

I think this question is better suited in a statistics forum, like https://stats.stackexchange.com/
Stata für Anfänger: www.statabook.com
Staxa
 
Beiträge: 679
Registriert: Di 27. Feb 2018, 12:56
Danke gegeben: 0
Danke bekommen: 0 mal in 0 Post


Zurück zu Regressionsmodelle

Wer ist online?

Mitglieder in diesem Forum: 0 Mitglieder und 1 Gast

cron