How to calculate standardized coefficients from an estimated multiple regression model





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I have a multiple regression model(original model) that has been estimated already, and the details on the mean and standard deviations of the regressors, and the standard errors of coefficients from the original model are provided. This model has 4 explanatory variables along with an intercept.



In general, what is the procedure to calculate standardized coefficients using the values of estimated coefficients in the original model, (which is linear in parameters and the regressors) and all the other details I just mentioned that have been provided to me?



The purpose of doing this being that I've been asked to compare the magnitudes of the influence of some explanatory variables on the dependent variable.










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    up vote
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    favorite












    I have a multiple regression model(original model) that has been estimated already, and the details on the mean and standard deviations of the regressors, and the standard errors of coefficients from the original model are provided. This model has 4 explanatory variables along with an intercept.



    In general, what is the procedure to calculate standardized coefficients using the values of estimated coefficients in the original model, (which is linear in parameters and the regressors) and all the other details I just mentioned that have been provided to me?



    The purpose of doing this being that I've been asked to compare the magnitudes of the influence of some explanatory variables on the dependent variable.










    share|cite|improve this question
























      up vote
      3
      down vote

      favorite









      up vote
      3
      down vote

      favorite











      I have a multiple regression model(original model) that has been estimated already, and the details on the mean and standard deviations of the regressors, and the standard errors of coefficients from the original model are provided. This model has 4 explanatory variables along with an intercept.



      In general, what is the procedure to calculate standardized coefficients using the values of estimated coefficients in the original model, (which is linear in parameters and the regressors) and all the other details I just mentioned that have been provided to me?



      The purpose of doing this being that I've been asked to compare the magnitudes of the influence of some explanatory variables on the dependent variable.










      share|cite|improve this question













      I have a multiple regression model(original model) that has been estimated already, and the details on the mean and standard deviations of the regressors, and the standard errors of coefficients from the original model are provided. This model has 4 explanatory variables along with an intercept.



      In general, what is the procedure to calculate standardized coefficients using the values of estimated coefficients in the original model, (which is linear in parameters and the regressors) and all the other details I just mentioned that have been provided to me?



      The purpose of doing this being that I've been asked to compare the magnitudes of the influence of some explanatory variables on the dependent variable.







      regression estimation econometrics standardization






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      divya garg

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          You can simply compute:



          $$
          hat{beta}_{i,std} = hat{beta}_i*frac{sd(x_i)}{sd(y)}
          $$



          Where $hat{beta}_i$ is the original coefficient of covariate $X_i$, and $sd(cdot)$ refers to sample standard deviations.






          share|cite|improve this answer








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            1 Answer
            1






            active

            oldest

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            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes








            up vote
            3
            down vote













            You can simply compute:



            $$
            hat{beta}_{i,std} = hat{beta}_i*frac{sd(x_i)}{sd(y)}
            $$



            Where $hat{beta}_i$ is the original coefficient of covariate $X_i$, and $sd(cdot)$ refers to sample standard deviations.






            share|cite|improve this answer








            New contributor




            statslearner2 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
            Check out our Code of Conduct.






















              up vote
              3
              down vote













              You can simply compute:



              $$
              hat{beta}_{i,std} = hat{beta}_i*frac{sd(x_i)}{sd(y)}
              $$



              Where $hat{beta}_i$ is the original coefficient of covariate $X_i$, and $sd(cdot)$ refers to sample standard deviations.






              share|cite|improve this answer








              New contributor




              statslearner2 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
              Check out our Code of Conduct.




















                up vote
                3
                down vote










                up vote
                3
                down vote









                You can simply compute:



                $$
                hat{beta}_{i,std} = hat{beta}_i*frac{sd(x_i)}{sd(y)}
                $$



                Where $hat{beta}_i$ is the original coefficient of covariate $X_i$, and $sd(cdot)$ refers to sample standard deviations.






                share|cite|improve this answer








                New contributor




                statslearner2 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.









                You can simply compute:



                $$
                hat{beta}_{i,std} = hat{beta}_i*frac{sd(x_i)}{sd(y)}
                $$



                Where $hat{beta}_i$ is the original coefficient of covariate $X_i$, and $sd(cdot)$ refers to sample standard deviations.







                share|cite|improve this answer








                New contributor




                statslearner2 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.









                share|cite|improve this answer



                share|cite|improve this answer






                New contributor




                statslearner2 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.









                answered yesterday









                statslearner2

                645




                645




                New contributor




                statslearner2 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.





                New contributor





                statslearner2 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.






                statslearner2 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.






























                     

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