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.
regression estimation econometrics standardization
asked Nov 23 '18 at 18:03
divya gargdivya garg
163
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add a comment |
$begingroup$
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
asked Nov 23 '18 at 18:03
divya gargdivya garg
163
$endgroup$
add a comment |
$begingroup$
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
asked Nov 23 '18 at 18:03
divya gargdivya garg
163
$endgroup$
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
regression estimation econometrics standardization
asked Nov 23 '18 at 18:03
divya gargdivya garg
163
asked Nov 23 '18 at 18:03
divya gargdivya garg
163
asked Nov 23 '18 at 18:03
divya gargdivya garg
163
asked Nov 23 '18 at 18:03
divya gargdivya garg
163
asked Nov 23 '18 at 18:03
divya gargdivya garg
163
163
add a comment |
add a comment |
1 Answer
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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.
answered Nov 23 '18 at 18:49
statslearner2statslearner2
160114
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1 Answer
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active
oldest
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1 Answer
1
active
oldest
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$begingroup$
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.
answered Nov 23 '18 at 18:49
statslearner2statslearner2
160114
$endgroup$
add a comment |
$begingroup$
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.
answered Nov 23 '18 at 18:49
statslearner2statslearner2
160114
$endgroup$
add a comment |
$begingroup$
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.
answered Nov 23 '18 at 18:49
statslearner2statslearner2
160114
$endgroup$
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.
answered Nov 23 '18 at 18:49
statslearner2statslearner2
160114
answered Nov 23 '18 at 18:49
statslearner2statslearner2
160114
answered Nov 23 '18 at 18:49
statslearner2statslearner2
160114
answered Nov 23 '18 at 18:49
statslearner2statslearner2
160114
160114
add a comment |
add a comment |
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