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 at 18:03
divya garg
163
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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.
regression estimation econometrics standardization
asked Nov 23 at 18:03
divya garg
163
add a comment |
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.
regression estimation econometrics standardization
asked Nov 23 at 18:03
divya garg
163
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 at 18:03
divya garg
163
asked Nov 23 at 18:03
divya garg
163
asked Nov 23 at 18:03
divya garg
163
asked Nov 23 at 18:03
divya garg
163
asked Nov 23 at 18:03
divya garg
163
163
add a comment |
add a comment |
1 Answer
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4
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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 at 18:49
statslearner2
14512
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
4
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.
answered Nov 23 at 18:49
statslearner2
14512
add a comment |
up vote
4
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.
answered Nov 23 at 18:49
statslearner2
14512
add a comment |
up vote
4
down vote
up vote
4
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.
answered Nov 23 at 18:49
statslearner2
14512
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 at 18:49
statslearner2
14512
answered Nov 23 at 18:49
statslearner2
14512
answered Nov 23 at 18:49
statslearner2
14512
answered Nov 23 at 18:49
statslearner2
14512
14512
add a comment |
add a comment |
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