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gung - Reinstate Monica
gung - Reinstate Monica
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Using logistic regression for a continuous dependent variable

I got a revision for my research paper recently and the following is the reviewer's comment on my paper:

results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid.

Is the reviewer's comment right? Is logistic regression better thatthan multiple linear regression?

The problem is that my dependent variable is not categorical, it's a scale variable. What can I do now? What other regression method do you recommend to evaluate my model?

Score is dependent variable in the following table. Recency, frequency, tenure and last score are independent variables.

enter image description here

I've extracted these variables from a site and I hypothesize that these independent variables have significant effect on the score. Therefore, I represent the following models:

enter image description here

By the way, the value of R squared for this linear model is 0.316! The reviewer also commented on this value too:

then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted.

Is 0.316 very low for R squared? In previous papers I saw the similar values a lot.

enter image description here

Using logistic regression for continuous dependent variable

I got a revision for my research paper recently and the following is the reviewer's comment on my paper:

results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid.

Is the reviewer's comment right? Is logistic regression better that multiple linear regression?

The problem is that my dependent variable is not categorical, it's a scale variable. What can I do now? What other regression method do you recommend to evaluate my model?

Score is dependent variable in the following table. Recency, frequency, tenure and last score are independent variables.

enter image description here

I've extracted these variables from a site and I hypothesize that these independent variables have significant effect on the score. Therefore, I represent the following models:

enter image description here

By the way, the value of R squared for this linear model is 0.316! The reviewer also commented on this value too:

then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted.

Is 0.316 very low for R squared? In previous papers I saw the similar values a lot.

enter image description here

Using logistic regression for a continuous dependent variable

I got a revision for my research paper recently and the following is the reviewer's comment on my paper:

results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid.

Is the reviewer's comment right? Is logistic regression better than multiple linear regression?

The problem is that my dependent variable is not categorical, it's a scale variable. What can I do now? What other regression method do you recommend to evaluate my model?

Score is dependent variable in the following table. Recency, frequency, tenure and last score are independent variables.

enter image description here

I've extracted these variables from a site and I hypothesize that these independent variables have significant effect on the score. Therefore, I represent the following models:

enter image description here

By the way, the value of R squared for this linear model is 0.316! The reviewer also commented on this value too:

then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted.

Is 0.316 very low for R squared? In previous papers I saw the similar values a lot.

enter image description here

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Gala
Gala
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using Using logistic regression for continuous dependent variable

I got a revision for my research paper recently. and the following is the reviewer's comment on my paper:

"results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid."

results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid.

isIs the reviewer's comment right? isIs logistic regression better that multiple linear regression?

theThe problem is that my dependent variable is not categorical variable and, it's a scale variable. whatWhat can I do now? whatWhat other regression method do you recommend to evaluate my model?

scoreScore is dependent variable in the following table. recenecyRecency,frequency frequency,tenure tenure and last score are independent variables.   

enter image description here

I've extracted these variables from a site. and I hypothesize that these independent variables have significant effect on the score. thereforeTherefore, I represent the following models:

enter image description here

.................................................................

 

byBy the way, the value of R squared thatfor this linear regression model returns is 0.316  ! theThe reviewer also commentcommented on this value too: " then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted. "

then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted.

isIs 0.316 very low for R squared? inIn previous papers I saw the similar values a lot.

enter image description here

I'm looking forward for your replies :)

using logistic regression for continuous dependent variable

I got a revision for my research paper recently. and the following is the reviewer's comment on my paper:

"results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid."

is reviewer's comment right? is logistic regression better that multiple linear regression?

the problem is that my dependent variable is not categorical variable and it's scale variable. what can I do now? what other regression method do you recommend to evaluate my model?

score is dependent variable in the following table. recenecy,frequency,tenure and last score are independent variables.  enter image description here

I've extracted these variables from a site. and I hypothesize that these independent variables have significant effect on the score. therefore, I represent the following models:

enter image description here

.................................................................

by the way, the value of R squared that linear regression model returns is 0.316  ! the reviewer also comment on this value too: " then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted. "

is 0.316 very low for R squared? in previous papers I saw the similar values a lot.

enter image description here

I'm looking forward for your replies :)

Using logistic regression for continuous dependent variable

I got a revision for my research paper recently and the following is the reviewer's comment on my paper:

results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid.

Is the reviewer's comment right? Is logistic regression better that multiple linear regression?

The problem is that my dependent variable is not categorical, it's a scale variable. What can I do now? What other regression method do you recommend to evaluate my model?

Score is dependent variable in the following table. Recency, frequency, tenure and last score are independent variables. 

enter image description here

I've extracted these variables from a site and I hypothesize that these independent variables have significant effect on the score. Therefore, I represent the following models:

enter image description here

 

By the way, the value of R squared for this linear model is 0.316! The reviewer also commented on this value too:

then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted.

Is 0.316 very low for R squared? In previous papers I saw the similar values a lot.

enter image description here

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I got a revision for my research paper recently. and the following is the reviewer's comment on my paper:

"results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid."

is reviewer's comment right? is logistic regression better that multiple linear regression?

the problem is that my dependent variable is not categorical variable and it's scale variable. what can I do now? what other regression method do you recommend to evaluate my model?

score is dependent variable in the following table. recenecy,frequency,tenure and last score are independent variables. enter image description here

I've extracted these variables from a site. and I hypothesize that these independent variables have significant effect on the score. therefore, I represent the following models:

enter image description here

.................................................................

by the way, the value of R squared that linear regression model returns is 0.316 ! the reviewer also comment on this value too: " then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted. "

is 0.316 very low for R squared? in previous papers I saw the similar values a lot.

enter image description here

I'm looking forward for your replies :)

I got a revision for my research paper recently. and the following is the reviewer's comment on my paper:

"results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid."

is reviewer's comment right? is logistic regression better that multiple linear regression?

the problem is that my dependent variable is not categorical variable and it's scale variable. what can I do now? what other regression method do you recommend to evaluate my model?

score is dependent variable in the following table. recenecy,frequency,tenure and last score are independent variables. enter image description here

I've extracted these variables from a site. and I hypothesize that these independent variables have significant effect on the score. therefore, I represent the following models:

enter image description here

.................................................................

by the way, the value of R squared that linear regression model returns is 0.316 ! the reviewer also comment on this value too: " then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted. "

is 0.316 very low for R squared? in previous papers I saw the similar values a lot.

enter image description here

I got a revision for my research paper recently. and the following is the reviewer's comment on my paper:

"results obtained from one model is not quite convincing especially linear regression usually has deficiencies in dealing with outliers. I suggest the authors also try logistic regression and compare the corresponding results with current results. If the similar observations are obtained, the results would be more solid."

is reviewer's comment right? is logistic regression better that multiple linear regression?

the problem is that my dependent variable is not categorical variable and it's scale variable. what can I do now? what other regression method do you recommend to evaluate my model?

score is dependent variable in the following table. recenecy,frequency,tenure and last score are independent variables. enter image description here

I've extracted these variables from a site. and I hypothesize that these independent variables have significant effect on the score. therefore, I represent the following models:

enter image description here

.................................................................

by the way, the value of R squared that linear regression model returns is 0.316 ! the reviewer also comment on this value too: " then the results are not convincing as there is no indicator on the quality of learned coefficients. A small R^2 cannot indicate good performance as the model may be over-fitted. "

is 0.316 very low for R squared? in previous papers I saw the similar values a lot.

enter image description here

I'm looking forward for your replies :)

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PSS
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added 305 characters in body
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PSS
PSS
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PSS
PSS
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