Regression: Insignificant Intercept [duplicate]
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When is it ok to remove the intercept in a linear regression model?
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I ran a regression and the intercept is statistically insignificant (the p-value is greater than 0.05). I tried to look in some textbooks as to how to handle this scenario but I am still unsure. One textbook I looked at 'Basic Econometrics'by Gujarati and Porter says that if the intercept is insignificant then we have a regression through the origin and that if we remove the intercept, in this case, the model will be more precise. On the other hand, 'Introductory Econometrics'by Chris Brooks says that even if the intercept is insignificant, we should not remove it from the model.
Which one of these textbooks is correct? Should I leave the insignificant intercept in the model or run a regression through the origin?
regression linear-model intercept
asked Nov 26 at 2:17
user198848
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marked as duplicate by kjetil b halvorsen, Peter Flom♦ regression
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Nov 26 at 10:48
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
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This question already has an answer here:
When is it ok to remove the intercept in a linear regression model?
8 answers
I ran a regression and the intercept is statistically insignificant (the p-value is greater than 0.05). I tried to look in some textbooks as to how to handle this scenario but I am still unsure. One textbook I looked at 'Basic Econometrics'by Gujarati and Porter says that if the intercept is insignificant then we have a regression through the origin and that if we remove the intercept, in this case, the model will be more precise. On the other hand, 'Introductory Econometrics'by Chris Brooks says that even if the intercept is insignificant, we should not remove it from the model.
Which one of these textbooks is correct? Should I leave the insignificant intercept in the model or run a regression through the origin?
regression linear-model intercept
asked Nov 26 at 2:17
user198848
83
marked as duplicate by kjetil b halvorsen, Peter Flom♦ regression
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Nov 26 at 10:48
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
1
It bears mentioning that failure to detect a nonzero intercept is not the same thing as inferring that the intercept is actually zero.
– heropup
Nov 26 at 7:32
1
Why do you think this is a problem?
– kjetil b halvorsen
Nov 26 at 9:16
I don't think its a problem sorry. I re edited the question. Rather its a scenario I haven't encountered before.
– user198848
Nov 27 at 0:19
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
This question already has an answer here:
When is it ok to remove the intercept in a linear regression model?
8 answers
I ran a regression and the intercept is statistically insignificant (the p-value is greater than 0.05). I tried to look in some textbooks as to how to handle this scenario but I am still unsure. One textbook I looked at 'Basic Econometrics'by Gujarati and Porter says that if the intercept is insignificant then we have a regression through the origin and that if we remove the intercept, in this case, the model will be more precise. On the other hand, 'Introductory Econometrics'by Chris Brooks says that even if the intercept is insignificant, we should not remove it from the model.
Which one of these textbooks is correct? Should I leave the insignificant intercept in the model or run a regression through the origin?
regression linear-model intercept
asked Nov 26 at 2:17
user198848
83
This question already has an answer here:
When is it ok to remove the intercept in a linear regression model?
8 answers
I ran a regression and the intercept is statistically insignificant (the p-value is greater than 0.05). I tried to look in some textbooks as to how to handle this scenario but I am still unsure. One textbook I looked at 'Basic Econometrics'by Gujarati and Porter says that if the intercept is insignificant then we have a regression through the origin and that if we remove the intercept, in this case, the model will be more precise. On the other hand, 'Introductory Econometrics'by Chris Brooks says that even if the intercept is insignificant, we should not remove it from the model.
Which one of these textbooks is correct? Should I leave the insignificant intercept in the model or run a regression through the origin?
This question already has an answer here:
When is it ok to remove the intercept in a linear regression model?
8 answers
regression linear-model intercept
regression linear-model intercept
asked Nov 26 at 2:17
user198848
83
asked Nov 26 at 2:17
user198848
83
edited Nov 27 at 0:18
asked Nov 26 at 2:17
user198848
83
asked Nov 26 at 2:17
user198848
83
asked Nov 26 at 2:17
user198848
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83
marked as duplicate by kjetil b halvorsen, Peter Flom♦ regression
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Nov 26 at 10:48
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
marked as duplicate by kjetil b halvorsen, Peter Flom♦ regression
Users with the regression badge can single-handedly close regression questions as duplicates and reopen them as needed.
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Nov 26 at 10:48
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
1
It bears mentioning that failure to detect a nonzero intercept is not the same thing as inferring that the intercept is actually zero.
– heropup
Nov 26 at 7:32
1
Why do you think this is a problem?
– kjetil b halvorsen
Nov 26 at 9:16
I don't think its a problem sorry. I re edited the question. Rather its a scenario I haven't encountered before.
– user198848
Nov 27 at 0:19
add a comment |
1
It bears mentioning that failure to detect a nonzero intercept is not the same thing as inferring that the intercept is actually zero.
– heropup
Nov 26 at 7:32
1
Why do you think this is a problem?
– kjetil b halvorsen
Nov 26 at 9:16
I don't think its a problem sorry. I re edited the question. Rather its a scenario I haven't encountered before.
– user198848
Nov 27 at 0:19
1
1
It bears mentioning that failure to detect a nonzero intercept is not the same thing as inferring that the intercept is actually zero.
– heropup
Nov 26 at 7:32
It bears mentioning that failure to detect a nonzero intercept is not the same thing as inferring that the intercept is actually zero.
– heropup
Nov 26 at 7:32
1
1
Why do you think this is a problem?
– kjetil b halvorsen
Nov 26 at 9:16
Why do you think this is a problem?
– kjetil b halvorsen
Nov 26 at 9:16
I don't think its a problem sorry. I re edited the question. Rather its a scenario I haven't encountered before.
– user198848
Nov 27 at 0:19
I don't think its a problem sorry. I re edited the question. Rather its a scenario I haven't encountered before.
– user198848
Nov 27 at 0:19
add a comment |
1 Answer
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If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.
answered Nov 26 at 3:40
user158565
4,4291316
There are many reasons not to follow this advice. See stats.stackexchange.com/questions/102709/…
– kjetil b halvorsen
Nov 26 at 9:16
Thanks for the link. I read and saw that it was pointed out that the insignificance of the intercept is not enough to remove it from the model. So is it that we remove the intercept only when we have strong theoretical reason to believe that when x=0, y must also equal 0?
– user198848
Nov 27 at 0:26
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
2
down vote
If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.
answered Nov 26 at 3:40
user158565
4,4291316
There are many reasons not to follow this advice. See stats.stackexchange.com/questions/102709/…
– kjetil b halvorsen
Nov 26 at 9:16
Thanks for the link. I read and saw that it was pointed out that the insignificance of the intercept is not enough to remove it from the model. So is it that we remove the intercept only when we have strong theoretical reason to believe that when x=0, y must also equal 0?
– user198848
Nov 27 at 0:26
add a comment |
up vote
2
down vote
If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.
answered Nov 26 at 3:40
user158565
4,4291316
There are many reasons not to follow this advice. See stats.stackexchange.com/questions/102709/…
– kjetil b halvorsen
Nov 26 at 9:16
Thanks for the link. I read and saw that it was pointed out that the insignificance of the intercept is not enough to remove it from the model. So is it that we remove the intercept only when we have strong theoretical reason to believe that when x=0, y must also equal 0?
– user198848
Nov 27 at 0:26
add a comment |
up vote
2
down vote
up vote
2
down vote
If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.
answered Nov 26 at 3:40
user158565
4,4291316
If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.
answered Nov 26 at 3:40
user158565
4,4291316
answered Nov 26 at 3:40
user158565
4,4291316
answered Nov 26 at 3:40
user158565
4,4291316
answered Nov 26 at 3:40
user158565
4,4291316
4,4291316
There are many reasons not to follow this advice. See stats.stackexchange.com/questions/102709/…
– kjetil b halvorsen
Nov 26 at 9:16
Thanks for the link. I read and saw that it was pointed out that the insignificance of the intercept is not enough to remove it from the model. So is it that we remove the intercept only when we have strong theoretical reason to believe that when x=0, y must also equal 0?
– user198848
Nov 27 at 0:26
add a comment |
There are many reasons not to follow this advice. See stats.stackexchange.com/questions/102709/…
– kjetil b halvorsen
Nov 26 at 9:16
Thanks for the link. I read and saw that it was pointed out that the insignificance of the intercept is not enough to remove it from the model. So is it that we remove the intercept only when we have strong theoretical reason to believe that when x=0, y must also equal 0?
– user198848
Nov 27 at 0:26
There are many reasons not to follow this advice. See stats.stackexchange.com/questions/102709/…
– kjetil b halvorsen
Nov 26 at 9:16
There are many reasons not to follow this advice. See stats.stackexchange.com/questions/102709/…
– kjetil b halvorsen
Nov 26 at 9:16
Thanks for the link. I read and saw that it was pointed out that the insignificance of the intercept is not enough to remove it from the model. So is it that we remove the intercept only when we have strong theoretical reason to believe that when x=0, y must also equal 0?
– user198848
Nov 27 at 0:26
Thanks for the link. I read and saw that it was pointed out that the insignificance of the intercept is not enough to remove it from the model. So is it that we remove the intercept only when we have strong theoretical reason to believe that when x=0, y must also equal 0?
– user198848
Nov 27 at 0:26
add a comment |
1
It bears mentioning that failure to detect a nonzero intercept is not the same thing as inferring that the intercept is actually zero.
– heropup
Nov 26 at 7:32
1
Why do you think this is a problem?
– kjetil b halvorsen
Nov 26 at 9:16
I don't think its a problem sorry. I re edited the question. Rather its a scenario I haven't encountered before.
– user198848
Nov 27 at 0:19