Can the “vif” function in Stata be used to estimate collinearity in regression models?
I watched a video on collinearity and Stata, and it seems the author of the video is trying to get the variance inflation factor (vif) below 4, as a number above 4 would indicate collinearity. Is it this simple to assess the collinearity of my model, or is there more work to it?
I'll be honest and say I am struggling here with my project, containing regression analysis, and it seems for every answer I unlock, two more questions appear.
regression stata
edited Dec 2 '18 at 19:34
COOLSerdash
16k75192
asked Dec 2 '18 at 19:14
Paze
1696
add a comment |
I watched a video on collinearity and Stata, and it seems the author of the video is trying to get the variance inflation factor (vif) below 4, as a number above 4 would indicate collinearity. Is it this simple to assess the collinearity of my model, or is there more work to it?
I'll be honest and say I am struggling here with my project, containing regression analysis, and it seems for every answer I unlock, two more questions appear.
regression stata
edited Dec 2 '18 at 19:34
COOLSerdash
16k75192
asked Dec 2 '18 at 19:14
Paze
1696
3
It's unfortunately not that simple. Simple rules abound in statistics, but they are never universally true and following some of them will impair your abilities to analyze data. This is one of them. Assessing collinearity is somewhat tricky: entire books have been written about it. The best, and the one subsequently referenced by all those that followed, was Belsley, Kuh and Welsch, Regression Diagnostics (1980).
– whuber♦
Dec 2 '18 at 19:22
add a comment |
I watched a video on collinearity and Stata, and it seems the author of the video is trying to get the variance inflation factor (vif) below 4, as a number above 4 would indicate collinearity. Is it this simple to assess the collinearity of my model, or is there more work to it?
I'll be honest and say I am struggling here with my project, containing regression analysis, and it seems for every answer I unlock, two more questions appear.
regression stata
edited Dec 2 '18 at 19:34
COOLSerdash
16k75192
asked Dec 2 '18 at 19:14
Paze
1696
I watched a video on collinearity and Stata, and it seems the author of the video is trying to get the variance inflation factor (vif) below 4, as a number above 4 would indicate collinearity. Is it this simple to assess the collinearity of my model, or is there more work to it?
I'll be honest and say I am struggling here with my project, containing regression analysis, and it seems for every answer I unlock, two more questions appear.
regression stata
regression stata
edited Dec 2 '18 at 19:34
COOLSerdash
16k75192
asked Dec 2 '18 at 19:14
Paze
1696
edited Dec 2 '18 at 19:34
COOLSerdash
16k75192
asked Dec 2 '18 at 19:14
Paze
1696
edited Dec 2 '18 at 19:34
COOLSerdash
16k75192
edited Dec 2 '18 at 19:34
COOLSerdash
16k75192
edited Dec 2 '18 at 19:34
COOLSerdash
16k75192
16k75192
asked Dec 2 '18 at 19:14
Paze
1696
asked Dec 2 '18 at 19:14
Paze
1696
asked Dec 2 '18 at 19:14
Paze
1696
1696
3
It's unfortunately not that simple. Simple rules abound in statistics, but they are never universally true and following some of them will impair your abilities to analyze data. This is one of them. Assessing collinearity is somewhat tricky: entire books have been written about it. The best, and the one subsequently referenced by all those that followed, was Belsley, Kuh and Welsch, Regression Diagnostics (1980).
– whuber♦
Dec 2 '18 at 19:22
add a comment |
3
It's unfortunately not that simple. Simple rules abound in statistics, but they are never universally true and following some of them will impair your abilities to analyze data. This is one of them. Assessing collinearity is somewhat tricky: entire books have been written about it. The best, and the one subsequently referenced by all those that followed, was Belsley, Kuh and Welsch, Regression Diagnostics (1980).
– whuber♦
Dec 2 '18 at 19:22
3
3
It's unfortunately not that simple. Simple rules abound in statistics, but they are never universally true and following some of them will impair your abilities to analyze data. This is one of them. Assessing collinearity is somewhat tricky: entire books have been written about it. The best, and the one subsequently referenced by all those that followed, was Belsley, Kuh and Welsch, Regression Diagnostics (1980).
– whuber♦
Dec 2 '18 at 19:22
It's unfortunately not that simple. Simple rules abound in statistics, but they are never universally true and following some of them will impair your abilities to analyze data. This is one of them. Assessing collinearity is somewhat tricky: entire books have been written about it. The best, and the one subsequently referenced by all those that followed, was Belsley, Kuh and Welsch, Regression Diagnostics (1980).
– whuber♦
Dec 2 '18 at 19:22
add a comment |
1 Answer
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Questions about code are off-topic, but your question appears to be about colinearity.
Variance inflation factor (VIF) is, indeed, one way to measure colinearity. In my dissertation I gave evidence supporting David Belsley's work which showed that condition indexes and proportion of variance explained have some better properties, but VIF is still pretty good.
I didn't watch the video you linked to, but I'm a bit worried about "trying to get the VIF ....". There are various methods of dealing with colinearity, and which one you choose ought to depend on what you are trying to do. Among the options are:
- Partial least squares (a better option that principal components regression, in my opinion).
- Removing some variables
- Ridge regression
- Getting more data
I can sympathize with your last sentence. Statistics isn't simple.
answered Dec 2 '18 at 19:24
Peter Flom♦
74.2k11105202
2
Thank you. I'm an MD student hoping to pursue a PhD after my MD and it seems I have to get an entire new degree to even grasp the statistics part of my research. Is this stuff normally outsourced to statisticians?
– Paze
Dec 2 '18 at 19:29
3
It often is. Certainly once you graduate and start doing research. Sometimes while you are getting the PhD.
– Peter Flom♦
Dec 2 '18 at 19:32
add a comment |
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Questions about code are off-topic, but your question appears to be about colinearity.
Variance inflation factor (VIF) is, indeed, one way to measure colinearity. In my dissertation I gave evidence supporting David Belsley's work which showed that condition indexes and proportion of variance explained have some better properties, but VIF is still pretty good.
I didn't watch the video you linked to, but I'm a bit worried about "trying to get the VIF ....". There are various methods of dealing with colinearity, and which one you choose ought to depend on what you are trying to do. Among the options are:
- Partial least squares (a better option that principal components regression, in my opinion).
- Removing some variables
- Ridge regression
- Getting more data
I can sympathize with your last sentence. Statistics isn't simple.
answered Dec 2 '18 at 19:24
Peter Flom♦
74.2k11105202
2
Thank you. I'm an MD student hoping to pursue a PhD after my MD and it seems I have to get an entire new degree to even grasp the statistics part of my research. Is this stuff normally outsourced to statisticians?
– Paze
Dec 2 '18 at 19:29
3
It often is. Certainly once you graduate and start doing research. Sometimes while you are getting the PhD.
– Peter Flom♦
Dec 2 '18 at 19:32
add a comment |
Questions about code are off-topic, but your question appears to be about colinearity.
Variance inflation factor (VIF) is, indeed, one way to measure colinearity. In my dissertation I gave evidence supporting David Belsley's work which showed that condition indexes and proportion of variance explained have some better properties, but VIF is still pretty good.
I didn't watch the video you linked to, but I'm a bit worried about "trying to get the VIF ....". There are various methods of dealing with colinearity, and which one you choose ought to depend on what you are trying to do. Among the options are:
- Partial least squares (a better option that principal components regression, in my opinion).
- Removing some variables
- Ridge regression
- Getting more data
I can sympathize with your last sentence. Statistics isn't simple.
answered Dec 2 '18 at 19:24
Peter Flom♦
74.2k11105202
2
Thank you. I'm an MD student hoping to pursue a PhD after my MD and it seems I have to get an entire new degree to even grasp the statistics part of my research. Is this stuff normally outsourced to statisticians?
– Paze
Dec 2 '18 at 19:29
3
It often is. Certainly once you graduate and start doing research. Sometimes while you are getting the PhD.
– Peter Flom♦
Dec 2 '18 at 19:32
add a comment |
Questions about code are off-topic, but your question appears to be about colinearity.
Variance inflation factor (VIF) is, indeed, one way to measure colinearity. In my dissertation I gave evidence supporting David Belsley's work which showed that condition indexes and proportion of variance explained have some better properties, but VIF is still pretty good.
I didn't watch the video you linked to, but I'm a bit worried about "trying to get the VIF ....". There are various methods of dealing with colinearity, and which one you choose ought to depend on what you are trying to do. Among the options are:
- Partial least squares (a better option that principal components regression, in my opinion).
- Removing some variables
- Ridge regression
- Getting more data
I can sympathize with your last sentence. Statistics isn't simple.
answered Dec 2 '18 at 19:24
Peter Flom♦
74.2k11105202
Questions about code are off-topic, but your question appears to be about colinearity.
Variance inflation factor (VIF) is, indeed, one way to measure colinearity. In my dissertation I gave evidence supporting David Belsley's work which showed that condition indexes and proportion of variance explained have some better properties, but VIF is still pretty good.
I didn't watch the video you linked to, but I'm a bit worried about "trying to get the VIF ....". There are various methods of dealing with colinearity, and which one you choose ought to depend on what you are trying to do. Among the options are:
- Partial least squares (a better option that principal components regression, in my opinion).
- Removing some variables
- Ridge regression
- Getting more data
I can sympathize with your last sentence. Statistics isn't simple.
answered Dec 2 '18 at 19:24
Peter Flom♦
74.2k11105202
answered Dec 2 '18 at 19:24
Peter Flom♦
74.2k11105202
answered Dec 2 '18 at 19:24
Peter Flom♦
74.2k11105202
answered Dec 2 '18 at 19:24
Peter Flom♦
74.2k11105202
74.2k11105202
2
Thank you. I'm an MD student hoping to pursue a PhD after my MD and it seems I have to get an entire new degree to even grasp the statistics part of my research. Is this stuff normally outsourced to statisticians?
– Paze
Dec 2 '18 at 19:29
3
It often is. Certainly once you graduate and start doing research. Sometimes while you are getting the PhD.
– Peter Flom♦
Dec 2 '18 at 19:32
add a comment |
2
Thank you. I'm an MD student hoping to pursue a PhD after my MD and it seems I have to get an entire new degree to even grasp the statistics part of my research. Is this stuff normally outsourced to statisticians?
– Paze
Dec 2 '18 at 19:29
3
It often is. Certainly once you graduate and start doing research. Sometimes while you are getting the PhD.
– Peter Flom♦
Dec 2 '18 at 19:32
2
2
Thank you. I'm an MD student hoping to pursue a PhD after my MD and it seems I have to get an entire new degree to even grasp the statistics part of my research. Is this stuff normally outsourced to statisticians?
– Paze
Dec 2 '18 at 19:29
Thank you. I'm an MD student hoping to pursue a PhD after my MD and it seems I have to get an entire new degree to even grasp the statistics part of my research. Is this stuff normally outsourced to statisticians?
– Paze
Dec 2 '18 at 19:29
3
3
It often is. Certainly once you graduate and start doing research. Sometimes while you are getting the PhD.
– Peter Flom♦
Dec 2 '18 at 19:32
It often is. Certainly once you graduate and start doing research. Sometimes while you are getting the PhD.
– Peter Flom♦
Dec 2 '18 at 19:32
add a comment |
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3
It's unfortunately not that simple. Simple rules abound in statistics, but they are never universally true and following some of them will impair your abilities to analyze data. This is one of them. Assessing collinearity is somewhat tricky: entire books have been written about it. The best, and the one subsequently referenced by all those that followed, was Belsley, Kuh and Welsch, Regression Diagnostics (1980).
– whuber♦
Dec 2 '18 at 19:22