What precisely does it mean to borrow information?
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I often people them talk about information borrowing or information sharing in Bayesian hierarchical models. I can't seem to get a straight answer about what this actually means and if it is unique to Bayesian hierarchical models. I sort of get the idea: some levels in your hierarchy share a common parameter. I have no idea how this translates to "information borrowing" though.
Is "information borrowing"/ "information sharing" a buzz word people like to throw out?
Is there an example with closed form posteriors that illustrates this sharing phenomenon?
Is this unique to a Bayesian analysis? Generally, when I see examples of "information borrowing" they are just mixed models. Maybe I learned this models in an old fashioned way, but I don't see any sharing.
I am not interested in starting a philosophical debate about methods. I am just curious about the use of this term.
machine-learning bayesian multilevel-analysis terminology hierarchical-bayesian
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up vote
2
down vote
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I often people them talk about information borrowing or information sharing in Bayesian hierarchical models. I can't seem to get a straight answer about what this actually means and if it is unique to Bayesian hierarchical models. I sort of get the idea: some levels in your hierarchy share a common parameter. I have no idea how this translates to "information borrowing" though.
Is "information borrowing"/ "information sharing" a buzz word people like to throw out?
Is there an example with closed form posteriors that illustrates this sharing phenomenon?
Is this unique to a Bayesian analysis? Generally, when I see examples of "information borrowing" they are just mixed models. Maybe I learned this models in an old fashioned way, but I don't see any sharing.
I am not interested in starting a philosophical debate about methods. I am just curious about the use of this term.
machine-learning bayesian multilevel-analysis terminology hierarchical-bayesian
For your question 2., you may find this link illuminating: tjmahr.com/plotting-partial-pooling-in-mixed-effects-models.
– Isabella Ghement
1 hour ago
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up vote
2
down vote
favorite
up vote
2
down vote
favorite
I often people them talk about information borrowing or information sharing in Bayesian hierarchical models. I can't seem to get a straight answer about what this actually means and if it is unique to Bayesian hierarchical models. I sort of get the idea: some levels in your hierarchy share a common parameter. I have no idea how this translates to "information borrowing" though.
Is "information borrowing"/ "information sharing" a buzz word people like to throw out?
Is there an example with closed form posteriors that illustrates this sharing phenomenon?
Is this unique to a Bayesian analysis? Generally, when I see examples of "information borrowing" they are just mixed models. Maybe I learned this models in an old fashioned way, but I don't see any sharing.
I am not interested in starting a philosophical debate about methods. I am just curious about the use of this term.
machine-learning bayesian multilevel-analysis terminology hierarchical-bayesian
I often people them talk about information borrowing or information sharing in Bayesian hierarchical models. I can't seem to get a straight answer about what this actually means and if it is unique to Bayesian hierarchical models. I sort of get the idea: some levels in your hierarchy share a common parameter. I have no idea how this translates to "information borrowing" though.
Is "information borrowing"/ "information sharing" a buzz word people like to throw out?
Is there an example with closed form posteriors that illustrates this sharing phenomenon?
Is this unique to a Bayesian analysis? Generally, when I see examples of "information borrowing" they are just mixed models. Maybe I learned this models in an old fashioned way, but I don't see any sharing.
I am not interested in starting a philosophical debate about methods. I am just curious about the use of this term.
machine-learning bayesian multilevel-analysis terminology hierarchical-bayesian
machine-learning bayesian multilevel-analysis terminology hierarchical-bayesian
asked 4 hours ago
EliK
304112
304112
For your question 2., you may find this link illuminating: tjmahr.com/plotting-partial-pooling-in-mixed-effects-models.
– Isabella Ghement
1 hour ago
add a comment |
For your question 2., you may find this link illuminating: tjmahr.com/plotting-partial-pooling-in-mixed-effects-models.
– Isabella Ghement
1 hour ago
For your question 2., you may find this link illuminating: tjmahr.com/plotting-partial-pooling-in-mixed-effects-models.
– Isabella Ghement
1 hour ago
For your question 2., you may find this link illuminating: tjmahr.com/plotting-partial-pooling-in-mixed-effects-models.
– Isabella Ghement
1 hour ago
add a comment |
1 Answer
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Consider a simple problem like estimating means of multiple groups. If your model treats them as completely unrelated then the only information you have about each mean is the information within that group. If your model treats their means as somewhat related (such as in some mixed-effects type model) then the estimates will be more precise because information from other groups informs the estimate for a given group. That's an example of 'borrowing information'.
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1 Answer
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
3
down vote
Consider a simple problem like estimating means of multiple groups. If your model treats them as completely unrelated then the only information you have about each mean is the information within that group. If your model treats their means as somewhat related (such as in some mixed-effects type model) then the estimates will be more precise because information from other groups informs the estimate for a given group. That's an example of 'borrowing information'.
add a comment |
up vote
3
down vote
Consider a simple problem like estimating means of multiple groups. If your model treats them as completely unrelated then the only information you have about each mean is the information within that group. If your model treats their means as somewhat related (such as in some mixed-effects type model) then the estimates will be more precise because information from other groups informs the estimate for a given group. That's an example of 'borrowing information'.
add a comment |
up vote
3
down vote
up vote
3
down vote
Consider a simple problem like estimating means of multiple groups. If your model treats them as completely unrelated then the only information you have about each mean is the information within that group. If your model treats their means as somewhat related (such as in some mixed-effects type model) then the estimates will be more precise because information from other groups informs the estimate for a given group. That's an example of 'borrowing information'.
Consider a simple problem like estimating means of multiple groups. If your model treats them as completely unrelated then the only information you have about each mean is the information within that group. If your model treats their means as somewhat related (such as in some mixed-effects type model) then the estimates will be more precise because information from other groups informs the estimate for a given group. That's an example of 'borrowing information'.
answered 3 hours ago
Glen_b♦
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For your question 2., you may find this link illuminating: tjmahr.com/plotting-partial-pooling-in-mixed-effects-models.
– Isabella Ghement
1 hour ago