Tagged Questions
1
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0answers
27 views
Is there a way to correct standard errors and/or prediction intervals for multiple comparison after doing backwards selection?
It is well known that most model selection algorithms can easily fall into a multiple comparison trap. To quote Friedman:
Consider developing a regression model in a context where substantive
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1
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0answers
73 views
Model comparison across multiple correlated responses
I have two multivariate linear regression models (multiple outcomes, i.e., the responses are a matrix), and I'm measuring their performance using $R^2$ in cross-validation, over these individual ...
3
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2answers
379 views
Following up a three-way interaction found with (mixed) model comparison
I hope this isn't a silly question, I'd like some advice on following up a threeway interaction in a mixed effects model. I've been building my models incrementally, like this:
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1
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2answers
315 views
Interaction term as a dependant variable in LMM with R
In a longitudinal study, two groups of subjects have been measured over a period of two years at 6 months intervals. During these measurements subjects have been assessed with a series of $k$ measures ...
5
votes
1answer
363 views
If a factor variable is to be dropped in model selection, should all levels be dropped simultaneously? If so, why?
In answer to a previous question factor pooling in model selection was discussed.
If a factor or categorical variable is to be dropped in model selection, should all levels be dropped simultaneously? ...
4
votes
2answers
179 views
Multiple comparisons for parameter significance in a sparse high dimensional regression model
I have a regularized linear regression model with a large number of parameters (~100,000) that has been optimized using a sparse fitting algorithm (coordinate descent with early stopping). The model ...
