When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary: Difference between revisions

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'''Main Contributions of the Research Article:'''
'''Main Contributions of the Research Article:'''
1. The main result is a hypothesis test to evaluate whether pooling data across multiple sites for regression (before or after correcting for site-specific distributional shifts) can improve the estimation (mean squared error) of the relevant coefficients (while permitting an influence from a set of confounding variables).  
#The main result is a hypothesis test to evaluate whether pooling data across multiple sites for regression (before or after correcting for site-specific distributional shifts) can improve the estimation (mean squared error) of the relevant coefficients (while permitting an influence from a set of confounding variables).  
2. Show how pooling is can be used even when the features are different across sites. For this they show the L2-consistency rate which supports the use of spare-multi-task Lasso when sparsity patterns are not identical
#Show how pooling is can be used even when the features are different across sites. For this they show the L2-consistency rate which supports the use of spare-multi-task Lasso when sparsity patterns are not identical
3. Experimental results showing consistent acceptance power for early Alzheimer’s detection (AD) in humans.
#Experimental results showing consistent acceptance power for early Alzheimer’s detection (AD) in humans.

Revision as of 00:24, 24 October 2017

Main Contributions of the Research Article:

  1. The main result is a hypothesis test to evaluate whether pooling data across multiple sites for regression (before or after correcting for site-specific distributional shifts) can improve the estimation (mean squared error) of the relevant coefficients (while permitting an influence from a set of confounding variables).
  2. Show how pooling is can be used even when the features are different across sites. For this they show the L2-consistency rate which supports the use of spare-multi-task Lasso when sparsity patterns are not identical
  3. Experimental results showing consistent acceptance power for early Alzheimer’s detection (AD) in humans.
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