Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Integrative High Dimensional Multiple Testing with Heterogeneity under
  Data Sharing Constraints   Identifying informative predictors in a high dimensional regression model is
a critical step for association analysis and predictive modeling. Signal
detection in the high dimensional setting often fails due to the limited sample
size. One approach to improve power is through meta-analyzing multiple studies
on the same scientific question. However, integrative analysis of high
dimensional data from multiple studies is challenging in the presence of
between study heterogeneity. The challenge is even more pronounced with
additional data sharing constraints under which only summary data but not
individual level data can be shared across different sites. In this paper, we
propose a novel data shielding integrative large-scale testing (DSILT) approach
to signal detection by allowing between study heterogeneity and not requiring
sharing of individual level data. Assuming the underlying high dimensional
regression models of the data differ across studies yet share similar support,
the DSILT approach incorporates proper integrative estimation and debiasing
procedures to construct test statistics for the overall effects of specific
covariates. We also develop a multiple testing procedure to identify
significant effects while controlling for false discovery rate (FDR) and false
discovery proportion (FDP). Theoretical comparisons of the DSILT procedure with
the ideal individual--level meta--analysis (ILMA) approach and other
distributed inference methods are investigated. Simulation studies demonstrate
that the DSILT procedure performs well in both false discovery control and
attaining power. The proposed method is applied to a real example on detecting
interaction effect of the genetic variants for statins and obesity on the risk
for Type 2 Diabetes.

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The categories of this paper are: solv-int
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The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
27
The categories of this paper are: comp-gas
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The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-ex
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The categories of this paper are: math
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: patt-sol
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The categories of this paper are: nucl-th
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The categories of this paper are: bayes-an