Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Infinite Diameter Confidence Sets in Hedges' Publication Bias Model   Meta-analysis, the statistical analysis of results from separate studies, is
a fundamental building block of science. But the assumptions of classical
meta-analysis models are not satisfied whenever publication bias is present,
which causes inconsistent parameter estimates. Hedges' selection function model
takes publication bias into account, but estimating and inferring with this
model is tough for some datasets. Using a generalized Gleser-Hwang theorem, we
show there is no confidence set of guaranteed finite diameter for the
parameters of Hedges' selection model. This result provides a partial
explanation for why inference with Hedges' selection model is fraught with
difficulties.

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The categories of this paper are: patt-sol
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
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The categories of this paper are: solv-int
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The categories of this paper are: supr-con
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The categories of this paper are: chem-ph
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The categories of this paper are: eess
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The categories of this paper are: hep-ex
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The categories of this paper are: chao-dyn
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The categories of this paper are: cond-mat
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The categories of this paper are: mtrl-th
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The categories of this paper are: acc-phys
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The categories of this paper are: dg-ga
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The categories of this paper are: bayes-an
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The categories of this paper are: physics