Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Kernel Test for Causal Association via Noise Contrastive Backdoor
  Adjustment   Causal inference grows increasingly complex as the number of confounders
increases. Given treatments $X$, confounders $Z$ and outcomes $Y$, we develop a
non-parametric method to test the \textit{do-null} hypothesis $H_0:\;
p(y|\text{\it do}(X=x))=p(y)$ against the general alternative. Building on the
Hilbert Schmidt Independence Criterion (HSIC) for marginal independence
testing, we propose backdoor-HSIC (bd-HSIC) and demonstrate that it is
calibrated and has power for both binary and continuous treatments under a
large number of confounders. Additionally, we establish convergence properties
of the estimators of covariance operators used in bd-HSIC. We investigate the
advantages and disadvantages of bd-HSIC against parametric tests as well as the
importance of using the do-null testing in contrast to marginal independence
testing or conditional independence testing. A complete implementation can be
found at
\hyperlink{https://github.com/MrHuff/kgformula}{\texttt{https://github.com/MrHuff/kgformula}}.

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The categories of this paper are: gr-qc
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The categories of this paper are: cmp-lg
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The categories of this paper are: physics
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-th
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The categories of this paper are: funct-an
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The categories of this paper are: patt-sol
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The categories of this paper are: econ
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The categories of this paper are: astro-ph
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The categories of this paper are: q-alg
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The categories of this paper are: acc-phys
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The categories of this paper are: quant-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: math-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: bayes-an