Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Regression adjustment in completely randomized experiments with a
  diverging number of covariates   Randomized experiments have become important tools in empirical research. In
a completely randomized treatment-control experiment, the simple difference in
means of the outcome is unbiased for the average treatment effect, and
covariate adjustment can further improve the efficiency without assuming a
correctly specified outcome model. In modern applications, experimenters often
have access to many covariates, motivating the need for a theory of covariate
adjustment under the asymptotic regime with a diverging number of covariates.
We study the asymptotic properties of covariate adjustment under the potential
outcomes model and propose a bias-corrected estimator that is consistent and
asymptotically normal under weaker conditions. Our theory is purely
randomization-based without imposing any parametric outcome model assumptions.
To prove the theoretical results, we develop novel vector and matrix
concentration inequalities for sampling without replacement.

35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int