Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Improving estimation of the volume under the ROC surface when data are
  missing not at random   In this paper, we propose a mean score equation-based approach to estimate
the the volume under the receiving operating characteristic (ROC) surface (VUS)
of a diagnostic test, under nonignorable (NI) verification bias. The proposed
approach involves a parametric regression model for the verification process,
which accommodates for possible NI missingness in the disease status of sample
subjects, and may use instrumental variables, which help avoid possible
identifiability problems. In order to solve the mean score equation derived by
the chosen verification model, we preliminarily need to estimate the parameters
of a model for the disease process, but its specification is required only for
verified subjects under study. Then, by using the estimated verification and
disease probabilities, we obtain four verification bias-corrected VUS
estimators, which are alternative to those recently proposed by To Duc et al.
(2019), based on a full likelihood approach. Consistency and asymptotic
normality of the new estimators are established. Simulation experiments are
conducted to evaluate their finite sample performances, and an application to a
dataset from a research on epithelial ovarian cancer is presented.

5
The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th