Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Regression with a right-censored predictor, using inverse probability
  weighting methods   In a longitudinal study, measures of key variables might be incomplete or
partially recorded due to drop-out, loss to follow-up, or early termination of
the study occurring before the advent of the event of interest. In this paper,
we focus primarily on the implementation of a regression model with a randomly
censored predictor. We examine, particularly, the use of inverse probability
weighting methods in a generalized linear model (GLM), when the predictor of
interest is right-censored, to adjust for censoring. To improve the performance
of the complete-case analysis and prevent selection bias, we consider three
different weighting schemes: inverse censoring probability weights,
Kaplan-Meier weights, and Cox proportional hazards weights. We use Monte Carlo
simulation studies to evaluate and compare the empirical properties of
different weighting estimation methods. Finally, we apply these methods to the
Framingham Heart Study data as an illustrative example to estimate the
relationship between age of onset of a clinically diagnosed cardiovascular
event and low-density lipoprotein (LDL) among cigarette smokers.

17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat