52 research outputs found
Doubly Flexible Estimation under Label Shift
In studies ranging from clinical medicine to policy research, complete data
are usually available from a population , but the quantity of
interest is often sought for a related but different population
which only has partial data. In this paper, we consider the setting that both
outcome and covariate are available from whereas
only is available from , under the so-called label shift
assumption, i.e., the conditional distribution of given remains
the same across the two populations. To estimate the parameter of interest in
via leveraging the information from , the following
three ingredients are essential: (a) the common conditional distribution of
given , (b) the regression model of given in
, and (c) the density ratio of between the two populations. We
propose an estimation procedure that only needs standard nonparametric
technique to approximate the conditional expectations with respect to (a),
while by no means needs an estimate or model for (b) or (c); i.e., doubly
flexible to the possible model misspecifications of both (b) and (c). This is
conceptually different from the well-known doubly robust estimation in that,
double robustness allows at most one model to be misspecified whereas our
proposal can allow both (b) and (c) to be misspecified. This is of particular
interest in our setting because estimating (c) is difficult, if not impossible,
by virtue of the absence of the -data in . Furthermore, even
though the estimation of (b) is sometimes off-the-shelf, it can face curse of
dimensionality or computational challenges. We develop the large sample theory
for the proposed estimator, and examine its finite-sample performance through
simulation studies as well as an application to the MIMIC-III database
Evaluation of transplant benefits with the U.S. Scientific Registry of Transplant Recipients by semiparametric regression of mean residual life
Kidney transplantation is the most effective renal replacement therapy for
end stage renal disease patients. With the severe shortage of kidney supplies
and for the clinical effectiveness of transplantation, patient's life
expectancy post transplantation is used to prioritize patients for
transplantation; however, severe comorbidity conditions and old age are the
most dominant factors that negatively impact post-transplantation life
expectancy, effectively precluding sick or old patients from receiving
transplants. It would be crucial to design objective measures to quantify the
transplantation benefit by comparing the mean residual life with and without a
transplant, after adjusting for comorbidity and demographic conditions. To
address this urgent need, we propose a new class of semiparametric
covariate-dependent mean residual life models. Our method estimates covariate
effects semiparametrically efficiently and the mean residual life function
nonparametrically, enabling us to predict the residual life increment potential
for any given patient. Our method potentially leads to a more fair system that
prioritizes patients who would have the largest residual life gains. Our
analysis of the kidney transplant data from the U.S. Scientific Registry of
Transplant Recipients also suggests that a single index of covariates summarize
well the impacts of multiple covariates, which may facilitate interpretations
of each covariate's effect. Our subgroup analysis further disclosed
inequalities in survival gains across groups defined by race, gender and
insurance type (reflecting socioeconomic status).Comment: 68 pages, 13 figures. arXiv admin note: text overlap with
arXiv:2011.0406
Observation of forbidden phonons and dark excitons by resonance Raman scattering in few-layer WS
The optical properties of the two-dimensional (2D) crystals are dominated by
tightly bound electron-hole pairs (excitons) and lattice vibration modes
(phonons). The exciton-phonon interaction is fundamentally important to
understand the optical properties of 2D materials and thus help develop
emerging 2D crystal based optoelectronic devices. Here, we presented the
excitonic resonant Raman scattering (RRS) spectra of few-layer WS excited
by 11 lasers lines covered all of A, B and C exciton transition energies at
different sample temperatures from 4 to 300 K. As a result, we are not only
able to probe the forbidden phonon modes unobserved in ordinary Raman
scattering, but also can determine the bright and dark state fine structures of
1s A exciton. In particular, we also observed the quantum interference between
low-energy discrete phonon and exciton continuum under resonant excitation. Our
works pave a way to understand the exciton-phonon coupling and many-body
effects in 2D materials.Comment: 14 pages, 11 figure
Anomalous Frequency Trends in MoS2 Thin Films Attributed to Surface Effects
The layered dichalcogenide MoS2 has many unique physical properties in low
dimensions. Recent experimental Raman spectroscopies report an anomalous blue
shift of the in-plane E2g1 mode with decreasing thickness, a trend that is not
understood. Here, we combine experimental Raman scattering and theoretical
studies to clarify and explain this trend. Special attention is given to
understanding the surface effect on Raman frequencies by using a force
constants model based on first-principles calculations. Surface effects refer
to the larger Mo-S force constants at the surface of thin film MoS2, which
results from a loss of neighbours in adjacent MoS2 layers. Without surface
effects, the frequencies of both out-of-plane A1g and in-plane E2g1 modes
decrease with decreasing thickness. However, the E2g1 mode blue shifts while
the A1g mode red shifts once the surface effect is included, in agreement with
the experiment. Our results show that competition between the thickness effect
and the surface effect determines the mechanical properties of two-dimensional
MoS2, which we believe applies to other layered materials
A Nested Semiparametric Method for Case-control study with missingness
We propose a nested semiparametric model to analyze a case-control study where genuine case status is missing for some individuals. The concept of a noncase is introduced to allow for the imputation of the missing genuine cases. The odds ratio parameter of the genuine cases compared to controls is of interest. The imputation procedure predicts the probability of being a genuine case compared to a noncase semiparametrically in a dimension reduction fashion. This procedure is flexible, and vastly generalizes the existing methods. We establish the root-n asymptotic normality of the odds ratio parameter estimator. Our method yields stable odds ratio parameter estimation owing to the application of an efficient semiparametric sufficient dimension reduction estimator. We conduct finite sample numerical simulations to illustrate the performance of our approach, and apply it to a dilated cardiomyopathy study
Anomalous frequency trends in MoS2 thin films attributed to surface effects
10.1103/PhysRevB.88.075320Physical Review B - Condensed Matter and Materials Physics88
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