Background Some heavy metals (eg, arsenic, cadmium, lead, mercury) have been
associated with obesity and obesity comorbidities. The analytical approach for those …

Nutrition influences health throughout the life course. Good nutrition increases the
probability of good pregnancy outcomes, proper childhood development, and healthy aging …

Much theoretical and applied work has been devoted to high-dimensional regression with
clean data. However, we often face corrupted data in many applications where missing data …

We continue our review of issues related to measurement error and misclassification in
epidemiology. We further describe methods of adjusting for biased estimation caused by …

The availability of large-scale datasets and sophisticated machine learning tools enables
develo** models that predict treatment outcomes for individual patients. However, few …

We consider the linear regression model with observation error in the design. In this setting,
we allow the number of covariates to be much larger than the sample size. Several new …

In many problems involving generalized linear models, the covariates are subject to
measurement error. When the number of covariates p exceeds the sample size n …

High-dimensional measurement error data are becoming more prevalent across various
fields. Research on measurement error regression models has gained momentum due to …

We study estimation and testing in the Poisson regression model with noisy high
dimensional covariates, which has wide applications in analyzing noisy big data. Correcting …

Suppose that we observe y∈R^n and X∈R^n*m in the following errors-in-variables model:
y&= &X_ 0 β^*+ ϵ\X&= &X_ 0+ W where X_0 is an n*m design matrix with independent …