We provide an overview of linear quantile regression models for continuous responses
repeatedly measured over time. We distinguish between marginal approaches, that explicitly …

With few exceptions crown profile models for coniferous trees have conventionally been
estimated within the least squares framework that is confined to describing the central trend …

Background Exposure data with repeated measures from occupational studies are
frequently right-skewed and left-censored. To address right-skewed data, data are generally …

An M-quantile regression model is developed for the analysis of multiple dependent
outcomes by introducing the notion of directional M-quantiles for multivariate responses. In …

This paper presents a unified framework for supervised learning and inference procedures
using the divide-and-conquer approach for high-dimensional correlated outcomes. We …

Background In studies of occupational health, longitudinal environmental exposure, and
biomonitoring data are often subject to right skewing and left censoring, in which …

It is well known that the composite quantile regression is a very useful tool for regression
analysis. In longitudinal studies, it requires a correct specification of the covariance structure …

In many biomedical studies independent variables may affect the conditional distribution of
the response differently in the middle as opposed to the upper or lower tail. Quantile …

Introduction The use of digital biomarker data in dementia research provides the opportunity
for frequent cognitive and functional assessments that was not previously available using …

Information from related source studies can often enhance the findings of a target study.
However, the distribution shift between target and source studies can severely impact the …