Xuming He

Bio: Xuming He is an academic researcher from University of Michigan. The author has contributed to research in topics: Estimator & Quantile regression. The author has an hindex of 52, co-authored 175 publications receiving 7519 citations. Previous affiliations of Xuming He include University of Rochester & Columbia University.

Quantile regression methods for reference growth charts.

Abstract: Estimation of reference growth curves for children's height and weight has traditionally relied on normal theory to construct families of quantile curves based on samples from the reference population. Age-specific parametric transformation has been used to significantly broaden the applicability of these normal theory methods. Non-parametric quantile regression methods offer a complementary strategy for estimating conditional quantile functions. We compare estimated reference curves for height using the penalized likelihood approach of Cole and Green (Statistics in Medicine 1992; 11:1305–1319) with quantile regression curves based on data used for modern Finnish reference charts. An advantage of the quantile regression approach is that it is relatively easy to incorporate prior growth and other covariates into the analysis of longitudinal growth data. Quantile specific autoregressive models for unequally spaced measurements are introduced and their application to diagnostic screening is illustrated. Copyright © 2005 John Wiley & Sons, Ltd.

Quantile Curves without Crossing

Abstract: Conventional regression techniques focus on the conditional averages, but often of more interest are lower or upper conditional quantiles. A more informative description of the relationship among variables can be obtained through regression quantiles (RQ). The percentile curves are usually computed one level at a time. Associated with great flexibility is the embarrassing phenomenon of quantile crossing. We propose a restricted version of regression quantiles (RRQ) that avoids the occurrence of crossing while maintaining sufficient modeling flexibility. RRQ remains in the general framework of the regression quantiles both conceptually and computationally. Because it relates all quantile functions through the conditional median, it also means substantial savings in computation costs when multiple quantiles for high-dimensional data are needed. Two examples in connection with the physical and engineering sciences are presented to demonstrate the usefulness of RRQ curves.

Estimation in a semiparametric model for longitudinal data with unspecified dependence structure

Abstract: This paper considers an extension of M-estimators in semiparametric models for independent observations to the case of longitudinal data. We approximate the nonparametric function by a regression spline, and any M-estimation algorithm for the usual linear models can then be used to obtain consistent estimators of the model and valid largesample inferences about the regression parameters without any specification of the error distribution and the covariance structure. Included as special cases are the analysis of the conditional mean and median functions for longitudinal data.

A general bahadur representation of M-estimators and its application to linear regression with nonstochastic designs

Abstract: We obtain strong Bahadur representations for a general class of M-estimators that satisfies $\Sigma_i \psi (x_i, \theta) = o(\delta_n)$, where the $x_i$'s are independent but not necessarily identically distributed random variables The results apply readily to M-estimators of regression with nonstochastic designs More specifically, we consider the minimum $L_p$ distance estimators, bounded influence GM-estimators and regression quantiles Under appropriate design conditions, the error ratesobtained for the first-order approximations are sharp in these cases We also provide weaker and more easily verifiable conditions that suffice for an error rate that is suboptimal but strong enough for deriving the asymptotic distribution of M-estimators in a wide variety of problems

Minfi: A flexible and comprehensive Bioconductor package for the analysis of Infinium DNA Methylation microarrays

Abstract: Motivation The recently released Infinium HumanMethylation450 array (the '450k' array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years. Results Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods. Availability and implementation http://bioconductor.org/packages/release/bioc/html/minfi.html. Contact khansen@jhsph.edu; rafa@jimmy.harvard.edu Supplementary information Supplementary data are available at Bioinformatics online.

Gut microbiota composition correlates with diet and health in the elderly

Abstract: Alterations in intestinal microbiota composition are associated with several chronic conditions, including obesity and inflammatory diseases. The microbiota of older people displays greater inter-individual variation than that of younger adults. Here we show that the faecal microbiota composition from 178 elderly subjects formed groups, correlating with residence location in the community, day-hospital, rehabilitation or in long-term residential care. However, clustering of subjects by diet separated them by the same residence location and microbiota groupings. The separation of microbiota composition significantly correlated with measures of frailty, co-morbidity, nutritional status, markers of inflammation and with metabolites in faecal water. The individual microbiota of people in long-stay care was significantly less diverse than that of community dwellers. Loss of community-associated microbiota correlated with increased frailty. Collectively, the data support a relationship between diet, microbiota and health status, and indicate a role for diet-driven microbiota alterations in varying rates of health decline upon ageing.