Sieve estimation in a Markov illness-death process under dual censoring

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Bioinformatics following peer review. The version of record Boruvka, Audrey and Cook, Richard J. (2016). Biostatistics, 17(2): 350-363. DOI: 10.1093/biostatistics/kxv042 is available online at: http://dx.doi.org/10.1093/biostatistics/kxv042Semiparametric methods are well-established for the analysis of a progressive Markov illness-death process observed up to a noninformative right censoring time. However often the intermediate and terminal events are censored in different ways, leading to a dual censoring scheme. In such settings unbiased estimation of the cumulative transition intensity functions cannot be achieved without some degree of smoothing. To overcome this problem we develop a sieve maximum likelihood approach for inference on the hazard ratio. A simulation study shows that the sieve estimator offers improved finite-sample performance over common imputation-based alternatives and is robust to some forms of dependent censoring. The proposed method is illustrated using data from cancer trials.Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626

Teaching Democracy Through Practice: Collaborative Governance on Campus

The Missouri School of Law Center for the Study of Dispute Resolution held a Symposium in Fall 2017 entitled “The First Amendment on Campus.” At the time, violent conflict had been erupting as marchers advocating white supremacy engaged in hate speech near college and university campuses. Participants in the Symposium sought to balance free speech and academic freedom with civility and respect for diverse viewpoints, while insuring safety in a learning community. The Symposium has made many important contributions to understanding how the field of dispute resolution can address this growing source of conflict

Semiparametric Methods for the Analysis of Progression-Related Endpoints

Use of progression-free survival in the evaluation of clinical interventions is hampered by a variety of issues, including censoring patterns not addressed in the usual methods for survival analysis. Progression can be right-censored before survival or interval-censored between inspection times. Current practice calls for imputing events to their time of detection. Such an approach is prone to bias, underestimates standard errors and makes inefficient use of the data at hand. Moreover a composite outcome prevents inference about the actual treatment effect on the risk of progression. This thesis develops semiparametric and sieve maximum likelihood estimators to more formally analyze progression-related endpoints. For the special case where death rarely precedes progression, a Cox-Aalen model is proposed for regression analysis of time-to-progression under intermittent inspection. The general setting considering both progression and survival is examined with a Markov Cox-type illness-death model under various censoring schemes. All of the resulting estimators globally converge to the truth slower than the parametric rate, but their finite-dimensional components are asymptotically efficient. Numerical studies suggest that the new methods perform better than their imputation-based alternatives under moderate to large samples having higher rates of censoring.1 yea

Satellite Imagery to Map Topsoil Organic Carbon Content over Cultivated Areas: An Overview

There is a need to update soil maps and monitor soil organic carbon (SOC) in the upper horizons or plough layer for enabling decision support and land management, while complying with several policies, especially those favoring soil carbon storage. This review paper is dedicated to the satellite-based spectral approaches for SOC assessment that have been achieved from several satellite sensors, study scales and geographical contexts in the past decade. Most approaches relying on pure spectral models have been carried out since 2019 and have dealt with temperate croplands in Europe, China and North America at the scale of small regions, of some hundreds of km(2): dry combustion and wet oxidation were the analytical determination methods used for 50% and 35% of the satellite-derived SOC studies, for which measured topsoil SOC contents mainly referred to mineral soils, typically cambisols and luvisols and to a lesser extent, regosols, leptosols, stagnosols and chernozems, with annual cropping systems with a SOC value of similar to 15 g.kg(-1) and a range of 30 g.kg(-1) in median. Most satellite-derived SOC spectral prediction models used limited preprocessing and were based on bare soil pixel retrieval after Normalized Difference Vegetation Index (NDVI) thresholding. About one third of these models used partial least squares regression (PLSR), while another third used random forest (RF), and the remaining included machine learning methods such as support vector machine (SVM). We did not find any studies either on deep learning methods or on all-performance evaluations and uncertainty analysis of spatial model predictions. Nevertheless, the literature examined here identifies satellite-based spectral information, especially derived under bare soil conditions, as an interesting approach that deserves further investigations. Future research includes considering the simultaneous analysis of imagery acquired at several dates i.e., temporal mosaicking, testing the influence of possible disturbing factors and mitigating their effects fusing mixed models incorporating non-spectral ancillary information

Shapes, contact angles, and line tensions of droplets on cylinders

Using an interface displacement model we calculate the shapes of nanometer-size liquid droplets on homogeneous cylindrical surfaces. We determine effective contact angles and line tensions, the latter defined as excess free energies per unit length associated with the two contact lines at the ends of the droplet. The dependences of these quantities on the cylinder radius and on the volume of the droplets are analyzed.Comment: 26 pages, RevTeX, 10 Figure

A Cox-Aalen model for interval-censored data

This is the peer reviewed version of the following article: Boruvka, A., and Cook, R. J. (2015), A Cox-Aalen Model for Interval-censored Data. Scand J Statist, 42, 414–426. doi: 10.1111/sjos.12113., which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/sjos.12113/full. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.The Cox-Aalen model, obtained by replacing the baseline hazard function in the well-known Cox model with a covariate-dependent Aalen model, allows for both fixed and dynamic covariate effects. In this paper, we examine maximum likelihood estimation for a Cox-Aalen model based on interval-censored failure times with fixed covariates. The resulting estimator globally converges to the truth slower than the parametric rate, but its finite-dimensional component is asymptotically efficient. Numerical studies show that estimation via a constrained Newton method performs well in terms of both finite sample properties and processing time for moderate-to-large samples with few covariates. We conclude with an application of the proposed methods to assess risk factors for disease progression in psoriatic arthritis.Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626

Selectivities of Potassium-Calcium and Potassium-Lead Exchange in Two Tropical Soils

Measurement of cation selectivity in soils provides important information about the affinity and binding strength of a particular cation on soil surfaces. Gaines-Thomas (KGT) selectivity coefficients were determined for a variety of K/Ca and K/Pb ratios on an Oxisol and Ultisol soil from Puerto Rico. The calculated KGT values indicated a preference for K+ over Ca2+ or Pb2+. The selectivity for Pb2+ was significantly greater than that for Ca2+ due to Pb2+\u27s larger hydrated charge density relative to that of Ca2+. The patterns of selectivity were independent of metal type. The selectivity of the Oxisol for Ca2+ or Pb2+ exhibited no trend and changed little with changes in divalent metal surface coverage. The Ultisol displayed a decrease in selectivity for Ca2+ and Pb2+ with increasing surface coverage of these ions. This was attributed to the presence of smectite in the Ultisol, which was able to partially collapse when K+ saturated. Some of the Pb sorption in the soils was due to chemisorption. The Oxisol chemisorbed 3000 mg Pb kg-1 while that value for the Ultisol was ≈1900 mg kg-1. The differences were due to the greater quantities of Fe/Al oxides and organic matter in the Oxisol relative to the Ultisol. Scanning electron microscopy-energy dispersive X-ray (SEM-EDX) spectroscopy detected discrete Pb-C phase in both soils. The C was from organic matter. Under experimental conditions, any Pb-carbonate phase would not have been stable. It was possible Pb was associated with organic sulfhydral groups. The selectivity exhibited by soil systems for various nutrient and heavy metals is important in elucidating how available these metals will be for plant/animal uptake as well as their mobility and stability in the soil environment