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Journal of the Royal Statistical Society. Series C, Applied Statistics

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https://www.readbyqxmd.com/read/29430064/survival-analysis-with-functions-of-mismeasured-covariate-histories-the-case-of-chronic-air-pollution-exposure-in-relation-to-mortality-in-the-nurses-health-study
#1
Xiaomei Liao, Xin Zhou, Molin Wang, Jaime E Hart, Francine Laden, Donna Spiegelman
Environmental epidemiologists are often interested in estimating the effect of functions of time-varying exposure histories, such as the 12-month moving average, in relation to chronic disease incidence or mortality. The individual exposure measurements that comprise such an exposure history are usually mis-measured, at least moderately, and, often, more substantially. To obtain unbiased estimates of Cox model hazard ratios for these complex mis-measured exposure functions, an extended risk set regression calibration method for Cox models is developed and applied to a study of long-term exposure to the fine particulate matter (PM2...
February 2018: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/29371746/clustered-multistate-models-with-observation-level-random-effects-mover-stayer-effects-and-dynamic-covariates-modelling-transition-intensities-and-sojourn-times-in-a-study-of-psoriatic-arthritis
#2
Sean Yiu, Vernon T Farewell, Brian D M Tom
In psoriatic arthritis, it is important to understand the joint activity (represented by swelling and pain) and damage processes because both are related to severe physical disability. The paper aims to provide a comprehensive investigation into both processes occurring over time, in particular their relationship, by specifying a joint multistate model at the individual hand joint level, which also accounts for many of their important features. As there are multiple hand joints, such an analysis will be based on the use of clustered multistate models...
February 2018: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/29353941/a-bayesian-model-selection-approach-for-identifying-differentially-expressed-transcripts-from-rna-sequencing-data
#3
Panagiotis Papastamoulis, Magnus Rattray
Recent advances in molecular biology allow the quantification of the transcriptome and scoring transcripts as differentially or equally expressed between two biological conditions. Although these two tasks are closely linked, the available inference methods treat them separately: a primary model is used to estimate expression and its output is post processed by using a differential expression model. In the paper, both issues are simultaneously addressed by proposing the joint estimation of expression levels and differential expression: the unknown relative abundance of each transcript can either be equal or not between two conditions...
January 2018: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/29249839/a-calibrated-power-prior-approach-to-borrow-information-from-historical-data-with-application-to-biosimilar-clinical-trials
#4
Haitao Pan, Ying Yuan, Jielai Xia
A biosimilar refers to a follow-on biologic intended to be approved for marketing based on biosimilarity to an existing patented biological product (i.e., the reference product). To develop a biosimilar product, it is essential to demonstrate biosimilarity between the follow-on biologic and the reference product, typically through two-arm randomization trials. We propose a Bayesian adaptive design for trials to evaluate biosimilar products. To take advantage of the abundant historical data on the efficacy of the reference product that is typically available at the time a biosimilar product is developed, we propose the calibrated power prior, which allows our design to adaptively borrow information from the historical data according to the congruence between the historical data and the new data collected from the current trial...
November 2017: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/29085158/phase-i-designs-that-allow-for-uncertainty-in-the-attribution-of-adverse-events
#5
Alexia Iasonos, John O'Quigley
In determining dose limiting toxicities in Phase I studies, it is necessary to attribute adverse events (AE) to being drug related or not. Such determination is subjective and may introduce bias. In this paper, we develop methods for removing or at least diminishing the impact of this bias on the estimation of the maximum tolerated dose (MTD). The approach we suggest takes into account the subjectivity in the attribution of AE by using model-based dose escalation designs. The results show that gains can be achieved in terms of accuracy by recovering information lost to biases...
November 2017: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/28943662/causal-mediation-analysis-for-the-cox-proportional-hazards-model-with-a-smooth-baseline-hazard-estimator
#6
Wei Wang, Jeffrey M Albert
An important problem within the social, behavioral, and health sciences is how to partition an exposure effect (e.g. treatment or risk factor) among specific pathway effects and to quantify the importance of each pathway. Mediation analysis based on the potential outcomes framework is an important tool to address this problem and we consider the estimation of mediation effects for the proportional hazards model in this paper. We give precise definitions of the total effect, natural indirect effect, and natural direct effect in terms of the survival probability, hazard function, and restricted mean survival time within the standard two-stage mediation framework...
August 2017: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/28785119/biomarker-detection-and-categorization-in-ribonucleic-acid-sequencing-meta-analysis-using-bayesian-hierarchical-models
#7
Tianzhou Ma, Faming Liang, George Tseng
Meta-analysis combining multiple transcriptomic studies increases statistical power and accuracy in detecting differentially expressed genes. As the next-generation sequencing experiments become mature and affordable, increasing number of RNA-seq datasets are available in the public domain. The count-data based technology provides better experimental accuracy, reproducibility and ability to detect low-expressed genes. A naive approach to combine multiple RNA-seq studies is to apply differential analysis tools such as edgeR and DESeq to each study and then combine the summary statistics of p-values or effect sizes by conventional meta-analysis methods...
August 2017: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/28706323/exploring-the-existence-of-a-stayer-population-with-mover-stayer-counting-process-models-application-to-joint-damage-in-psoriatic-arthritis
#8
Sean Yiu, Vernon T Farewell, Brian D M Tom
Many psoriatic arthritis patients do not progress to permanent joint damage in any of the 28 hand joints, even under prolonged follow-up. This has led several researchers to fit models that estimate the proportion of stayers (those who do not have the propensity to experience the event of interest) and to characterize the rate of developing damaged joints in the movers (those who have the propensity to experience the event of interest). However, when fitted to the same data, the paper demonstrates that the choice of model for the movers can lead to widely varying conclusions on a stayer population, thus implying that, if interest lies in a stayer population, a single analysis should not generally be adopted...
August 2017: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/28255183/parametric-dose-standardization-for-optimizing-two-agent-combinations-in-a-phase-i-ii-trial-with-ordinal-outcomes
#9
Peter F Thall, Hoang Q Nguyen, Ralph G Zinner
A Bayesian model and design are described for a phase I-II trial to jointly optimise the doses of a targeted agent and a chemotherapy agent for solid tumors. A challenge in designing the trial was that both the efficacy and toxicity outcomes were defined as four-level ordinal variables. To reflect possibly complex joint effects of the two doses on each of the two outcomes, for each marginal distribution a generalised continuation ratio model was assumed, with each agent's dose parametrically standardised in the linear term...
January 2017: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/28239197/linear-regression-with-a-randomly-censored-covariate-application-to-an-alzheimer-s-study
#10
Folefac D Atem, Jing Qian, Jacqueline E Maye, Keith A Johnson, Rebecca A Betensky
The association between maternal age of onset of dementia and amyloid deposition (measured by in vivo positron emission tomography (PET) imaging) in cognitively normal older offspring is of interest. In a regression model for amyloid, special methods are required due to the random right censoring of the covariate of maternal age of onset of dementia. Prior literature has proposed methods to address the problem of censoring due to assay limit of detection, but not random censoring. We propose imputation methods and a survival regression method that do not require parametric assumptions about the distribution of the censored covariate...
2017: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/28239196/a-novel-principal-component-analysis-for-spatially-misaligned-multivariate-air-pollution-data
#11
Roman A Jandarov, Lianne A Sheppard, Paul D Sampson, Adam A Szpiro
We propose novel methods for predictive (sparse) PCA with spatially misaligned data. These methods identify principal component loading vectors that explain as much variability in the observed data as possible, while also ensuring the corresponding principal component scores can be predicted accurately by means of spatial statistics at locations where air pollution measurements are not available. This will make it possible to identify important mixtures of air pollutants and to quantify their health effects in cohort studies, where currently available methods cannot be used...
January 2017: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/27789915/multipollutant-measurement-error-in-air-pollution-epidemiology-studies-arising-from-predicting-exposures-with-penalized-regression-splines
#12
Silas Bergen, Lianne Sheppard, Joel D Kaufman, Adam A Szpiro
Air pollution epidemiology studies are trending towards a multi-pollutant approach. In these studies, exposures at subject locations are unobserved and must be predicted using observed exposures at misaligned monitoring locations. This induces measurement error, which can bias the estimated health effects and affect standard error estimates. We characterize this measurement error and develop an analytic bias correction when using penalized regression splines to predict exposure. Our simulations show bias from multi-pollutant measurement error can be severe, and in opposite directions or simultaneously positive or negative...
November 2016: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/28461708/bayesian-inference-for-intratumour-heterogeneity-in-mutations-and-copy-number-variation
#13
Juhee Lee, Peter Müller, Subhajit Sengupta, Kamalakar Gulukota, Yuan Ji
Tumor samples are heterogeneous. They consist of different subclones that are characterized by differences in DNA nucleotide sequences and copy numbers on multiple loci. Heterogeneity can be measured through the identification of the subclonal copy number and sequence at a selected set of loci. Understanding that the accurate identification of variant allele fractions greatly depends on a precise determination of copy numbers, we develop a Bayesian feature allocation model for jointly calling subclonal copy numbers and the corresponding allele sequences for the same loci...
August 2016: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/27609994/multivariate-emulation-of-computer-simulators-model-selection-and-diagnostics-with-application-to-a-humanitarian-relief-model
#14
Antony M Overstall, David C Woods
We present a common framework for Bayesian emulation methodologies for multivariate output simulators, or computer models, that employ either parametric linear models or non-parametric Gaussian processes. Novel diagnostics suitable for multivariate covariance separable emulators are developed and techniques to improve the adequacy of an emulator are discussed and implemented. A variety of emulators are compared for a humanitarian relief simulator, modelling aid missions to Sicily after a volcanic eruption and earthquake, and a sensitivity analysis is conducted to determine the sensitivity of the simulator output to changes in the input variables...
August 2016: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/27524839/nonparametric-spatial-models-for-clustered-ordered-periodontal-data
#15
Dipankar Bandyopadhyay, Antonio Canale
Clinical attachment level (CAL) is regarded as the most popular measure to assess periodontal disease (PD). These probed tooth-site level measures are usually rounded and recorded as whole numbers (in mm) producing clustered (site measures within a mouth) error-prone ordinal responses representing some ordering of the underlying PD progression. In addition, it is hypothesized that PD progression can be spatially-referenced, i.e., proximal tooth-sites share similar PD status in comparison to sites that are distantly located...
August 2016: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/27134314/bayesian-hierarchical-modelling-for-inferring-genetic-interactions-in-yeast
#16
Jonathan Heydari, Conor Lawless, David A Lydall, Darren J Wilkinson
Quantitative fitness analysis (QFA) is a high throughput experimental and computational methodology for measuring the growth of microbial populations. QFA screens can be used to compare the health of cell populations with and without a mutation in a query gene to infer genetic interaction strengths genomewide, examining thousands of separate genotypes. We introduce Bayesian hierarchical models of population growth rates and genetic interactions that better reflect QFA experimental design than current approaches...
April 2016: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/27041773/two-stage-model-for-time-varying-effects-of-zero-in%C3%AF-ated-count-longitudinal-covariates-with-applications-in-health-behaviour-research
#17
Hanyu Yang, Runze Li, Robert A Zucker, Anne Buu
This study proposes a two-stage approach to characterize individual developmental trajectories of health risk behaviors and delineate their time-varying effects on short-term or long-term health outcomes. Our model can accommodate longitudinal covariates with zero-inflated counts and discrete outcomes. The longitudinal data of a well-known study of youth at high risk for substance abuse are presented as a motivating example to demonstrate the effectiveness of the model in delineating critical developmental periods of prevention and intervention...
April 2016: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/27041772/a-two-sample-distribution-free-test-for-functional-data-with-application-to-a-diffusion-tensor-imaging-study-of-multiple-sclerosis
#18
Gina-Maria Pomann, Ana-Maria Staicu, Sujit Ghosh
Motivated by an imaging study, this paper develops a nonparametric testing procedure for testing the null hypothesis that two samples of curves observed at discrete grids and with noise have the same underlying distribution. The objective is to formally compare white matter tract profiles between healthy individuals and multiple sclerosis patients, as assessed by conventional diffusion tensor imaging measures. We propose to decompose the curves using functional principal component analysis of a mixture process, which we refer to as marginal functional principal component analysis...
April 1, 2016: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/27546913/assessing-systematic-effects-of-stroke-on-motorcontrol-by-using-hierarchical-function-on-scalar-regression
#19
Jeff Goldsmith, Tomoko Kitago
This work is concerned with understanding common population-level effects of stroke on motor control while accounting for possible subject-level idiosyncratic effects. Upper extremity motor control for each subject is assessed through repeated planar reaching motions from a central point to eight pre-specified targets arranged on a circle. We observe the kinematic data for hand position as a bivariate function of time for each reach. Our goal is to estimate the bivariate function-on-scalar regression with subject-level random functional effects while accounting for potential correlation in residual curves; covariates of interest are severity of motor impairment and target number...
February 2016: Journal of the Royal Statistical Society. Series C, Applied Statistics
https://www.readbyqxmd.com/read/27034510/bayesian-group-sequential-clinical-trial-design-using-total-toxicity-burden-and-progression-free-survival
#20
Brian P Hobbs, Peter F Thall, Steven H Lin
Delivering radiation to eradicate a solid tumor while minimizing damage to nearby critical organs remains a challenge. For esophageal cancer, radiation therapy may damage the heart or lungs, and several qualitatively different, possibly recurrent toxicities associated with chemoradiation or surgery may occur, each at two or more possible grades. In this article, we describe a Bayesian group sequential clinical trial design, based on total toxicity burden (TTB) and progression-free survival duration, for comparing two radiation therapy modalities for esophageal cancer...
February 2016: Journal of the Royal Statistical Society. Series C, Applied Statistics
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