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International Journal of Biostatistics

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https://www.readbyqxmd.com/read/29906269/a-fast-and-robust-way-to-estimate-overlap-of-niches-and-draw-inference
#1
Judith H Parkinson, Raoul Kutil, Jonas Kuppler, Robert R Junker, Wolfgang Trutschnig, Arne C Bathke
The problem of quantifying the overlap of Hutchinsonian niches has received much attention lately, in particular in quantitative ecology, from where it also originates. However, the niche concept has the potential to also be useful in many other application areas, as for example in economics. We are presenting a fully nonparametric, robust solution to this problem, along with exact shortcut formulas based on rank-statistics, and with a rather intuitive probabilistic interpretation. Furthermore, by deriving the asymptotic sampling distribution of the estimators, we are proposing the first asymptotically valid inference method, providing confidence intervals for the niche overlap...
June 15, 2018: International Journal of Biostatistics
https://www.readbyqxmd.com/read/29878883/unfolding-the-genome-the-case-study-of-p-falciparum
#2
Nelle Varoquaux
The development of new ways to probe samples for the three-dimensional (3D) structure of DNA paves the way for in depth and systematic analyses of the genome architecture. 3C-like methods coupled with high-throughput sequencing can now assess physical interactions between pairs of loci in a genome-wide fashion, thus enabling the creation of genome-by-genome contact maps. The spreading of such protocols creates many new opportunities for methodological development: how can we infer 3D models from these contact maps? Can such models help us gain insights into biological processes? Several recent studies applied such protocols to P...
June 7, 2018: International Journal of Biostatistics
https://www.readbyqxmd.com/read/29621006/a-bayesian-framework-for-estimating-the-concordance-correlation-coefficient-using-skew-elliptical-distributions
#3
Dai Feng, Richard Baumgartner, Vladimir Svetnik
The concordance correlation coefficient (CCC) is a widely used scaled index in the study of agreement. In this article, we propose estimating the CCC by a unified Bayesian framework that can (1) accommodate symmetric or asymmetric and light- or heavy-tailed data; (2) select model from several candidates; and (3) address other issues frequently encountered in practice such as confounding covariates and missing data. The performance of the proposal was studied and demonstrated using simulated as well as real-life biomarker data from a clinical study of an insomnia drug...
April 5, 2018: International Journal of Biostatistics
https://www.readbyqxmd.com/read/29883322/marginal-structural-models-with-counterfactual-effect-modifiers
#4
Wenjing Zheng, Zhehui Luo, Mark J van der Laan
In health and social sciences, research questions often involve systematic assessment of the modification of treatment causal effect by patient characteristics. In longitudinal settings, time-varying or post-intervention effect modifiers are also of interest. In this work, we investigate the robust and efficient estimation of the Counterfactual-History-Adjusted Marginal Structural Model (van der Laan MJ, Petersen M. Statistical learning of origin-specific statically optimal individualized treatment rules. Int J Biostat...
June 8, 2018: International Journal of Biostatistics
https://www.readbyqxmd.com/read/29676993/nonparametric-interval-estimators-for-the-coefficient-of-variation
#5
Dongliang Wang, Margaret K Formica, Song Liu
The coefficient of variation (CV) is a widely used scaleless measure of variability in many disciplines. However the inference for the CV is limited to parametric methods or standard bootstrap. In this paper we propose two nonparametric methods aiming to construct confidence intervals for the coefficient of variation. The first one is to apply the empirical likelihood after transforming the original data. The second one is a modified jackknife empirical likelihood method. We also propose bootstrap procedures for calibrating the test statistics...
April 19, 2018: International Journal of Biostatistics
https://www.readbyqxmd.com/read/29517976/notes-on-test-and-estimation-in-comparison-of-three-treatments-under-a-simple-carry-over-three-period-model
#6
Kung-Jong Lui
Under the three-treatment three-period crossover design with simple carry-over effects, we derive the least-squares estimators for period effects, treatment effects and carry-over effects, as well as their covariance matrix in closed and explicit expressions. Using Monte Carlo simulation, we compare the test procedure adjusting carry-over with that ignoring carry-over with respect to Type I error and power. We further compare interval estimators adjusting carry-over with those ignoring carry-over with respect to the coverage probability and the average length...
March 7, 2018: International Journal of Biostatistics
https://www.readbyqxmd.com/read/29389664/joint-models-of-longitudinal-and-time-to-event-data-with-more-than-one-event-time-outcome-a-review
#7
Graeme L Hickey, Pete Philipson, Andrea Jorgensen, Ruwanthi Kolamunnage-Dona
Methodological development and clinical application of joint models of longitudinal and time-to-event outcomes have grown substantially over the past two decades. However, much of this research has concentrated on a single longitudinal outcome and a single event time outcome. In clinical and public health research, patients who are followed up over time may often experience multiple, recurrent, or a succession of clinical events. Models that utilise such multivariate event time outcomes are quite valuable in clinical decision-making...
January 31, 2018: International Journal of Biostatistics
https://www.readbyqxmd.com/read/29306919/zero-inflated-conway-maxwell-poisson-distribution-to-analyze-discrete-data
#8
Shin Zhu Sim, Ramesh C Gupta, Seng Huat Ong
In this paper, we study the zero-inflated Conway-Maxwell Poisson (ZICMP) distribution and develop a regression model. Score and likelihood ratio tests are also implemented for testing the inflation/deflation parameter. Simulation studies are carried out to examine the performance of these tests. A data example is presented to illustrate the concepts. In this example, the proposed model is compared to the well-known zero-inflated Poisson (ZIP) and the zero- inflated generalized Poisson (ZIGP) regression models...
January 9, 2018: International Journal of Biostatistics
https://www.readbyqxmd.com/read/29023235/a-generally-efficient-targeted-minimum-loss-based-estimator-based-on-the-highly-adaptive-lasso
#9
Mark van der Laan
Suppose we observe n $n$ independent and identically distributed observations of a finite dimensional bounded random variable. This article is concerned with the construction of an efficient targeted minimum loss-based estimator (TMLE) of a pathwise differentiable target parameter of the data distribution based on a realistic statistical model. The only smoothness condition we will enforce on the statistical model is that the nuisance parameters of the data distribution that are needed to evaluate the canonical gradient of the pathwise derivative of the target parameter are multivariate real valued cadlag functions (right-continuous and left-hand limits, (G...
October 12, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28961139/adaptation-of-chain-event-graphs-for-use-with-case-control-studies-in-epidemiology
#10
Claire Keeble, Peter Adam Thwaites, Stuart Barber, Graham Richard Law, Paul David Baxter
Case-control studies are used in epidemiology to try to uncover the causes of diseases, but are a retrospective study design known to suffer from non-participation and recall bias, which may explain their decreased popularity in recent years. Traditional analyses report usually only the odds ratio for given exposures and the binary disease status. Chain event graphs are a graphical representation of a statistical model derived from event trees which have been developed in artificial intelligence and statistics, and only recently introduced to the epidemiology literature...
September 26, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28953454/a-comparison-of-methods-for-estimating-the-determinant-of-high-dimensional-covariance-matrix
#11
Zongliang Hu, Kai Dong, Wenlin Dai, Tiejun Tong
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix...
September 21, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28930628/estimation-and-inference-for-the-mediation-proportion
#12
Daniel Nevo, Xiaomei Liao, Donna Spiegelman
In epidemiology, public health and social science, mediation analysis is often undertaken to investigate the extent to which the effect of a risk factor on an outcome of interest is mediated by other covariates. A pivotal quantity of interest in such an analysis is the mediation proportion. A common method for estimating it, termed the "difference method", compares estimates from models with and without the hypothesized mediator. However, rigorous methodology for estimation and statistical inference for this quantity has not previously been available...
September 20, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28686573/modelling-mixed-types-of-outcomes-in-additive-genetic-models
#13
Wagner Hugo Bonat
We present a general statistical modelling framework for handling multivariate mixed types of outcomes in the context of quantitative genetic analysis. The models are based on the multivariate covariance generalized linear models, where the matrix linear predictor is composed of an identity matrix combined with a relatedness matrix defined by a pedigree, representing the environmental and genetic components, respectively. We also propose a new index of heritability for non-Gaussian data. A case study on house sparrow (Passer domesticus) population with continuous, binomial and count outcomes is employed to motivate the new model...
July 7, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28628480/kernel-based-measure-of-variable-importance-for-genetic-association-studies
#14
Vicente Gallego, M Luz Calle, Ramon Oller
The identification of genetic variants that are associated with disease risk is an important goal of genetic association studies. Standard approaches perform univariate analysis where each genetic variant, usually Single Nucleotide Polymorphisms (SNPs), is tested for association with disease status. Though many genetic variants have been identified and validated so far using this univariate approach, for most complex diseases a large part of their genetic component is still unknown, the so called missing heritability...
June 17, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28672773/generalized-confidence-intervals-for-intra-and-inter-subject-coefficients-of-variation-in-linear-mixed-effects-models
#15
Johannes Forkman
Linear mixed-effects models are linear models with several variance components. Models with a single random-effects factor have two variance components: the random-effects variance, i. e., the inter-subject variance, and the residual error variance, i. e., the intra-subject variance. In many applications, it is practice to report variance components as coefficients of variation. The intra- and inter-subject coefficients of variation are the square roots of the corresponding variances divided by the mean...
June 15, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28599385/big-data-small-sample
#16
Inna Gerlovina, Mark J van der Laan, Alan Hubbard
Multiple comparisons and small sample size, common characteristics of many types of "Big Data" including those that are produced by genomic studies, present specific challenges that affect reliability of inference. Use of multiple testing procedures necessitates calculation of very small tail probabilities of a test statistic distribution. Results based on large deviation theory provide a formal condition that is necessary to guarantee error rate control given practical sample sizes, linking the number of tests and the sample size; this condition, however, is rarely satisfied...
May 20, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28541924/characterizing-highly-benefited-patients-in-randomized-clinical-trials
#17
Vivek Charu, Paul B Rosenberg, Lon S Schneider, Lea T Drye, Lisa Rein, David Shade, Constantine G Lyketsos, Constantine E Frangakis
Physicians and patients may choose a certain treatment only if it is predicted to have a large effect for the profile of that patient. We consider randomized controlled trials in which the clinical goal is to identify as many patients as possible that can highly benefit from the treatment. This is challenging with large numbers of covariate profiles, first, because the theoretical, exact method is not feasible, and, second, because usual model-based methods typically give incorrect results. Better, more recent methods use a two-stage approach, where a first stage estimates a working model to produce a scalar predictor of the treatment effect for each covariate profile; and a second stage estimates empirically a high-benefit group based on the first-stage predictor...
May 20, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28541925/improvement-screening-for-ultra-high-dimensional-data-with-censored-survival-outcomes-and-varying-coefficients
#18
Mu Yue, Jialiang Li
Motivated by risk prediction studies with ultra-high dimensional bio markers, we propose a novel improvement screening methodology. Accurate risk prediction can be quite useful for patient treatment selection, prevention strategy or disease management in evidence-based medicine. The question of how to choose new markers in addition to the conventional ones is especially important. In the past decade, a number of new measures for quantifying the added value from the new markers were proposed, among which the integrated discrimination improvement (IDI) and net reclassification improvement (NRI) stand out...
May 18, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28525350/comparing-four-methods-for-estimating-tree-based-treatment-regimes
#19
Aniek Sies, Iven Van Mechelen
When multiple treatment alternatives are available for a certain psychological or medical problem, an important challenge is to find an optimal treatment regime, which specifies for each patient the most effective treatment alternative given his or her pattern of pretreatment characteristics. The focus of this paper is on tree-based treatment regimes, which link an optimal treatment alternative to each leaf of a tree; as such they provide an insightful representation of the decision structure underlying the regime...
May 12, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28493818/group-tests-for-high-dimensional-failure-time-data-with-the-additive-hazards-models
#20
Dandan Jiang, Jianguo Sun
Statistical analysis of high-dimensional data has been attracting more and more attention due to the abundance of such data in various fields such as genetic studies or genomics and the existence of many interesting topics. Among them, one is the identification of a gene or genes that have significant effects on the occurrence of or are significantly related to a certain disease. In this paper, we will discuss such a problem that can be formulated as a group test or testing a group of variables or coefficients when one faces right-censored failure time response variable...
May 9, 2017: International Journal of Biostatistics
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