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https://www.readbyqxmd.com/read/28430872/optimal-screening-schedules-for-disease-progression-with-application-to-diabetic-retinopathy
#1
Ionut Bebu, John M Lachin
Clinical management of chronic diseases requires periodic evaluations. Subjects transition between various levels of severity of a disease over time, one of which may trigger an intervention that requires treatment. For example, in diabetic retinopathy, patients with type 1 diabetes are evaluated yearly for either the onset of proliferative diabetic retinopathy (PDR) or clinically significant macular edema (CSME) that would require immediate treatment to preserve vision. Herein, we investigate methods for the selection of personalized cost-effective screening schedules and compare them with a fixed visit schedule (e...
April 20, 2017: Biostatistics
https://www.readbyqxmd.com/read/28419189/propensity-scores-with-misclassified-treatment-assignment-a-likelihood-based-adjustment
#2
Danielle Braun, Malka Gorfine, Giovanni Parmigiani, Nils D Arvold, Francesca Dominici, Corwin Zigler
Propensity score methods are widely used in comparative effectiveness research using claims data. In this context, the inaccuracy of procedural or billing codes in claims data frequently misclassifies patients into treatment groups, that is, the treatment assignment ($T$) is often measured with error. In the context of a validation data where treatment assignment is accurate, we show that misclassification of treatment assignment can impact three distinct stages of a propensity score analysis: (i) propensity score estimation; (ii) propensity score implementation; and (iii) outcome analysis conducted conditional on the estimated propensity score and its implementation...
April 17, 2017: Biostatistics
https://www.readbyqxmd.com/read/28369273/computational-health-economics-for-identification-of-unprofitable-health-care-enrollees
#3
Sherri Rose, Savannah L Bergquist, Timothy J Layton
Health insurers may attempt to design their health plans to attract profitable enrollees while deterring unprofitable ones. Such insurers would not be delivering socially efficient levels of care by providing health plans that maximize societal benefit, but rather intentionally distorting plan benefits to avoid high-cost enrollees, potentially to the detriment of health and efficiency. In this work, we focus on a specific component of health plan design at risk for health insurer distortion in the Health Insurance Marketplaces: the prescription drug formulary...
March 22, 2017: Biostatistics
https://www.readbyqxmd.com/read/28369172/multivariate-t-nonlinear-mixed-models-with-application-to-censored-multi-outcome-aids-studies
#4
Tsung-I Lin, Wan-Lun Wang
In multivariate longitudinal HIV/AIDS studies, multi-outcome repeated measures on each patient over time may contain outliers, and the viral loads are often subject to a upper or lower limit of detection depending on the quantification assays. In this article, we consider an extension of the multivariate nonlinear mixed-effects model by adopting a joint multivariate-$t$ distribution for random effects and within-subject errors and taking the censoring information of multiple responses into account. The proposed model is called the multivariate-$t$ nonlinear mixed-effects model with censored responses (MtNLMMC), allowing for analyzing multi-outcome longitudinal data exhibiting nonlinear growth patterns with censorship and fat-tailed behavior...
March 20, 2017: Biostatistics
https://www.readbyqxmd.com/read/28369228/marginal-likelihood-estimation-of-negative-binomial-parameters-with-applications-to-rna-seq-data
#5
Luis León-Novelo, Claudio Fuentes, Sarah Emerson
RNA-Seq data characteristically exhibits large variances, which need to be appropriately accounted for in any proposed model. We first explore the effects of this variability on the maximum likelihood estimator (MLE) of the dispersion parameter of the negative binomial distribution, and propose instead to use an estimator obtained via maximization of the marginal likelihood in a conjugate Bayesian framework. We show, via simulation studies, that the marginal MLE can better control this variation and produce a more stable and reliable estimator...
March 19, 2017: Biostatistics
https://www.readbyqxmd.com/read/28369170/supervised-multiblock-sparse-multivariable-analysis-with-application-to-multimodal-brain-imaging-genetics
#6
Atsushi Kawaguchi, Fumio Yamashita
This article proposes a procedure for describing the relationship between high-dimensional data sets, such as multimodal brain images and genetic data. We propose a supervised technique to incorporate the clinical outcome to determine a score, which is a linear combination of variables with hieratical structures to multimodalities. This approach is expected to obtain interpretable and predictive scores. The proposed method was applied to a study of Alzheimer's disease (AD). We propose a diagnostic method for AD that involves using whole-brain magnetic resonance imaging (MRI) and positron emission tomography (PET), and we select effective brain regions for the diagnostic probability and investigate the genome-wide association with the regions using single nucleotide polymorphisms (SNPs)...
March 19, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334312/efficient-inference-for-genetic-association-studies-with-multiple-outcomes
#7
Helene Ruffieux, Anthony C Davison, Jorg Hager, Irina Irincheeva
Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on many genetic variants one by one, but there is an increasing demand for joint analysis of many molecular outcomes and genetic variants in order to unravel functional interactions. Unfortunately, most existing approaches to joint modeling are either too simplistic to be powerful or are impracticable for computational reasons...
March 16, 2017: Biostatistics
https://www.readbyqxmd.com/read/28369188/bayesian-inference-for-causal-mechanisms-with-application-to-a-randomized-study-for-postoperative-pain-control
#8
Michela Baccini, Alessandra Mattei, Fabrizia Mealli
We conduct principal stratification and mediation analysis to investigate to what extent the positive overall effect of treatment on postoperative pain control is mediated by postoperative self administration of intra-venous analgesia by patients in a prospective, randomized, double-blind study. Using the Bayesian approach for inference, we estimate both associative and dissociative principal strata effects arising in principal stratification, as well as natural effects from mediation analysis. We highlight that principal stratification and mediation analysis focus on different causal estimands, answer different causal questions, and involve different sets of structural assumptions...
March 15, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334305/variance-component-score-test-for-time-course-gene-set-analysis-of-longitudinal-rna-seq-data
#9
Denis Agniel, Boris P Hejblum
As gene expression measurement technology is shifting from microarrays to sequencing, the statistical tools available for their analysis must be adapted since RNA-seq data are measured as counts. It has been proposed to model RNA-seq counts as continuous variables using nonparametric regression to account for their inherent heteroscedasticity. In this vein, we propose tcgsaseq, a principled, model-free, and efficient method for detecting longitudinal changes in RNA-seq gene sets defined a priori. The method identifies those gene sets whose expression varies over time, based on an original variance component score test accounting for both covariates and heteroscedasticity without assuming any specific parametric distribution for the (transformed) counts...
March 10, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334261/penalized-likelihood-estimation-of-a-trivariate-additive-probit-model
#10
Panagiota Filippou, Giampiero Marra, Rosalba Radice
This article proposes a penalized likelihood method to estimate a trivariate probit model, which accounts for several types of covariate effects (such as linear, nonlinear, random, and spatial effects), as well as error correlations. The proposed approach also addresses the difficulty in estimating accurately the correlation coefficients, which characterize the dependence of binary responses conditional on covariates. The parameters of the model are estimated within a penalized likelihood framework based on a carefully structured trust region algorithm with integrated automatic multiple smoothing parameter selection...
March 4, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334230/guided-bayesian-imputation-to-adjust-for-confounding-when-combining-heterogeneous-data-sources-in-comparative-effectiveness-research
#11
Joseph Antonelli, Corwin Zigler, Francesca Dominici
In comparative effectiveness research, we are often interested in the estimation of an average causal effect from large observational data (the main study). Often this data does not measure all the necessary confounders. In many occasions, an extensive set of additional covariates is measured for a smaller and non-representative population (the validation study). In this setting, standard approaches for missing data imputation might not be adequate due to the large number of missing covariates in the main data relative to the smaller sample size of the validation data...
March 3, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334179/bayesian-distributed-lag-interaction-models-to-identify-perinatal-windows-of-vulnerability-in-children-s-health
#12
Ander Wilson, Yueh-Hsiu Mathilda Chiu, Hsiao-Hsien Leon Hsu, Robert O Wright, Rosalind J Wright, Brent A Coull
Epidemiological research supports an association between maternal exposure to air pollution during pregnancy and adverse children's health outcomes. Advances in exposure assessment and statistics allow for estimation of both critical windows of vulnerability and exposure effect heterogeneity. Simultaneous estimation of windows of vulnerability and effect heterogeneity can be accomplished by fitting a distributed lag model (DLM) stratified by subgroup. However, this can provide an incomplete picture of how effects vary across subgroups because it does not allow for subgroups to have the same window but different within-window effects or to have different windows but the same within-window effect...
February 27, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334131/pca-leverage-outlier-detection-for-high-dimensional-functional-magnetic-resonance-imaging-data
#13
Amanda F Mejia, Mary Beth Nebel, Ani Eloyan, Brian Caffo, Martin A Lindquist
Outlier detection for high-dimensional (HD) data is a popular topic in modern statistical research. However, one source of HD data that has received relatively little attention is functional magnetic resonance images (fMRI), which consists of hundreds of thousands of measurements sampled at hundreds of time points. At a time when the availability of fMRI data is rapidly growing-primarily through large, publicly available grassroots datasets-automated quality control and outlier detection methods are greatly needed...
February 27, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334368/performance-of-two-formal-tests-based-on-martingales-residuals-to-check-the-proportional-hazard-assumption-and-the-functional-form-of-the-prognostic-factors-in-flexible-parametric-excess-hazard-models
#14
Coraline Danieli, Nadine Bossard, Laurent Roche, Aurelien Belot, Zoe Uhry, Hadrien Charvat, Laurent Remontet
Net survival, the one that would be observed if the disease under study was the only cause of death, is an important, useful, and increasingly used indicator in public health, especially in population-based studies. Estimates of net survival and effects of prognostic factor can be obtained by excess hazard regression modeling. Whereas various diagnostic tools were developed for overall survival analysis, few methods are available to check the assumptions of excess hazard models. We propose here two formal tests to check the proportional hazard assumption and the validity of the functional form of the covariate effects in the context of flexible parametric excess hazard modeling...
February 26, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334132/maximum-likelihood-estimation-and-em-algorithm-of-copas-like-selection-model-for-publication-bias-correction
#15
Jing Ning, Yong Chen, Jin Piao
Publication bias occurs when the published research results are systematically unrepresentative of the population of studies that have been conducted, and is a potential threat to meaningful meta-analysis. The Copas selection model provides a flexible framework for correcting estimates and offers considerable insight into the publication bias. However, maximizing the observed likelihood under the Copas selection model is challenging because the observed data contain very little information on the latent variable...
February 25, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334081/reply-to-towfic-and-others-letter-to-the-editor
#16
Vegard Nygaard, Einar Andreas Rødland, Eivind Hovig
No abstract text is available yet for this article.
February 20, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334077/a-powerful-and-efficient-two-stage-method-for-detecting-gene-to-gene-interactions-in-gwas
#17
Jakub Pecanka, Marianne A Jonker, Zoltan Bochdanovits, Aad W Van Der Vaart
For over a decade functional gene-to-gene interaction (epistasis) has been suspected to be a determinant in the "missing heritability" of complex traits. However, searching for epistasis on the genome-wide scale has been challenging due to the prohibitively large number of tests which result in a serious loss of statistical power as well as computational challenges. In this article, we propose a two-stage method applicable to existing case-control data sets, which aims to lessen both of these problems by pre-assessing whether a candidate pair of genetic loci is involved in epistasis before it is actually tested for interaction with respect to a complex phenotype...
February 6, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334062/overcoming-confounding-plate-effects-in-differential-expression-analyses-of-single-cell-rna-seq-data
#18
Aaron T L Lun, John C Marioni
An increasing number of studies are using single-cell RNA-sequencing (scRNA-seq) to characterize the gene expression profiles of individual cells. One common analysis applied to scRNA-seq data involves detecting differentially expressed (DE) genes between cells in different biological groups. However, many experiments are designed such that the cells to be compared are processed in separate plates or chips, meaning that the groupings are confounded with systematic plate effects. This confounding aspect is frequently ignored in DE analyses of scRNA-seq data...
February 6, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334061/instrumental-variable-estimation-of-causal-odds-ratios-using-structural-nested-mean-models
#19
Roland A Matsouaka, Eric J Tchetgen Tchetgen
We consider estimating causal odds ratios using an instrumental variable under a logistic structural nested mean model (LSNMM). Current methods for LSNMMs either rely heavily on possible "uncongenial" modeling assumptions or involve intricate numerical challenges, which have impeded their use. In this article, we present an alternative method that ensures a congenial parametrization, circumvents computational complexity of existing methods, and is easy to implement. We illustrate the proposed method to (1) estimate the causal effect of years of education on earnings using data from the NLSYM and (2) assess the impact of moving families from high to low-poverty neighborhoods had on lifetime major depressive disorder among adolescents in the "Moving to Opportunity (MTO) for Fair Housing Demonstration Project" from the Department of Housing and Urban Development...
February 6, 2017: Biostatistics
https://www.readbyqxmd.com/read/28375451/multivariate-semiparametric-spatial-methods-for-imaging-data
#20
Huaihou Chen, Guanqun Cao, Ronald A Cohen
Univariate semiparametric methods are often used in modeling nonlinear age trajectories for imaging data, which may result in efficiency loss and lower power for identifying important age-related effects that exist in the data. As observed in multiple neuroimaging studies, age trajectories show similar nonlinear patterns for the left and right corresponding regions and for the different parts of a big organ such as the corpus callosum. To incorporate the spatial similarity information without assuming spatial smoothness, we propose a multivariate semiparametric regression model with a spatial similarity penalty, which constrains the variation of the age trajectories among similar regions...
April 1, 2017: Biostatistics
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