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Biostatistics

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https://www.readbyqxmd.com/read/28637279/high-dimensional-multivariate-mediation-with-application-to-neuroimaging-data
#1
Oliver Y Chén, Ciprian Crainiceanu, Elizabeth L Ogburn, Brian S Caffo, Tor D Wager, Martin A Lindquist
Mediation analysis is an important tool in the behavioral sciences for investigating the role of intermediate variables that lie in the path between a treatment and an outcome variable. The influence of the intermediate variable on the outcome is often explored using a linear structural equation model (LSEM), with model coefficients interpreted as possible effects. While there has been significant research on the topic, little work has been done when the intermediate variable (mediator) is a high-dimensional vector...
June 15, 2017: Biostatistics
https://www.readbyqxmd.com/read/28633320/discussion-is-fda-in-need-of-a-major-change-in-the-way-it-regulates
#2
Janet Wittes
No abstract text is available yet for this article.
June 12, 2017: Biostatistics
https://www.readbyqxmd.com/read/28633317/discussion-is-the-fda-in-need-of-a-major-change-in-the-way-it-regulates
#3
Alex Tabarrok
No abstract text is available yet for this article.
June 12, 2017: Biostatistics
https://www.readbyqxmd.com/read/28633316/discussion-is-the-fda-in-need-of-a-major-change-in-the-way-it-regulates
#4
Geert Molenberghs
No abstract text is available yet for this article.
June 12, 2017: Biostatistics
https://www.readbyqxmd.com/read/28633313/discussion-new-directions-for-the-fda-in-the-21st-century
#5
Andrew W Lo
No abstract text is available yet for this article.
June 12, 2017: Biostatistics
https://www.readbyqxmd.com/read/28633307/discussion-the-role-position-and-function-of-the-fda-the-past-present-and-future
#6
Thomas R Fleming, David L Demets, Lisa M McShane
No abstract text is available yet for this article.
June 12, 2017: Biostatistics
https://www.readbyqxmd.com/read/28633289/discussion-is-the-fda-in-need-of-a-major-change-in-the-way-it-regulates
#7
Susan S Ellenberg
No abstract text is available yet for this article.
June 12, 2017: Biostatistics
https://www.readbyqxmd.com/read/28605411/estimating-causal-effects-from-a-randomized-clinical-trial-when-noncompliance-is-measured-with-error
#8
Jeffrey A Boatman, David M Vock, Joseph S Koopmeiners, Eric C Donny
Noncompliance or non-adherence to randomized treatment is a common challenge when interpreting data from randomized clinical trials. The effect of an intervention if all participants were forced to comply with the assigned treatment (i.e., the causal effect) is often of primary scientific interest. For example, in trials of very low nicotine content (VLNC) cigarettes, policymakers are interested in their effect on smoking behavior if their use were to be compelled by regulation. A variety of statistical methods to estimate the causal effect of an intervention have been proposed, but these methods, including inverse probability of compliance weighted (IPCW) estimators, assume that participants' compliance statuses are reported without error...
June 12, 2017: Biostatistics
https://www.readbyqxmd.com/read/28586407/a-bayesian-hierarchical-model-for-network-meta-analysis-of-multiple-diagnostic-tests
#9
Xiaoye Ma, Qinshu Lian, Haitao Chu, Joseph G Ibrahim, Yong Chen
To compare the accuracy of multiple diagnostic tests in a single study, three designs are commonly used (i) the multiple test comparison design; (ii) the randomized design, and (iii) the non-comparative design. Existing meta-analysis methods of diagnostic tests (MA-DT) have been focused on evaluating the performance of a single test by comparing it with a reference test. The increasing number of available diagnostic instruments for a disease condition and the different study designs being used have generated the need to develop efficient and flexible meta-analysis framework to combine all designs for simultaneous inference...
June 6, 2017: Biostatistics
https://www.readbyqxmd.com/read/28541380/a-fully-bayesian-latent-variable-model-for-integrative-clustering-analysis-of-multi-type-omics-data
#10
Qianxing Mo, Ronglai Shen, Cui Guo, Marina Vannucci, Keith S Chan, Susan G Hilsenbeck
Identification of clinically relevant tumor subtypes and omics signatures is an important task in cancer translational research for precision medicine. Large-scale genomic profiling studies such as The Cancer Genome Atlas (TCGA) Research Network have generated vast amounts of genomic, transcriptomic, epigenomic, and proteomic data. While these studies have provided great resources for researchers to discover clinically relevant tumor subtypes and driver molecular alterations, there are few computationally efficient methods and tools for integrative clustering analysis of these multi-type omics data...
May 24, 2017: Biostatistics
https://www.readbyqxmd.com/read/28525542/semiparametric-model-and-inference-for-spontaneous-abortion-data-with-a-cured-proportion-and-biased-sampling
#11
Jin Piao, Jing Ning, Christina D Chambers, Ronghui Xu
Evaluating and understanding the risk and safety of using medications for autoimmune disease in a woman during her pregnancy will help both clinicians and pregnant women to make better treatment decisions. However, utilizing spontaneous abortion (SAB) data collected in observational studies of pregnancy to derive valid inference poses two major challenges. First, the data from the observational cohort are not random samples of the target population due to the sampling mechanism. Pregnant women with early SAB are more likely to be excluded from the cohort, and there may be substantial differences between the observed SAB time and those in the target population...
May 18, 2017: Biostatistics
https://www.readbyqxmd.com/read/28520903/covariate-adjusted-classification-trees
#12
Josephine K Asafu-Adjei, Allan R Sampson
In studies that compare several diagnostic groups, subjects can be measured on certain features and classification trees can be used to identify which of them best characterize the differences among groups. However, subjects may also be measured on additional covariates whose ability to characterize group differences is not meaningful or of interest, but may still have an impact on the examined features. Therefore, it is important to adjust for the effects of covariates on these features. We present a new semi-parametric approach to adjust for covariate effects when constructing classification trees based on the features of interest that is readily implementable...
May 17, 2017: Biostatistics
https://www.readbyqxmd.com/read/28520893/using-bayesian-modeling-in-frequentist-adaptive-enrichment-designs
#13
Noah Simon, Richard Simon
Our increased understanding of the mechanistic heterogeneity of diseases has pushed the development of targeted therapeutics. We do not expect all patients with a given disease to benefit from a targeted drug; only those in the target population. That is, those with sufficient dysregulation in the biomolecular pathway targeted by treatment. However, due to complexity of the pathway, and/or technical issues with our characterizing assay, it is often hard to characterize the target population until well into large-scale clinical trials...
May 17, 2017: Biostatistics
https://www.readbyqxmd.com/read/28481968/concordance-measure-and-discriminatory-accuracy-in-transformation-cure-models
#14
Yilong Zhang, Yongzhao Shao
Many populations of early-stage cancer patients have non-negligible latent cure fractions that can be modeled using transformation cure models. However, there is a lack of statistical metrics to evaluate prognostic utility of biomarkers in this context due to the challenges associated with unknown cure status and heavy censorship. In this article, we develop general concordance measures as evaluation metrics for the discriminatory accuracy of transformation cure models including the so-called promotion time cure models and mixture cure models...
May 5, 2017: Biostatistics
https://www.readbyqxmd.com/read/28430872/optimal-screening-schedules-for-disease-progression-with-application-to-diabetic-retinopathy
#15
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
#16
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/28375451/multivariate-semiparametric-spatial-methods-for-imaging-data
#17
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
https://www.readbyqxmd.com/read/28025183/inequality-in-treatment-benefits-can-we-determine-if-a-new-treatment-benefits-the-many-or-the-few
#18
Emily J Huang, Ethan X Fang, Daniel F Hanley, Michael Rosenblum
In many randomized controlled trials, the primary analysis focuses on the average treatment effect and does not address whether treatment benefits are widespread or limited to a select few. This problem affects many disease areas, since it stems from how randomized trials, often the gold standard for evaluating treatments, are designed and analyzed. Our goal is to learn about the fraction who benefit from a new treatment using randomized trial data. We consider the case where the outcome is ordinal, with binary outcomes as a special case...
April 1, 2017: Biostatistics
https://www.readbyqxmd.com/read/28025182/incorporating-social-contact-data-in-spatio-temporal-models-for-infectious-disease-spread
#19
Sebastian Meyer, Leonhard Held
Routine public health surveillance of notifiable infectious diseases gives rise to weekly counts of reported cases-possibly stratified by region and/or age group. We investigate how an age-structured social contact matrix can be incorporated into a spatio-temporal endemic-epidemic model for infectious disease counts. To illustrate the approach, we analyze the spread of norovirus gastroenteritis over six age groups within the 12 districts of Berlin, 2011-2015, using contact data from the POLYMOD study. The proposed age-structured model outperforms alternative scenarios with homogeneous or no mixing between age groups...
April 1, 2017: Biostatistics
https://www.readbyqxmd.com/read/28025181/a-rigorous-statistical-framework-for-spatio-temporal-pollution-prediction-and-estimation-of-its-long-term-impact-on-health
#20
Duncan Lee, Sabyasachi Mukhopadhyay, Alastair Rushworth, Sujit K Sahu
In the United Kingdom, air pollution is linked to around 40000 premature deaths each year, but estimating its health effects is challenging in a spatio-temporal study. The challenges include spatial misalignment between the pollution and disease data; uncertainty in the estimated pollution surface; and complex residual spatio-temporal autocorrelation in the disease data. This article develops a two-stage model that addresses these issues. The first stage is a spatio-temporal fusion model linking modeled and measured pollution data, while the second stage links these predictions to the disease data...
April 1, 2017: Biostatistics
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