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PubMed Journals Articles About "Control Based Imputation Sensitivity Analyses Informative Censoring Recurrent" RSS

02:10 EDT 25th June 2018 | BioPortfolio

Control Based Imputation Sensitivity Analyses Informative Censoring Recurrent PubMed articles on BioPortfolio. Our PubMed references draw on over 21 million records from the medical literature. Here you can see the latest Control Based Imputation Sensitivity Analyses Informative Censoring Recurrent articles that have been published worldwide.

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Showing "Control based imputation sensitivity analyses informative censoring recurrent" PubMed Articles 1–25 of 51,000+

GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies.

Left-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). Improper data processing procedures for missing values will cause adverse impacts on subsequent statistical analyses. However, few imputation methods have been developed and applied to the situation of MNAR in the field of metabolomics. Thus, a practical left-censored missing value imputation method is urgently needed. We developed an iterative Gibbs sampler based left-censore...


Multiple imputation of missing data in nested case-control and case-cohort studies.

The nested case-control and case-cohort designs are two main approaches for carrying out a substudy within a prospective cohort. This article adapts multiple imputation (MI) methods for handling missing covariates in full-cohort studies for nested case-control and case-cohort studies. We consider data missing by design and data missing by chance. MI analyses that make use of full-cohort data and MI analyses based on substudy data only are described, alongside an intermediate approach in which the imputation...

Imputation-Based HLA Typing with SNPs in GWAS Studies.

SNP-based imputation approaches for human leukocyte antigen (HLA) typing take advantage of the extended haplotype structure within the major histocompatibility complex (MHC) to predict classical HLA alleles using dense SNP genotypes, such as those available on chip panels of genome-wide association study (GWAS). These methods enable HLA analyses of classical alleles on existing SNP datasets genotyped in GWAS studies at no extra cost. Here, I describe the workflow of HIBAG, an imputation method with attribut...


3D-MICE: integration of cross-sectional and longitudinal imputation for multi-analyte longitudinal clinical data.

A key challenge in clinical data mining is that most clinical datasets contain missing data. Since many commonly used machine learning algorithms require complete datasets (no missing data), clinical analytic approaches often entail an imputation procedure to "fill in" missing data. However, although most clinical datasets contain a temporal component, most commonly used imputation methods do not adequately accommodate longitudinal time-based data. We sought to develop a new imputation algorithm, 3-dimensio...

Using a Counting Process Method to Impute Censored Follow-Up Time Data.

Censoring occurs when complete follow-up time information is unavailable for patients enrolled in a clinical study. The process is considered to be informative (non-ignorable) if the likelihood function for the model cannot be partitioned into a set of response parameters that are independent of the censoring parameters. In such cases, estimated survival time probabilities may be biased, prompting the need for special statistical methods to remedy the situation. The problem is especially salient when censor...

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data.

Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD)...

Prospective trial evaluating the sensitivity and specificity of 3,4-dihydroxy-6-18F-fluoro-L-phenylalanine (18F-DOPA) PET and MRI in patients with recurrent gliomas.

Treatment-related changes can be difficult to differentiate from progressive glioma using MRI with contrast (CE). The purpose of this study is to compare the sensitivity and specificity of 18F-DOPA-PET and MRI in patients with recurrent glioma. Thirteen patients with MRI findings suspicious for recurrent glioma were prospectively enrolled and underwent 18F-DOPA-PET and MRI for neurosurgical planning. Stereotactic biopsies were obtained from regions of concordant and discordant PET and MRI CE, all within reg...

Missing data in trial-based cost-effectiveness analysis: An incomplete journey.

Cost-effectiveness analyses (CEA) conducted alongside randomised trials provide key evidence for informing healthcare decision making, but missing data pose substantive challenges. Recently, there have been a number of developments in methods and guidelines addressing missing data in trials. However, it is unclear whether these developments have permeated CEA practice. This paper critically reviews the extent of and methods used to address missing data in recently published trial-based CEA. Issues of the He...

A Kriging based spatiotemporal approach for traffic volume data imputation.

Along with the rapid development of Intelligent Transportation Systems, traffic data collection technologies have progressed fast. The emergence of innovative data collection technologies such as remote traffic microwave sensor, Bluetooth sensor, GPS-based floating car method, and automated license plate recognition, has significantly increased the variety and volume of traffic data. Despite the development of these technologies, the missing data issue is still a problem that poses great challenge for data ...

Semiparametric estimation of the accelerated mean model with panel count data under informative examination times.

Panel count data arise when the number of recurrent events experienced by each subject is observed intermittently at discrete examination times. The examination time process can be informative about the underlying recurrent event process even after conditioning on covariates. We consider a semiparametric accelerated mean model for the recurrent event process and allow the two processes to be correlated through a shared frailty. The regression parameters have a simple marginal interpretation of modifying the...

Genotype imputation performance of three reference panels using African ancestry individuals.

Genotype imputation estimates unobserved genotypes from genome-wide makers, to increase genome coverage and power for genome-wide association studies. Imputation has been successful for European ancestry populations in which very large reference panels are available. Smaller subsets of African descent populations are available in 1000 Genomes (1000G), the Consortium on Asthma among African ancestry Populations in the Americas (CAAPA) and the Haplotype Reference Consortium (HRC). We compared the performance ...

GIGI-Quick: A Fast Approach to Impute Missing Genotypes in Genome-Wide Association Family Data.

Genome-wide association studies have become common over the last ten years, with a shift towards targeting rare variants, especially in pedigree-data. Despite lower costs, sequencing for rare variants still remains expensive. To have a relatively large sample with acceptable cost, imputation approaches may be used, such as GIGI for pedigree data. GIGI is an imputation method that handles large pedigrees and is particularly good for rare variant imputation. GIGI requires a subset of individuals in a pedigree...

Amyloid Beta Detection by Faradaic Electrochemical Impedance Spectroscopy Using Interdigitated Microelectrodes.

Faradaic electrochemical impedance spectroscopy (f-EIS) in the presence of redox reagent, e.g., [Fe(CN)₆]3-/4-, is widely used in biosensors owing to its high sensitivity. However, in sensors detecting amyloid beta (Aβ), the redox reagent can cause the aggregation of Aβ, which is a disturbance factor in accurate detection. Here, we propose an interdigitated microelectrode (IME) based f-EIS technique that can alleviate the aggregation of Aβ and achieve high sensitivity by buffer control. The proposed me...

Evaluation and application of summary statistic imputation to discover new height-associated loci.

As most of the heritability of complex traits is attributed to common and low frequency genetic variants, imputing them by combining genotyping chips and large sequenced reference panels is the most cost-effective approach to discover the genetic basis of these traits. Association summary statistics from genome-wide meta-analyses are available for hundreds of traits. Updating these to ever-increasing reference panels is very cumbersome as it requires reimputation of the genetic data, rerunning the associati...

Missing value imputation for LC-MS metabolomics data by incorporating metabolic network and adduct ion relations.

Metabolomics data generated from liquid chromatography-mass spectrometry (LC-MS) platforms often contain missing values. Existing imputation methods do not consider underlying feature relations and the metabolic network information. As a result, the imputation results may not be optimal.

The Impact of Missing Values and Single Imputation upon Rasch Analysis Outcomes: A Simulation Study.

Imputation becomes common practice through availability of easy-to-use algorithms and software. This study aims to determine if different imputation strategies are robust to the extent and type of missingness, local item dependencies (LID), differential item functioning (DIF), and misfit when doing a Rasch analysis. Four samples were simulated and represented a sample with good metric properties, a sample with LID, a sample with DIF, and a sample with LID and DIF. Missing values were generated with increasi...

Proportional hazard model estimation under dependent censoring using copulas and penalized likelihood.

This paper considers Cox proportional hazard models estimation under informative right censored data using maximum penalized likelihood, where dependence between censoring and event times are modelled by a copula function and a roughness penalty function is used to restrain the baseline hazard as a smooth function. Since the baseline hazard is nonnegative, we propose a special algorithm where each iteration involves updating regression coefficients by the Newton algorithm and baseline hazard by the multipli...

An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI.

Estimates of functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) are sensitive to artefacts caused by in-scanner head motion. This susceptibility has motivated the development of numerous denoising methods designed to mitigate motion-related artefacts. Here, we compare popular retrospective rs-fMRI denoising methods, such as regression of head motion parameters and mean white matter (WM) and cerebrospinal fluid (CSF) (with and without expansion terms), aCompCor...

full-FORCE: A target-based method for training recurrent networks.

Trained recurrent networks are powerful tools for modeling dynamic neural computations. We present a target-based method for modifying the full connectivity matrix of a recurrent network to train it to perform tasks involving temporally complex input/output transformations. The method introduces a second network during training to provide suitable "target" dynamics useful for performing the task. Because it exploits the full recurrent connectivity, the method produces networks that perform tasks with fewer ...

Shedding light on the association between repetitive negative thinking and deficits in cognitive control - A meta-analysis.

Individuals who experience recurrent negative thoughts are at elevated risk for mood and anxiety disorders. It is thus essential to understand why some individuals get stuck in recurrent negative thinking (RNT), whereas others are able to disengage eventually. Theoretical models propose that individuals high in recurrent negative thinking suffer from deficits in controlling the contents of working memory. Empirical findings, however, are inconclusive. In this meta-analysis, we synthesize findings from 94 st...

Diagnostic value of narrow-band imaging in detection of recurrent nasopharyngeal carcinoma.

Objective: To evaluate the diagnostic value and feasibility of narrow-band imaging in detection of recurrent nasopharyngeal carcinoma (NPC). Methods: One thousand three hundred and sixty-four NPC patients who had completed NPC treatment were enrolled. All patients were followed-up with imaging, serological examination of EB virus and nasopharyngeal endoscopy(WL and NBI mode), in which (1) both white light (WL) and NBI modes were done; (2) positive endoscopic patients were given nasopharyngeal biopsy; (3) us...

Recurrent post-tonsillectomy bleeding due to an iatrogenic facial artery pseudoaneurysm.

This is a report of an illustrative case of recurrent post-tonsillectomy bleeding that was caused by an iatrogenic facial artery pseudoaneurysm and controlled by endovascular embolization. A 37 year-old female who underwent bilateral tonsillectomy for chronic tonsillitis had recurrent secondary hemorrhage despite multiple operative interventions to control the bleeding. Because of the recurrent nature of the bleeding, an angiography of the external carotid artery was performed demonstrating a pseudoaneurysm...

Considerations of multiple imputation approaches for handling missing data in clinical trials.

Missing data exist in all clinical trials and missing data issue is a very serious issue in terms of the interpretability of the trial results. There is no universally applicable solution for all missing data problems. Methods used for handling missing data issue depend on the circumstances particularly the assumptions on missing data mechanisms. In recent years, if the missing at random mechanism cannot be assumed, conservative approaches such as the control-based and returning to baseline multiple imputat...

Extending CART-based Multiple Imputation with Gradient Boosting Machines.

A Multiple-Imputation "Forward Bridging" Approach to Address Changes in the Classification of Asian Race/Ethnicity on the US Death Certificate.

The incomparability of old and new classification systems for describing the same data can be seen as a missing-data problem, and, under certain assumptions, multiple imputation may be used to "bridge" 2 classification systems. One example of such a change is the introduction of detailed Asian-American race/ethnicity classifications on the 2003 version of the US national death certificate, which was adopted for use by 38 states between 2003 and 2011. Using county- and decedent-level data from 3 different na...


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