Missing value imputation for epistatic MAPs

LENUS (Irish Health Repository)

Ryan, Colm

2010-04-20

Abstract Background Epistatic miniarray profiling (E-MAPs) is a high-throughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from E-MAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values - up to 35% - that can reduce the effectiveness of some data analysis techniques and prevent the use of others. An effective method for imputing interactions would therefore increase the types of possible analysis, as well as increase the potential to identify novel functional interactions between gene pairs. Several methods have been developed to handle missing values in microarray data, but it is unclear how applicable these methods are to E-MAP data because of their pairwise nature and the significantly larger number of missing values. Here we evaluate four alternative imputation strategies, three local (Nearest neighbor-based) and one global (PCA-based), that have been modified to work with symmetric pairwise data. Results We identify different categories for the missing data based on their underlying cause, and show that values from the largest category can be imputed effectively. We compare local and global imputation approaches across a variety of distinct E-MAP datasets, showing that both are competitive and preferable to filling in with zeros. In addition we show that these methods are effective in an E-MAP from a different species, suggesting that pairwise imputation techniques will be increasingly useful as analogous epistasis mapping techniques are developed in different species. We show that strongly alleviating interactions are significantly more difficult to predict than strongly aggravating interactions. Finally we show that imputed interactions, generated using nearest neighbor methods, are enriched for annotations in the same manner as measured interactions. Therefore our method potentially

Defining, evaluating, and removing bias induced by linear imputation in longitudinal clinical trials with MNAR missing data.

Science.gov (United States)

Helms, Ronald W; Reece, Laura Helms; Helms, Russell W; Helms, Mary W

2011-03-01

Missing not at random (MNAR) post-dropout missing data from a longitudinal clinical trial result in the collection of "biased data," which leads to biased estimators and tests of corrupted hypotheses. In a full rank linear model analysis the model equation, E[Y] = Xβ, leads to the definition of the primary parameter β = (X'X)(-1)X'E[Y], and the definition of linear secondary parameters of the form θ = Lβ = L(X'X)(-1)X'E[Y], including, for example, a parameter representing a "treatment effect." These parameters depend explicitly on E[Y], which raises the questions: What is E[Y] when some elements of the incomplete random vector Y are not observed and MNAR, or when such a Y is "completed" via imputation? We develop a rigorous, readily interpretable definition of E[Y] in this context that leads directly to definitions of β, Bias(β) = E[β] - β, Bias(θ) = E[θ] - Lβ, and the extent of hypothesis corruption. These definitions provide a basis for evaluating, comparing, and removing biases induced by various linear imputation methods for MNAR incomplete data from longitudinal clinical trials. Linear imputation methods use earlier data from a subject to impute values for post-dropout missing values and include "Last Observation Carried Forward" (LOCF) and "Baseline Observation Carried Forward" (BOCF), among others. We illustrate the methods of evaluating, comparing, and removing biases and the effects of testing corresponding corrupted hypotheses via a hypothetical but very realistic longitudinal analgesic clinical trial.

On multivariate imputation and forecasting of decadal wind speed missing data.

Science.gov (United States)

Wesonga, Ronald

2015-01-01

This paper demonstrates the application of multiple imputations by chained equations and time series forecasting of wind speed data. The study was motivated by the high prevalence of missing wind speed historic data. Findings based on the fully conditional specification under multiple imputations by chained equations, provided reliable wind speed missing data imputations. Further, the forecasting model shows, the smoothing parameter, alpha (0.014) close to zero, confirming that recent past observations are more suitable for use to forecast wind speeds. The maximum decadal wind speed for Entebbe International Airport was estimated to be 17.6 metres per second at a 0.05 level of significance with a bound on the error of estimation of 10.8 metres per second. The large bound on the error of estimations confirms the dynamic tendencies of wind speed at the airport under study.

Comparison of results from different imputation techniques for missing data from an anti-obesity drug trial

DEFF Research Database (Denmark)

Jørgensen, Anders W.; Lundstrøm, Lars H; Wetterslev, Jørn

2014-01-01

BACKGROUND: In randomised trials of medical interventions, the most reliable analysis follows the intention-to-treat (ITT) principle. However, the ITT analysis requires that missing outcome data have to be imputed. Different imputation techniques may give different results and some may lead to bias...... of handling missing data in a 60-week placebo controlled anti-obesity drug trial on topiramate. METHODS: We compared an analysis of complete cases with datasets where missing body weight measurements had been replaced using three different imputation methods: LOCF, baseline carried forward (BOCF) and MI...

Using imputation to provide location information for nongeocoded addresses.

Directory of Open Access Journals (Sweden)

Frank C Curriero

2010-02-01

Full Text Available The importance of geography as a source of variation in health research continues to receive sustained attention in the literature. The inclusion of geographic information in such research often begins by adding data to a map which is predicated by some knowledge of location. A precise level of spatial information is conventionally achieved through geocoding, the geographic information system (GIS process of translating mailing address information to coordinates on a map. The geocoding process is not without its limitations, though, since there is always a percentage of addresses which cannot be converted successfully (nongeocodable. This raises concerns regarding bias since traditionally the practice has been to exclude nongeocoded data records from analysis.In this manuscript we develop and evaluate a set of imputation strategies for dealing with missing spatial information from nongeocoded addresses. The strategies are developed assuming a known zip code with increasing use of collateral information, namely the spatial distribution of the population at risk. Strategies are evaluated using prostate cancer data obtained from the Maryland Cancer Registry. We consider total case enumerations at the Census county, tract, and block group level as the outcome of interest when applying and evaluating the methods. Multiple imputation is used to provide estimated total case counts based on complete data (geocodes plus imputed nongeocodes with a measure of uncertainty. Results indicate that the imputation strategy based on using available population-based age, gender, and race information performed the best overall at the county, tract, and block group levels.The procedure allows for the potentially biased and likely under reported outcome, case enumerations based on only the geocoded records, to be presented with a statistically adjusted count (imputed count with a measure of uncertainty that are based on all the case data, the geocodes and imputed

Multiple imputation strategies for zero-inflated cost data in economic evaluations : which method works best?

NARCIS (Netherlands)

MacNeil Vroomen, Janet; Eekhout, Iris; Dijkgraaf, Marcel G; van Hout, Hein; de Rooij, Sophia E; Heymans, Martijn W; Bosmans, Judith E

2016-01-01

Cost and effect data often have missing data because economic evaluations are frequently added onto clinical studies where cost data are rarely the primary outcome. The objective of this article was to investigate which multiple imputation strategy is most appropriate to use for missing

LinkImputeR: user-guided genotype calling and imputation for non-model organisms.

Science.gov (United States)

Money, Daniel; Migicovsky, Zoë; Gardner, Kyle; Myles, Sean

2017-07-10

Genomic studies such as genome-wide association and genomic selection require genome-wide genotype data. All existing technologies used to create these data result in missing genotypes, which are often then inferred using genotype imputation software. However, existing imputation methods most often make use only of genotypes that are successfully inferred after having passed a certain read depth threshold. Because of this, any read information for genotypes that did not pass the threshold, and were thus set to missing, is ignored. Most genomic studies also choose read depth thresholds and quality filters without investigating their effects on the size and quality of the resulting genotype data. Moreover, almost all genotype imputation methods require ordered markers and are therefore of limited utility in non-model organisms. Here we introduce LinkImputeR, a software program that exploits the read count information that is normally ignored, and makes use of all available DNA sequence information for the purposes of genotype calling and imputation. It is specifically designed for non-model organisms since it requires neither ordered markers nor a reference panel of genotypes. Using next-generation DNA sequence (NGS) data from apple, cannabis and grape, we quantify the effect of varying read count and missingness thresholds on the quantity and quality of genotypes generated from LinkImputeR. We demonstrate that LinkImputeR can increase the number of genotype calls by more than an order of magnitude, can improve genotyping accuracy by several percent and can thus improve the power of downstream analyses. Moreover, we show that the effects of quality and read depth filters can differ substantially between data sets and should therefore be investigated on a per-study basis. By exploiting DNA sequence data that is normally ignored during genotype calling and imputation, LinkImputeR can significantly improve both the quantity and quality of genotype data generated from

Dynamic reliability assessment and prediction for repairable systems with interval-censored data

International Nuclear Information System (INIS)

Peng, Yizhen; Wang, Yu; Zi, YanYang; Tsui, Kwok-Leung; Zhang, Chuhua

2017-01-01

The ‘Test, Analyze and Fix’ process is widely applied to improve the reliability of a repairable system. In this process, dynamic reliability assessment for the system has been paid a great deal of attention. Due to instrument malfunctions, staff omissions and imperfect inspection strategies, field reliability data are often subject to interval censoring, making dynamic reliability assessment become a difficult task. Most traditional methods assume this kind of data as multiple normal distributed variables or the missing mechanism as missing at random, which may cause a large bias in parameter estimation. This paper proposes a novel method to evaluate and predict the dynamic reliability of a repairable system subject to interval-censored problem. First, a multiple imputation strategy based on the assumption that the reliability growth trend follows a nonhomogeneous Poisson process is developed to derive the distributions of missing data. Second, a new order statistic model that can transfer the dependent variables into independent variables is developed to simplify the imputation procedure. The unknown parameters of the model are iteratively inferred by the Monte Carlo expectation maximization (MCEM) algorithm. Finally, to verify the effectiveness of the proposed method, a simulation and a real case study for gas pipeline compressor system are implemented. - Highlights: • A new multiple imputation strategy was developed to derive the PDF of missing data. • A new order statistic model was developed to simplify the imputation procedure. • The parameters of the order statistic model were iteratively inferred by MCEM. • A real cases study was conducted to verify the effectiveness of the proposed method.

Highly accurate sequence imputation enables precise QTL mapping in Brown Swiss cattle.

Science.gov (United States)

Frischknecht, Mirjam; Pausch, Hubert; Bapst, Beat; Signer-Hasler, Heidi; Flury, Christine; Garrick, Dorian; Stricker, Christian; Fries, Ruedi; Gredler-Grandl, Birgit

2017-12-29

Within the last few years a large amount of genomic information has become available in cattle. Densities of genomic information vary from a few thousand variants up to whole genome sequence information. In order to combine genomic information from different sources and infer genotypes for a common set of variants, genotype imputation is required. In this study we evaluated the accuracy of imputation from high density chips to whole genome sequence data in Brown Swiss cattle. Using four popular imputation programs (Beagle, FImpute, Impute2, Minimac) and various compositions of reference panels, the accuracy of the imputed sequence variant genotypes was high and differences between the programs and scenarios were small. We imputed sequence variant genotypes for more than 1600 Brown Swiss bulls and performed genome-wide association studies for milk fat percentage at two stages of lactation. We found one and three quantitative trait loci for early and late lactation fat content, respectively. Known causal variants that were imputed from the sequenced reference panel were among the most significantly associated variants of the genome-wide association study. Our study demonstrates that whole-genome sequence information can be imputed at high accuracy in cattle populations. Using imputed sequence variant genotypes in genome-wide association studies may facilitate causal variant detection.

Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data.

Science.gov (United States)

Ritz, Cecilia; Edén, Patrik

2008-01-19

For 2-dye microarray platforms, some missing values may arise from an un-measurably low RNA expression in one channel only. Information of such "one-channel depletion" is so far not included in algorithms for imputation of missing values. Calculating the mean deviation between imputed values and duplicate controls in five datasets, we show that KNN-based imputation gives a systematic bias of the imputed expression values of one-channel depleted spots. Evaluating the correction of this bias by cross-validation showed that the mean square deviation between imputed values and duplicates were reduced up to 51%, depending on dataset. By including more information in the imputation step, we more accurately estimate missing expression values.

Missing value imputation: with application to handwriting data

Science.gov (United States)

Xu, Zhen; Srihari, Sargur N.

2015-01-01

Missing values make pattern analysis difficult, particularly with limited available data. In longitudinal research, missing values accumulate, thereby aggravating the problem. Here we consider how to deal with temporal data with missing values in handwriting analysis. In the task of studying development of individuality of handwriting, we encountered the fact that feature values are missing for several individuals at several time instances. Six algorithms, i.e., random imputation, mean imputation, most likely independent value imputation, and three methods based on Bayesian network (static Bayesian network, parameter EM, and structural EM), are compared with children's handwriting data. We evaluate the accuracy and robustness of the algorithms under different ratios of missing data and missing values, and useful conclusions are given. Specifically, static Bayesian network is used for our data which contain around 5% missing data to provide adequate accuracy and low computational cost.

Genotype Imputation for Latinos Using the HapMap and 1000 Genomes Project Reference Panels

Directory of Open Access Journals (Sweden)

Xiaoyi eGao

2012-06-01

Full Text Available Genotype imputation is a vital tool in genome-wide association studies (GWAS and meta-analyses of multiple GWAS results. Imputation enables researchers to increase genomic coverage and to pool data generated using different genotyping platforms. HapMap samples are often employed as the reference panel. More recently, the 1000 Genomes Project resource is becoming the primary source for reference panels. Multiple GWAS and meta-analyses are targeting Latinos, the most populous and fastest growing minority group in the US. However, genotype imputation resources for Latinos are rather limited compared to individuals of European ancestry at present, largely because of the lack of good reference data. One choice of reference panel for Latinos is one derived from the population of Mexican individuals in Los Angeles contained in the HapMap Phase 3 project and the 1000 Genomes Project. However, a detailed evaluation of the quality of the imputed genotypes derived from the public reference panels has not yet been reported. Using simulation studies, the Illumina OmniExpress GWAS data from the Los Angles Latino Eye Study and the MACH software package, we evaluated the accuracy of genotype imputation in Latinos. Our results show that the 1000 Genomes Project AMR+CEU+YRI reference panel provides the highest imputation accuracy for Latinos, and that also including Asian samples in the panel can reduce imputation accuracy. We also provide the imputation accuracy for each autosomal chromosome using the 1000 Genomes Project panel for Latinos. Our results serve as a guide to future imputation-based analysis in Latinos.

Data imputation analysis for Cosmic Rays time series

Science.gov (United States)

Fernandes, R. C.; Lucio, P. S.; Fernandez, J. H.

2017-05-01

The occurrence of missing data concerning Galactic Cosmic Rays time series (GCR) is inevitable since loss of data is due to mechanical and human failure or technical problems and different periods of operation of GCR stations. The aim of this study was to perform multiple dataset imputation in order to depict the observational dataset. The study has used the monthly time series of GCR Climax (CLMX) and Roma (ROME) from 1960 to 2004 to simulate scenarios of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90% of missing data compared to observed ROME series, with 50 replicates. Then, the CLMX station as a proxy for allocation of these scenarios was used. Three different methods for monthly dataset imputation were selected: AMÉLIA II - runs the bootstrap Expectation Maximization algorithm, MICE - runs an algorithm via Multivariate Imputation by Chained Equations and MTSDI - an Expectation Maximization algorithm-based method for imputation of missing values in multivariate normal time series. The synthetic time series compared with the observed ROME series has also been evaluated using several skill measures as such as RMSE, NRMSE, Agreement Index, R, R2, F-test and t-test. The results showed that for CLMX and ROME, the R2 and R statistics were equal to 0.98 and 0.96, respectively. It was observed that increases in the number of gaps generate loss of quality of the time series. Data imputation was more efficient with MTSDI method, with negligible errors and best skill coefficients. The results suggest a limit of about 60% of missing data for imputation, for monthly averages, no more than this. It is noteworthy that CLMX, ROME and KIEL stations present no missing data in the target period. This methodology allowed reconstructing 43 time series.

Data driven estimation of imputation error-a strategy for imputation with a reject option

DEFF Research Database (Denmark)

Bak, Nikolaj; Hansen, Lars Kai

2016-01-01

Missing data is a common problem in many research fields and is a challenge that always needs careful considerations. One approach is to impute the missing values, i.e., replace missing values with estimates. When imputation is applied, it is typically applied to all records with missing values i...

An Imputation Model for Dropouts in Unemployment Data

Directory of Open Access Journals (Sweden)

Nilsson Petra

2016-09-01

Full Text Available Incomplete unemployment data is a fundamental problem when evaluating labour market policies in several countries. Many unemployment spells end for unknown reasons; in the Swedish Public Employment Service’s register as many as 20 percent. This leads to an ambiguity regarding destination states (employment, unemployment, retired, etc.. According to complete combined administrative data, the employment rate among dropouts was close to 50 for the years 1992 to 2006, but from 2007 the employment rate has dropped to 40 or less. This article explores an imputation approach. We investigate imputation models estimated both on survey data from 2005/2006 and on complete combined administrative data from 2005/2006 and 2011/2012. The models are evaluated in terms of their ability to make correct predictions. The models have relatively high predictive power.

The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer

Directory of Open Access Journals (Sweden)

Rosa Aghdam

2017-12-01

Full Text Available Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/.

Genomic evaluations with many more genotypes

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Wiggans George R

2011-03-01

Full Text Available Abstract Background Genomic evaluations in Holstein dairy cattle have quickly become more reliable over the last two years in many countries as more animals have been genotyped for 50,000 markers. Evaluations can also include animals genotyped with more or fewer markers using new tools such as the 777,000 or 2,900 marker chips recently introduced for cattle. Gains from more markers can be predicted using simulation, whereas strategies to use fewer markers have been compared using subsets of actual genotypes. The overall cost of selection is reduced by genotyping most animals at less than the highest density and imputing their missing genotypes using haplotypes. Algorithms to combine different densities need to be efficient because numbers of genotyped animals and markers may continue to grow quickly. Methods Genotypes for 500,000 markers were simulated for the 33,414 Holsteins that had 50,000 marker genotypes in the North American database. Another 86,465 non-genotyped ancestors were included in the pedigree file, and linkage disequilibrium was generated directly in the base population. Mixed density datasets were created by keeping 50,000 (every tenth of the markers for most animals. Missing genotypes were imputed using a combination of population haplotyping and pedigree haplotyping. Reliabilities of genomic evaluations using linear and nonlinear methods were compared. Results Differing marker sets for a large population were combined with just a few hours of computation. About 95% of paternal alleles were determined correctly, and > 95% of missing genotypes were called correctly. Reliability of breeding values was already high (84.4% with 50,000 simulated markers. The gain in reliability from increasing the number of markers to 500,000 was only 1.6%, but more than half of that gain resulted from genotyping just 1,406 young bulls at higher density. Linear genomic evaluations had reliabilities 1.5% lower than the nonlinear evaluations with 50

Local exome sequences facilitate imputation of less common variants and increase power of genome wide association studies.

Directory of Open Access Journals (Sweden)

Peter K Joshi

Full Text Available The analysis of less common variants in genome-wide association studies promises to elucidate complex trait genetics but is hampered by low power to reliably detect association. We show that addition of population-specific exome sequence data to global reference data allows more accurate imputation, particularly of less common SNPs (minor allele frequency 1-10% in two very different European populations. The imputation improvement corresponds to an increase in effective sample size of 28-38%, for SNPs with a minor allele frequency in the range 1-3%.

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

Science.gov (United States)

Luo, Yuan; Szolovits, Peter; Dighe, Anand S; Baron, Jason M

2018-06-01

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-dimensional multiple imputation with chained equations (3D-MICE), that can perform accurate imputation of missing clinical time series data. We extracted clinical laboratory test results for 13 commonly measured analytes (clinical laboratory tests). We imputed missing test results for the 13 analytes using 3 imputation methods: multiple imputation with chained equations (MICE), Gaussian process (GP), and 3D-MICE. 3D-MICE utilizes both MICE and GP imputation to integrate cross-sectional and longitudinal information. To evaluate imputation method performance, we randomly masked selected test results and imputed these masked results alongside results missing from our original data. We compared predicted results to measured results for masked data points. 3D-MICE performed significantly better than MICE and GP-based imputation in a composite of all 13 analytes, predicting missing results with a normalized root-mean-square error of 0.342, compared to 0.373 for MICE alone and 0.358 for GP alone. 3D-MICE offers a novel and practical approach to imputing clinical laboratory time series data. 3D-MICE may provide an additional tool for use as a foundation in clinical predictive analytics and intelligent clinical decision support.

A web-based approach to data imputation

KAUST Repository

Li, Zhixu

2013-10-24

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques. © 2013 Springer Science+Business Media New York.

Missing value imputation in DNA microarrays based on conjugate gradient method.

Science.gov (United States)

Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh

2012-02-01

Analysis of gene expression profiles needs a complete matrix of gene array values; consequently, imputation methods have been suggested. In this paper, an algorithm that is based on conjugate gradient (CG) method is proposed to estimate missing values. k-nearest neighbors of the missed entry are first selected based on absolute values of their Pearson correlation coefficient. Then a subset of genes among the k-nearest neighbors is labeled as the best similar ones. CG algorithm with this subset as its input is then used to estimate the missing values. Our proposed CG based algorithm (CGimpute) is evaluated on different data sets. The results are compared with sequential local least squares (SLLSimpute), Bayesian principle component analysis (BPCAimpute), local least squares imputation (LLSimpute), iterated local least squares imputation (ILLSimpute) and adaptive k-nearest neighbors imputation (KNNKimpute) methods. The average of normalized root mean squares error (NRMSE) and relative NRMSE in different data sets with various missing rates shows CGimpute outperforms other methods. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparison of missing value imputation methods in time series: the case of Turkish meteorological data

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Yozgatligil, Ceylan; Aslan, Sipan; Iyigun, Cem; Batmaz, Inci

2013-04-01

This study aims to compare several imputation methods to complete the missing values of spatio-temporal meteorological time series. To this end, six imputation methods are assessed with respect to various criteria including accuracy, robustness, precision, and efficiency for artificially created missing data in monthly total precipitation and mean temperature series obtained from the Turkish State Meteorological Service. Of these methods, simple arithmetic average, normal ratio (NR), and NR weighted with correlations comprise the simple ones, whereas multilayer perceptron type neural network and multiple imputation strategy adopted by Monte Carlo Markov Chain based on expectation-maximization (EM-MCMC) are computationally intensive ones. In addition, we propose a modification on the EM-MCMC method. Besides using a conventional accuracy measure based on squared errors, we also suggest the correlation dimension (CD) technique of nonlinear dynamic time series analysis which takes spatio-temporal dependencies into account for evaluating imputation performances. Depending on the detailed graphical and quantitative analysis, it can be said that although computational methods, particularly EM-MCMC method, are computationally inefficient, they seem favorable for imputation of meteorological time series with respect to different missingness periods considering both measures and both series studied. To conclude, using the EM-MCMC algorithm for imputing missing values before conducting any statistical analyses of meteorological data will definitely decrease the amount of uncertainty and give more robust results. Moreover, the CD measure can be suggested for the performance evaluation of missing data imputation particularly with computational methods since it gives more precise results in meteorological time series.

The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer.

Science.gov (United States)

Aghdam, Rosa; Baghfalaki, Taban; Khosravi, Pegah; Saberi Ansari, Elnaz

2017-12-01

Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/. Copyright © 2017. Production and hosting by Elsevier B.V.

Missing in space: an evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes.

Science.gov (United States)

Baker, Jannah; White, Nicole; Mengersen, Kerrie

2014-11-20

Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.

Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

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Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

2016-01-01

Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

The multiple imputation method: a case study involving secondary data analysis.

Science.gov (United States)

Walani, Salimah R; Cleland, Charles M

2015-05-01

To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.

Cost reduction for web-based data imputation

KAUST Repository

Li, Zhixu; Shang, Shuo; Xie, Qing; Zhang, Xiangliang

2014-01-01

Web-based Data Imputation enables the completion of incomplete data sets by retrieving absent field values from the Web. In particular, complete fields can be used as keywords in imputation queries for absent fields. However, due to the ambiguity

Multiple imputation in the presence of non-normal data.

Science.gov (United States)

Lee, Katherine J; Carlin, John B

2017-02-20

Multiple imputation (MI) is becoming increasingly popular for handling missing data. Standard approaches for MI assume normality for continuous variables (conditionally on the other variables in the imputation model). However, it is unclear how to impute non-normally distributed continuous variables. Using simulation and a case study, we compared various transformations applied prior to imputation, including a novel non-parametric transformation, to imputation on the raw scale and using predictive mean matching (PMM) when imputing non-normal data. We generated data from a range of non-normal distributions, and set 50% to missing completely at random or missing at random. We then imputed missing values on the raw scale, following a zero-skewness log, Box-Cox or non-parametric transformation and using PMM with both type 1 and 2 matching. We compared inferences regarding the marginal mean of the incomplete variable and the association with a fully observed outcome. We also compared results from these approaches in the analysis of depression and anxiety symptoms in parents of very preterm compared with term-born infants. The results provide novel empirical evidence that the decision regarding how to impute a non-normal variable should be based on the nature of the relationship between the variables of interest. If the relationship is linear in the untransformed scale, transformation can introduce bias irrespective of the transformation used. However, if the relationship is non-linear, it may be important to transform the variable to accurately capture this relationship. A useful alternative is to impute the variable using PMM with type 1 matching. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Missing data imputation using statistical and machine learning methods in a real breast cancer problem.

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Jerez, José M; Molina, Ignacio; García-Laencina, Pedro J; Alba, Emilio; Ribelles, Nuria; Martín, Miguel; Franco, Leonardo

2010-10-01

Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. This work evaluates the performance of several statistical and machine learning imputation methods that were used to predict recurrence in patients in an extensive real breast cancer data set. Imputation methods based on statistical techniques, e.g., mean, hot-deck and multiple imputation, and machine learning techniques, e.g., multi-layer perceptron (MLP), self-organisation maps (SOM) and k-nearest neighbour (KNN), were applied to data collected through the "El Álamo-I" project, and the results were then compared to those obtained from the listwise deletion (LD) imputation method. The database includes demographic, therapeutic and recurrence-survival information from 3679 women with operable invasive breast cancer diagnosed in 32 different hospitals belonging to the Spanish Breast Cancer Research Group (GEICAM). The accuracies of predictions on early cancer relapse were measured using artificial neural networks (ANNs), in which different ANNs were estimated using the data sets with imputed missing values. The imputation methods based on machine learning algorithms outperformed imputation statistical methods in the prediction of patient outcome. Friedman's test revealed a significant difference (p=0.0091) in the observed area under the ROC curve (AUC) values, and the pairwise comparison test showed that the AUCs for MLP, KNN and SOM were significantly higher (p=0.0053, p=0.0048 and p=0.0071, respectively) than the AUC from the LD-based prognosis model. The methods based on machine learning techniques were the most suited for the imputation of missing values and led to a significant enhancement of prognosis accuracy compared to imputation methods based on statistical procedures. Copyright © 2010 Elsevier B.V. All rights reserved.

Imputation methods for filling missing data in urban air pollution data for Malaysia

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Nur Afiqah Zakaria

2018-06-01

Full Text Available The air quality measurement data obtained from the continuous ambient air quality monitoring (CAAQM station usually contained missing data. The missing observations of the data usually occurred due to machine failure, routine maintenance and human error. In this study, the hourly monitoring data of CO, O3, PM10, SO2, NOx, NO2, ambient temperature and humidity were used to evaluate four imputation methods (Mean Top Bottom, Linear Regression, Multiple Imputation and Nearest Neighbour. The air pollutants observations were simulated into four percentages of simulated missing data i.e. 5%, 10%, 15% and 20%. Performance measures namely the Mean Absolute Error, Root Mean Squared Error, Coefficient of Determination and Index of Agreement were used to describe the goodness of fit of the imputation methods. From the results of the performance measures, Mean Top Bottom method was selected as the most appropriate imputation method for filling in the missing values in air pollutants data.

Multiple imputation and its application

CERN Document Server

Carpenter, James

2013-01-01

A practical guide to analysing partially observed data. Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete  data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods. This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures. Multiple Imputation and its Application: Discusses the issues ...

Comparison of different Methods for Univariate Time Series Imputation in R

OpenAIRE

Moritz, Steffen; Sardá, Alexis; Bartz-Beielstein, Thomas; Zaefferer, Martin; Stork, Jörg

2015-01-01

Missing values in datasets are a well-known problem and there are quite a lot of R packages offering imputation functions. But while imputation in general is well covered within R, it is hard to find functions for imputation of univariate time series. The problem is, most standard imputation techniques can not be applied directly. Most algorithms rely on inter-attribute correlations, while univariate time series imputation needs to employ time dependencies. This paper provides an overview of ...

Flexible Imputation of Missing Data

CERN Document Server

van Buuren, Stef

2012-01-01

Missing data form a problem in every scientific discipline, yet the techniques required to handle them are complicated and often lacking. One of the great ideas in statistical science--multiple imputation--fills gaps in the data with plausible values, the uncertainty of which is coded in the data itself. It also solves other problems, many of which are missing data problems in disguise. Flexible Imputation of Missing Data is supported by many examples using real data taken from the author's vast experience of collaborative research, and presents a practical guide for handling missing data unde

A nonparametric multiple imputation approach for missing categorical data

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Muhan Zhou

2017-06-01

Full Text Available Abstract Background Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness probabilities. Methods We propose a nearest-neighbour multiple imputation approach to impute a missing at random categorical outcome and to estimate the proportion of each category. The donor set for imputation is formed by measuring distances between each missing value with other non-missing values. The distance function is calculated based on a predictive score, which is derived from two working models: one fits a multinomial logistic regression for predicting the missing categorical outcome (the outcome model and the other fits a logistic regression for predicting missingness probabilities (the missingness model. A weighting scheme is used to accommodate contributions from two working models when generating the predictive score. A missing value is imputed by randomly selecting one of the non-missing values with the smallest distances. We conduct a simulation to evaluate the performance of the proposed method and compare it with several alternative methods. A real-data application is also presented. Results The simulation study suggests that the proposed method performs well when missingness probabilities are not extreme under some misspecifications of the working models. However, the calibration estimator, which is also based on two working models, can be highly unstable when missingness probabilities for some observations are extremely high. In this scenario, the proposed method produces more stable and better estimates. In addition, proper weights need to be chosen to balance the contributions from the two working models and achieve optimal results for the proposed method. Conclusions We conclude that the proposed multiple imputation method is a reasonable approach to dealing with missing categorical outcome data with

Saturated linkage map construction in Rubus idaeus using genotyping by sequencing and genome-independent imputation

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Ward Judson A

2013-01-01

Full Text Available Abstract Background Rapid development of highly saturated genetic maps aids molecular breeding, which can accelerate gain per breeding cycle in woody perennial plants such as Rubus idaeus (red raspberry. Recently, robust genotyping methods based on high-throughput sequencing were developed, which provide high marker density, but result in some genotype errors and a large number of missing genotype values. Imputation can reduce the number of missing values and can correct genotyping errors, but current methods of imputation require a reference genome and thus are not an option for most species. Results Genotyping by Sequencing (GBS was used to produce highly saturated maps for a R. idaeus pseudo-testcross progeny. While low coverage and high variance in sequencing resulted in a large number of missing values for some individuals, a novel method of imputation based on maximum likelihood marker ordering from initial marker segregation overcame the challenge of missing values, and made map construction computationally tractable. The two resulting parental maps contained 4521 and 2391 molecular markers spanning 462.7 and 376.6 cM respectively over seven linkage groups. Detection of precise genomic regions with segregation distortion was possible because of map saturation. Microsatellites (SSRs linked these results to published maps for cross-validation and map comparison. Conclusions GBS together with genome-independent imputation provides a rapid method for genetic map construction in any pseudo-testcross progeny. Our method of imputation estimates the correct genotype call of missing values and corrects genotyping errors that lead to inflated map size and reduced precision in marker placement. Comparison of SSRs to published R. idaeus maps showed that the linkage maps constructed with GBS and our method of imputation were robust, and marker positioning reliable. The high marker density allowed identification of genomic regions with segregation

Assessing accuracy of genotype imputation in American Indians.

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Alka Malhotra

Full Text Available Genotype imputation is commonly used in genetic association studies to test untyped variants using information on linkage disequilibrium (LD with typed markers. Imputing genotypes requires a suitable reference population in which the LD pattern is known, most often one selected from HapMap. However, some populations, such as American Indians, are not represented in HapMap. In the present study, we assessed accuracy of imputation using HapMap reference populations in a genome-wide association study in Pima Indians.Data from six randomly selected chromosomes were used. Genotypes in the study population were masked (either 1% or 20% of SNPs available for a given chromosome. The masked genotypes were then imputed using the software Markov Chain Haplotyping Algorithm. Using four HapMap reference populations, average genotype error rates ranged from 7.86% for Mexican Americans to 22.30% for Yoruba. In contrast, use of the original Pima Indian data as a reference resulted in an average error rate of 1.73%.Our results suggest that the use of HapMap reference populations results in substantial inaccuracy in the imputation of genotypes in American Indians. A possible solution would be to densely genotype or sequence a reference American Indian population.

Assessment of imputation methods using varying ecological information to fill the gaps in a tree functional trait database

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Poyatos, Rafael; Sus, Oliver; Vilà-Cabrera, Albert; Vayreda, Jordi; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi

2016-04-01

Plant functional traits are increasingly being used in ecosystem ecology thanks to the growing availability of large ecological databases. However, these databases usually contain a large fraction of missing data because measuring plant functional traits systematically is labour-intensive and because most databases are compilations of datasets with different sampling designs. As a result, within a given database, there is an inevitable variability in the number of traits available for each data entry and/or the species coverage in a given geographical area. The presence of missing data may severely bias trait-based analyses, such as the quantification of trait covariation or trait-environment relationships and may hamper efforts towards trait-based modelling of ecosystem biogeochemical cycles. Several data imputation (i.e. gap-filling) methods have been recently tested on compiled functional trait databases, but the performance of imputation methods applied to a functional trait database with a regular spatial sampling has not been thoroughly studied. Here, we assess the effects of data imputation on five tree functional traits (leaf biomass to sapwood area ratio, foliar nitrogen, maximum height, specific leaf area and wood density) in the Ecological and Forest Inventory of Catalonia, an extensive spatial database (covering 31900 km2). We tested the performance of species mean imputation, single imputation by the k-nearest neighbors algorithm (kNN) and a multiple imputation method, Multivariate Imputation with Chained Equations (MICE) at different levels of missing data (10%, 30%, 50%, and 80%). We also assessed the changes in imputation performance when additional predictors (species identity, climate, forest structure, spatial structure) were added in kNN and MICE imputations. We evaluated the imputed datasets using a battery of indexes describing departure from the complete dataset in trait distribution, in the mean prediction error, in the correlation matrix

Bootstrap inference when using multiple imputation.

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Schomaker, Michael; Heumann, Christian

2018-04-16

Many modern estimators require bootstrapping to calculate confidence intervals because either no analytic standard error is available or the distribution of the parameter of interest is nonsymmetric. It remains however unclear how to obtain valid bootstrap inference when dealing with multiple imputation to address missing data. We present 4 methods that are intuitively appealing, easy to implement, and combine bootstrap estimation with multiple imputation. We show that 3 of the 4 approaches yield valid inference, but that the performance of the methods varies with respect to the number of imputed data sets and the extent of missingness. Simulation studies reveal the behavior of our approaches in finite samples. A topical analysis from HIV treatment research, which determines the optimal timing of antiretroviral treatment initiation in young children, demonstrates the practical implications of the 4 methods in a sophisticated and realistic setting. This analysis suffers from missing data and uses the g-formula for inference, a method for which no standard errors are available. Copyright © 2018 John Wiley & Sons, Ltd.

Imputation of variants from the 1000 Genomes Project modestly improves known associations and can identify low-frequency variant-phenotype associations undetected by HapMap based imputation.

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Wood, Andrew R; Perry, John R B; Tanaka, Toshiko; Hernandez, Dena G; Zheng, Hou-Feng; Melzer, David; Gibbs, J Raphael; Nalls, Michael A; Weedon, Michael N; Spector, Tim D; Richards, J Brent; Bandinelli, Stefania; Ferrucci, Luigi; Singleton, Andrew B; Frayling, Timothy M

2013-01-01

Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF 1000 Genomes imputation, respectively, and 9 and 11 that reached a stricter, likely conservative, threshold of P1000 Genomes genotype data modestly improved the strength of known associations. Of 20 associations detected at P1000 Genomes imputed data and one was nominally more strongly associated in HapMap imputed data. We also detected an association between a low frequency variant and phenotype that was previously missed by HapMap based imputation approaches. An association between rs112635299 and alpha-1 globulin near the SERPINA gene represented the known association between rs28929474 (MAF = 0.007) and alpha1-antitrypsin that predisposes to emphysema (P = 2.5×10(-12)). Our data provide important proof of principle that 1000 Genomes imputation will detect novel, low frequency-large effect associations.

Imputing data that are missing at high rates using a boosting algorithm

Energy Technology Data Exchange (ETDEWEB)

Cauthen, Katherine Regina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lambert, Gregory [Apple Inc., Cupertino, CA (United States); Ray, Jaideep [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Lefantzi, Sophia [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

2016-09-01

Traditional multiple imputation approaches may perform poorly for datasets with high rates of missingness unless many m imputations are used. This paper implements an alternative machine learning-based approach to imputing data that are missing at high rates. Here, we use boosting to create a strong learner from a weak learner fitted to a dataset missing many observations. This approach may be applied to a variety of types of learners (models). The approach is demonstrated by application to a spatiotemporal dataset for predicting dengue outbreaks in India from meteorological covariates. A Bayesian spatiotemporal CAR model is boosted to produce imputations, and the overall RMSE from a k-fold cross-validation is used to assess imputation accuracy.

A Comparison of Joint Model and Fully Conditional Specification Imputation for Multilevel Missing Data

Science.gov (United States)

Mistler, Stephen A.; Enders, Craig K.

2017-01-01

Multiple imputation methods can generally be divided into two broad frameworks: joint model (JM) imputation and fully conditional specification (FCS) imputation. JM draws missing values simultaneously for all incomplete variables using a multivariate distribution, whereas FCS imputes variables one at a time from a series of univariate conditional…

Performance of genotype imputation for low frequency and rare variants from the 1000 genomes.

Science.gov (United States)

Zheng, Hou-Feng; Rong, Jing-Jing; Liu, Ming; Han, Fang; Zhang, Xing-Wei; Richards, J Brent; Wang, Li

2015-01-01

Genotype imputation is now routinely applied in genome-wide association studies (GWAS) and meta-analyses. However, most of the imputations have been run using HapMap samples as reference, imputation of low frequency and rare variants (minor allele frequency (MAF) 1000 Genomes panel) are available to facilitate imputation of these variants. Therefore, in order to estimate the performance of low frequency and rare variants imputation, we imputed 153 individuals, each of whom had 3 different genotype array data including 317k, 610k and 1 million SNPs, to three different reference panels: the 1000 Genomes pilot March 2010 release (1KGpilot), the 1000 Genomes interim August 2010 release (1KGinterim), and the 1000 Genomes phase1 November 2010 and May 2011 release (1KGphase1) by using IMPUTE version 2. The differences between these three releases of the 1000 Genomes data are the sample size, ancestry diversity, number of variants and their frequency spectrum. We found that both reference panel and GWAS chip density affect the imputation of low frequency and rare variants. 1KGphase1 outperformed the other 2 panels, at higher concordance rate, higher proportion of well-imputed variants (info>0.4) and higher mean info score in each MAF bin. Similarly, 1M chip array outperformed 610K and 317K. However for very rare variants (MAF ≤ 0.3%), only 0-1% of the variants were well imputed. We conclude that the imputation of low frequency and rare variants improves with larger reference panels and higher density of genome-wide genotyping arrays. Yet, despite a large reference panel size and dense genotyping density, very rare variants remain difficult to impute.

Public Undertakings and Imputability

DEFF Research Database (Denmark)

Ølykke, Grith Skovgaard

2013-01-01

In this article, the issue of impuability to the State of public undertakings’ decision-making is analysed and discussed in the context of the DSBFirst case. DSBFirst is owned by the independent public undertaking DSB and the private undertaking FirstGroup plc and won the contracts in the 2008...... Oeresund tender for the provision of passenger transport by railway. From the start, the services were provided at a loss, and in the end a part of DSBFirst was wound up. In order to frame the problems illustrated by this case, the jurisprudence-based imputability requirement in the definition of State aid...... in Article 107(1) TFEU is analysed. It is concluded that where the public undertaking transgresses the control system put in place by the State, conditions for imputability are not fulfilled, and it is argued that in the current state of law, there is no conditional link between the level of control...

Missing value imputation for microarray gene expression data using histone acetylation information

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Feng Jihua

2008-05-01

Full Text Available Abstract Background It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages. Results The paper explores the feasibility of doing missing value imputation with the help of gene regulatory mechanism. An imputation framework called histone acetylation information aided imputation method (HAIimpute method is presented. It incorporates the histone acetylation information into the conventional KNN(k-nearest neighbor and LLS(local least square imputation algorithms for final prediction of the missing values. The experimental results indicated that the use of acetylation information can provide significant improvements in microarray imputation accuracy. The HAIimpute methods consistently improve the widely used methods such as KNN and LLS in terms of normalized root mean squared error (NRMSE. Meanwhile, the genes imputed by HAIimpute methods are more correlated with the original complete genes in terms of Pearson correlation coefficients. Furthermore, the proposed methods also outperform GOimpute, which is one of the existing related methods that use the functional similarity as the external information. Conclusion We demonstrated that the using of histone acetylation information could greatly improve the performance of the imputation especially at high missing percentages. This idea can be generalized to various imputation methods to facilitate the performance. Moreover, with more knowledge accumulated on gene regulatory mechanism in addition to histone acetylation, the performance of our approach can be further improved and verified.

Imputed prices of greenhouse gases and land forests

International Nuclear Information System (INIS)

Uzawa, Hirofumi

1993-01-01

The theory of dynamic optimum formulated by Maeler gives us the basic theoretical framework within which it is possible to analyse the economic and, possibly, political circumstances under which the phenomenon of global warming occurs, and to search for the policy and institutional arrangements whereby it would be effectively arrested. The analysis developed here is an application of Maeler's theory to atmospheric quality. In the analysis a central role is played by the concept of imputed price in the dynamic context. Our determination of imputed prices of atmospheric carbon dioxide and land forests takes into account the difference in the stages of economic development. Indeed, the ratios of the imputed prices of atmospheric carbon dioxide and land forests over the per capita level of real national income are identical for all countries involved. (3 figures, 2 tables) (Author)

VIGAN: Missing View Imputation with Generative Adversarial Networks.

Science.gov (United States)

Shang, Chao; Palmer, Aaron; Sun, Jiangwen; Chen, Ko-Shin; Lu, Jin; Bi, Jinbo

2017-01-01

In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collected from heterogeneous sources, resulting in multi-view or multi-modal datasets. The missing data problem has been challenging to address in multi-view data analysis. Especially, when certain samples miss an entire view of data, it creates the missing view problem. Classic multiple imputations or matrix completion methods are hardly effective here when no information can be based on in the specific view to impute data for such samples. The commonly-used simple method of removing samples with a missing view can dramatically reduce sample size, thus diminishing the statistical power of a subsequent analysis. In this paper, we propose a novel approach for view imputation via generative adversarial networks (GANs), which we name by VIGAN. This approach first treats each view as a separate domain and identifies domain-to-domain mappings via a GAN using randomly-sampled data from each view, and then employs a multi-modal denoising autoencoder (DAE) to reconstruct the missing view from the GAN outputs based on paired data across the views. Then, by optimizing the GAN and DAE jointly, our model enables the knowledge integration for domain mappings and view correspondences to effectively recover the missing view. Empirical results on benchmark datasets validate the VIGAN approach by comparing against the state of the art. The evaluation of VIGAN in a genetic study of substance use disorders further proves the effectiveness and usability of this approach in life science.

Missing Data Imputation of Solar Radiation Data under Different Atmospheric Conditions

Science.gov (United States)

Turrado, Concepción Crespo; López, María del Carmen Meizoso; Lasheras, Fernando Sánchez; Gómez, Benigno Antonio Rodríguez; Rollé, José Luis Calvo; de Cos Juez, Francisco Javier

2014-01-01

Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE). This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR). The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW. PMID:25356644

Missing Data Imputation of Solar Radiation Data under Different Atmospheric Conditions

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Concepción Crespo Turrado

2014-10-01

Full Text Available Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE. This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW and Multiple Linear Regression (MLR. The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW.

Missing data imputation of solar radiation data under different atmospheric conditions.

Science.gov (United States)

Turrado, Concepción Crespo; López, María Del Carmen Meizoso; Lasheras, Fernando Sánchez; Gómez, Benigno Antonio Rodríguez; Rollé, José Luis Calvo; Juez, Francisco Javier de Cos

2014-10-29

Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE). This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR). The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW.

Multiple Improvements of Multiple Imputation Likelihood Ratio Tests

OpenAIRE

Chan, Kin Wai; Meng, Xiao-Li

2017-01-01

Multiple imputation (MI) inference handles missing data by first properly imputing the missing values $m$ times, and then combining the $m$ analysis results from applying a complete-data procedure to each of the completed datasets. However, the existing method for combining likelihood ratio tests has multiple defects: (i) the combined test statistic can be negative in practice when the reference null distribution is a standard $F$ distribution; (ii) it is not invariant to re-parametrization; ...

Age at menopause: imputing age at menopause for women with a hysterectomy with application to risk of postmenopausal breast cancer

Science.gov (United States)

Rosner, Bernard; Colditz, Graham A.

2011-01-01

Purpose Age at menopause, a major marker in the reproductive life, may bias results for evaluation of breast cancer risk after menopause. Methods We follow 38,948 premenopausal women in 1980 and identify 2,586 who reported hysterectomy without bilateral oophorectomy, and 31,626 who reported natural menopause during 22 years of follow-up. We evaluate risk factors for natural menopause, impute age at natural menopause for women reporting hysterectomy without bilateral oophorectomy and estimate the hazard of reaching natural menopause in the next 2 years. We apply this imputed age at menopause to both increase sample size and to evaluate the relation between postmenopausal exposures and risk of breast cancer. Results Age, cigarette smoking, age at menarche, pregnancy history, body mass index, history of benign breast disease, and history of breast cancer were each significantly related to age at natural menopause; duration of oral contraceptive use and family history of breast cancer were not. The imputation increased sample size substantially and although some risk factors after menopause were weaker in the expanded model (height, and alcohol use), use of hormone therapy is less biased. Conclusions Imputing age at menopause increases sample size, broadens generalizability making it applicable to women with hysterectomy, and reduces bias. PMID:21441037

Two-pass imputation algorithm for missing value estimation in gene expression time series.

Science.gov (United States)

Tsiporkova, Elena; Boeva, Veselka

2007-10-01

Gene expression microarray experiments frequently generate datasets with multiple values missing. However, most of the analysis, mining, and classification methods for gene expression data require a complete matrix of gene array values. Therefore, the accurate estimation of missing values in such datasets has been recognized as an important issue, and several imputation algorithms have already been proposed to the biological community. Most of these approaches, however, are not particularly suitable for time series expression profiles. In view of this, we propose a novel imputation algorithm, which is specially suited for the estimation of missing values in gene expression time series data. The algorithm utilizes Dynamic Time Warping (DTW) distance in order to measure the similarity between time expression profiles, and subsequently selects for each gene expression profile with missing values a dedicated set of candidate profiles for estimation. Three different DTW-based imputation (DTWimpute) algorithms have been considered: position-wise, neighborhood-wise, and two-pass imputation. These have initially been prototyped in Perl, and their accuracy has been evaluated on yeast expression time series data using several different parameter settings. The experiments have shown that the two-pass algorithm consistently outperforms, in particular for datasets with a higher level of missing entries, the neighborhood-wise and the position-wise algorithms. The performance of the two-pass DTWimpute algorithm has further been benchmarked against the weighted K-Nearest Neighbors algorithm, which is widely used in the biological community; the former algorithm has appeared superior to the latter one. Motivated by these findings, indicating clearly the added value of the DTW techniques for missing value estimation in time series data, we have built an optimized C++ implementation of the two-pass DTWimpute algorithm. The software also provides for a choice between three different

Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes

Directory of Open Access Journals (Sweden)

Lotz Meredith J

2008-01-01

Full Text Available Abstract Background Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures × time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. Results We found that the optimal imputation algorithms (LSA, LLS, and BPCA are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Conclusion Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA

Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes.

Science.gov (United States)

Brock, Guy N; Shaffer, John R; Blakesley, Richard E; Lotz, Meredith J; Tseng, George C

2008-01-10

Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures x time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. We found that the optimal imputation algorithms (LSA, LLS, and BPCA) are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS) scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS) scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA) are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA) performed better on mcroarray data with lower complexity

48 CFR 1830.7002-4 - Determining imputed cost of money.

Science.gov (United States)

2010-10-01

... money. 1830.7002-4 Section 1830.7002-4 Federal Acquisition Regulations System NATIONAL AERONAUTICS AND... Determining imputed cost of money. (a) Determine the imputed cost of money for an asset under construction, fabrication, or development by applying a cost of money rate (see 1830.7002-2) to the representative...

Synthetic Multiple-Imputation Procedure for Multistage Complex Samples

Directory of Open Access Journals (Sweden)

Zhou Hanzhi

2016-03-01

Full Text Available Multiple imputation (MI is commonly used when item-level missing data are present. However, MI requires that survey design information be built into the imputation models. For multistage stratified clustered designs, this requires dummy variables to represent strata as well as primary sampling units (PSUs nested within each stratum in the imputation model. Such a modeling strategy is not only operationally burdensome but also inferentially inefficient when there are many strata in the sample design. Complexity only increases when sampling weights need to be modeled. This article develops a generalpurpose analytic strategy for population inference from complex sample designs with item-level missingness. In a simulation study, the proposed procedures demonstrate efficient estimation and good coverage properties. We also consider an application to accommodate missing body mass index (BMI data in the analysis of BMI percentiles using National Health and Nutrition Examination Survey (NHANES III data. We argue that the proposed methods offer an easy-to-implement solution to problems that are not well-handled by current MI techniques. Note that, while the proposed method borrows from the MI framework to develop its inferential methods, it is not designed as an alternative strategy to release multiply imputed datasets for complex sample design data, but rather as an analytic strategy in and of itself.

Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

Science.gov (United States)

Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi

2016-06-21

Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.

TRIP: An interactive retrieving-inferring data imputation approach

KAUST Repository

Li, Zhixu

2016-06-25

Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

TRIP: An interactive retrieving-inferring data imputation approach

KAUST Repository

Li, Zhixu; Qin, Lu; Cheng, Hong; Zhang, Xiangliang; Zhou, Xiaofang

2016-01-01

Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

Imputation of genotypes in Danish two-way crossbred pigs using low density panels

DEFF Research Database (Denmark)

Xiang, Tao; Christensen, Ole Fredslund; Legarra, Andres

Genotype imputation is commonly used as an initial step of genomic selection. Studies on humans, plants and ruminants suggested many factors would affect the performance of imputation. However, studies rarely investigated pigs, especially crossbred pigs. In this study, different scenarios...... of imputation from 5K SNPs to 7K SNPs on Danish Landrace, Yorkshire, and crossbred Landrace-Yorkshire were compared. In conclusion, genotype imputation on crossbreds performs equally well as in purebreds, when parental breeds are used as the reference panel. When the size of reference is considerably large...... SNPs. This dataset will be analyzed for genomic selection in a future study...

Impute DC link (IDCL) cell based power converters and control thereof

Science.gov (United States)

Divan, Deepakraj M.; Prasai, Anish; Hernendez, Jorge; Moghe, Rohit; Iyer, Amrit; Kandula, Rajendra Prasad

2016-04-26

Power flow controllers based on Imputed DC Link (IDCL) cells are provided. The IDCL cell is a self-contained power electronic building block (PEBB). The IDCL cell may be stacked in series and parallel to achieve power flow control at higher voltage and current levels. Each IDCL cell may comprise a gate drive, a voltage sharing module, and a thermal management component in order to facilitate easy integration of the cell into a variety of applications. By providing direct AC conversion, the IDCL cell based AC/AC converters reduce device count, eliminate the use of electrolytic capacitors that have life and reliability issues, and improve system efficiency compared with similarly rated back-to-back inverter system.

[Imputing missing data in public health: general concepts and application to dichotomous variables].

Science.gov (United States)

Hernández, Gilma; Moriña, David; Navarro, Albert

The presence of missing data in collected variables is common in health surveys, but the subsequent imputation thereof at the time of analysis is not. Working with imputed data may have certain benefits regarding the precision of the estimators and the unbiased identification of associations between variables. The imputation process is probably still little understood by many non-statisticians, who view this process as highly complex and with an uncertain goal. To clarify these questions, this note aims to provide a straightforward, non-exhaustive overview of the imputation process to enable public health researchers ascertain its strengths. All this in the context of dichotomous variables which are commonplace in public health. To illustrate these concepts, an example in which missing data is handled by means of simple and multiple imputation is introduced. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Imputing amino acid polymorphisms in human leukocyte antigens.

Directory of Open Access Journals (Sweden)

Xiaoming Jia

Full Text Available DNA sequence variation within human leukocyte antigen (HLA genes mediate susceptibility to a wide range of human diseases. The complex genetic structure of the major histocompatibility complex (MHC makes it difficult, however, to collect genotyping data in large cohorts. Long-range linkage disequilibrium between HLA loci and SNP markers across the major histocompatibility complex (MHC region offers an alternative approach through imputation to interrogate HLA variation in existing GWAS data sets. Here we describe a computational strategy, SNP2HLA, to impute classical alleles and amino acid polymorphisms at class I (HLA-A, -B, -C and class II (-DPA1, -DPB1, -DQA1, -DQB1, and -DRB1 loci. To characterize performance of SNP2HLA, we constructed two European ancestry reference panels, one based on data collected in HapMap-CEPH pedigrees (90 individuals and another based on data collected by the Type 1 Diabetes Genetics Consortium (T1DGC, 5,225 individuals. We imputed HLA alleles in an independent data set from the British 1958 Birth Cohort (N = 918 with gold standard four-digit HLA types and SNPs genotyped using the Affymetrix GeneChip 500 K and Illumina Immunochip microarrays. We demonstrate that the sample size of the reference panel, rather than SNP density of the genotyping platform, is critical to achieve high imputation accuracy. Using the larger T1DGC reference panel, the average accuracy at four-digit resolution is 94.7% using the low-density Affymetrix GeneChip 500 K, and 96.7% using the high-density Illumina Immunochip. For amino acid polymorphisms within HLA genes, we achieve 98.6% and 99.3% accuracy using the Affymetrix GeneChip 500 K and Illumina Immunochip, respectively. Finally, we demonstrate how imputation and association testing at amino acid resolution can facilitate fine-mapping of primary MHC association signals, giving a specific example from type 1 diabetes.

Partial F-tests with multiply imputed data in the linear regression framework via coefficient of determination.

Science.gov (United States)

Chaurasia, Ashok; Harel, Ofer

2015-02-10

Tests for regression coefficients such as global, local, and partial F-tests are common in applied research. In the framework of multiple imputation, there are several papers addressing tests for regression coefficients. However, for simultaneous hypothesis testing, the existing methods are computationally intensive because they involve calculation with vectors and (inversion of) matrices. In this paper, we propose a simple method based on the scalar entity, coefficient of determination, to perform (global, local, and partial) F-tests with multiply imputed data. The proposed method is evaluated using simulated data and applied to suicide prevention data. Copyright © 2014 John Wiley & Sons, Ltd.

Imputation across genotyping arrays for genome-wide association studies: assessment of bias and a correction strategy.

Science.gov (United States)

Johnson, Eric O; Hancock, Dana B; Levy, Joshua L; Gaddis, Nathan C; Saccone, Nancy L; Bierut, Laura J; Page, Grier P

2013-05-01

A great promise of publicly sharing genome-wide association data is the potential to create composite sets of controls. However, studies often use different genotyping arrays, and imputation to a common set of SNPs has shown substantial bias: a problem which has no broadly applicable solution. Based on the idea that using differing genotyped SNP sets as inputs creates differential imputation errors and thus bias in the composite set of controls, we examined the degree to which each of the following occurs: (1) imputation based on the union of genotyped SNPs (i.e., SNPs available on one or more arrays) results in bias, as evidenced by spurious associations (type 1 error) between imputed genotypes and arbitrarily assigned case/control status; (2) imputation based on the intersection of genotyped SNPs (i.e., SNPs available on all arrays) does not evidence such bias; and (3) imputation quality varies by the size of the intersection of genotyped SNP sets. Imputations were conducted in European Americans and African Americans with reference to HapMap phase II and III data. Imputation based on the union of genotyped SNPs across the Illumina 1M and 550v3 arrays showed spurious associations for 0.2 % of SNPs: ~2,000 false positives per million SNPs imputed. Biases remained problematic for very similar arrays (550v1 vs. 550v3) and were substantial for dissimilar arrays (Illumina 1M vs. Affymetrix 6.0). In all instances, imputing based on the intersection of genotyped SNPs (as few as 30 % of the total SNPs genotyped) eliminated such bias while still achieving good imputation quality.

Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

Science.gov (United States)

Resche-Rigon, Matthieu; White, Ian R

2018-06-01

In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

Classifier Fusion With Contextual Reliability Evaluation.

Science.gov (United States)

Liu, Zhunga; Pan, Quan; Dezert, Jean; Han, Jun-Wei; He, You

2018-05-01

Classifier fusion is an efficient strategy to improve the classification performance for the complex pattern recognition problem. In practice, the multiple classifiers to combine can have different reliabilities and the proper reliability evaluation plays an important role in the fusion process for getting the best classification performance. We propose a new method for classifier fusion with contextual reliability evaluation (CF-CRE) based on inner reliability and relative reliability concepts. The inner reliability, represented by a matrix, characterizes the probability of the object belonging to one class when it is classified to another class. The elements of this matrix are estimated from the -nearest neighbors of the object. A cautious discounting rule is developed under belief functions framework to revise the classification result according to the inner reliability. The relative reliability is evaluated based on a new incompatibility measure which allows to reduce the level of conflict between the classifiers by applying the classical evidence discounting rule to each classifier before their combination. The inner reliability and relative reliability capture different aspects of the classification reliability. The discounted classification results are combined with Dempster-Shafer's rule for the final class decision making support. The performance of CF-CRE have been evaluated and compared with those of main classical fusion methods using real data sets. The experimental results show that CF-CRE can produce substantially higher accuracy than other fusion methods in general. Moreover, CF-CRE is robust to the changes of the number of nearest neighbors chosen for estimating the reliability matrix, which is appealing for the applications.

Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies

Directory of Open Access Journals (Sweden)

McElwee Joshua

2009-06-01

Full Text Available Abstract Background Although high-throughput genotyping arrays have made whole-genome association studies (WGAS feasible, only a small proportion of SNPs in the human genome are actually surveyed in such studies. In addition, various SNP arrays assay different sets of SNPs, which leads to challenges in comparing results and merging data for meta-analyses. Genome-wide imputation of untyped markers allows us to address these issues in a direct fashion. Methods 384 Caucasian American liver donors were genotyped using Illumina 650Y (Ilmn650Y arrays, from which we also derived genotypes from the Ilmn317K array. On these data, we compared two imputation methods: MACH and BEAGLE. We imputed 2.5 million HapMap Release22 SNPs, and conducted GWAS on ~40,000 liver mRNA expression traits (eQTL analysis. In addition, 200 Caucasian American and 200 African American subjects were genotyped using the Affymetrix 500 K array plus a custom 164 K fill-in chip. We then imputed the HapMap SNPs and quantified the accuracy by randomly masking observed SNPs. Results MACH and BEAGLE perform similarly with respect to imputation accuracy. The Ilmn650Y results in excellent imputation performance, and it outperforms Affx500K or Ilmn317K sets. For Caucasian Americans, 90% of the HapMap SNPs were imputed at 98% accuracy. As expected, imputation of poorly tagged SNPs (untyped SNPs in weak LD with typed markers was not as successful. It was more challenging to impute genotypes in the African American population, given (1 shorter LD blocks and (2 admixture with Caucasian populations in this population. To address issue (2, we pooled HapMap CEU and YRI data as an imputation reference set, which greatly improved overall performance. The approximate 40,000 phenotypes scored in these populations provide a path to determine empirically how the power to detect associations is affected by the imputation procedures. That is, at a fixed false discovery rate, the number of cis

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

NARCIS (Netherlands)

I. Tachmazidou (Ioanna); Süveges, D. (Dániel); J. Min (Josine); G.R.S. Ritchie (Graham R.S.); Steinberg, J. (Julia); K. Walter (Klaudia); V. Iotchkova (Valentina); J.A. Schwartzentruber (Jeremy); J. Huang (Jian); Y. Memari (Yasin); McCarthy, S. (Shane); Crawford, A.A. (Andrew A.); C. Bombieri (Cristina); M. Cocca (Massimiliano); A.-E. Farmaki (Aliki-Eleni); T.R. Gaunt (Tom); P. Jousilahti (Pekka); M.N. Kooijman (Marjolein ); Lehne, B. (Benjamin); G. Malerba (Giovanni); S. Männistö (Satu); A. Matchan (Angela); M.C. Medina-Gomez (Carolina); S. Metrustry (Sarah); A. Nag (Abhishek); I. Ntalla (Ioanna); L. Paternoster (Lavinia); N.W. Rayner (Nigel William); C. Sala (Cinzia); W.R. Scott (William R.); H.A. Shihab (Hashem A.); L. Southam (Lorraine); B. St Pourcain (Beate); M. Traglia (Michela); K. Trajanoska (Katerina); Zaza, G. (Gialuigi); W. Zhang (Weihua); M.S. Artigas; Bansal, N. (Narinder); M. Benn (Marianne); Chen, Z. (Zhongsheng); P. Danecek (Petr); Lin, W.-Y. (Wei-Yu); A. Locke (Adam); J. Luan (Jian'An); A.K. Manning (Alisa); Mulas, A. (Antonella); C. Sidore (Carlo); A. Tybjaerg-Hansen; A. Varbo (Anette); M. Zoledziewska (Magdalena); C. Finan (Chris); Hatzikotoulas, K. (Konstantinos); A.E. Hendricks (Audrey E.); J.P. Kemp (John); A. Moayyeri (Alireza); Panoutsopoulou, K. (Kalliope); Szpak, M. (Michal); S.G. Wilson (Scott); M. Boehnke (Michael); F. Cucca (Francesco); Di Angelantonio, E. (Emanuele); C. Langenberg (Claudia); C.M. Lindgren (Cecilia M.); McCarthy, M.I. (Mark I.); A.P. Morris (Andrew); B.G. Nordestgaard (Børge); R.A. Scott (Robert); M.D. Tobin (Martin); N.J. Wareham (Nick); P.R. Burton (Paul); J.C. Chambers (John); Smith, G.D. (George Davey); G.V. Dedoussis (George); J.F. Felix (Janine); O.H. Franco (Oscar); Gambaro, G. (Giovanni); P. Gasparini (Paolo); C.J. Hammond (Christopher J.); A. Hofman (Albert); V.W.V. Jaddoe (Vincent); M.E. Kleber (Marcus); J.S. Kooner (Jaspal S.); M. Perola (Markus); C.L. Relton (Caroline); S.M. Ring (Susan); F. Rivadeneira Ramirez (Fernando); V. Salomaa (Veikko); T.D. Spector (Timothy); O. Stegle (Oliver); D. Toniolo (Daniela); A.G. Uitterlinden (André); I.E. Barroso (Inês); C.M.T. Greenwood (Celia); Perry, J.R.B. (John R.B.); Walker, B.R. (Brian R.); A.S. Butterworth (Adam); Y. Xue (Yali); R. Durbin (Richard); K.S. Small (Kerrin); N. Soranzo (Nicole); N.J. Timpson (Nicholas); E. Zeggini (Eleftheria)

2016-01-01

textabstractDeep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

DEFF Research Database (Denmark)

Tachmazidou, Ioanna; Süveges, Dániel; Min, Josine L

2017-01-01

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader alleli...

Time Series Imputation via L1 Norm-Based Singular Spectrum Analysis

Science.gov (United States)

Kalantari, Mahdi; Yarmohammadi, Masoud; Hassani, Hossein; Silva, Emmanuel Sirimal

Missing values in time series data is a well-known and important problem which many researchers have studied extensively in various fields. In this paper, a new nonparametric approach for missing value imputation in time series is proposed. The main novelty of this research is applying the L1 norm-based version of Singular Spectrum Analysis (SSA), namely L1-SSA which is robust against outliers. The performance of the new imputation method has been compared with many other established methods. The comparison is done by applying them to various real and simulated time series. The obtained results confirm that the SSA-based methods, especially L1-SSA can provide better imputation in comparison to other methods.

An Evaluation Method of Equipment Reliability Configuration Management

Science.gov (United States)

Wang, Wei; Feng, Weijia; Zhang, Wei; Li, Yuan

2018-01-01

At present, many equipment development companies have been aware of the great significance of reliability of the equipment development. But, due to the lack of effective management evaluation method, it is very difficult for the equipment development company to manage its own reliability work. Evaluation method of equipment reliability configuration management is to determine the reliability management capabilities of equipment development company. Reliability is not only designed, but also managed to achieve. This paper evaluates the reliability management capabilities by reliability configuration capability maturity model(RCM-CMM) evaluation method.

Fully conditional specification in multivariate imputation

NARCIS (Netherlands)

van Buuren, S.; Brand, J. P.L.; Groothuis-Oudshoorn, C. G.M.; Rubin, D. B.

2006-01-01

The use of the Gibbs sampler with fully conditionally specified models, where the distribution of each variable given the other variables is the starting point, has become a popular method to create imputations in incomplete multivariate data. The theoretical weakness of this approach is that the

Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information

Science.gov (United States)

Poyatos, Rafael; Sus, Oliver; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi

2018-05-01

The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density) in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2). We simulated gaps at different missingness levels (10-80 %) in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN), ordinary and regression kriging, and multivariate imputation using chained equations (MICE) to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %), species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables allowed us to fill the gaps in

Validation of Land Cover Products Using Reliability Evaluation Methods

Directory of Open Access Journals (Sweden)

Wenzhong Shi

2015-06-01

Full Text Available Validation of land cover products is a fundamental task prior to data applications. Current validation schemes and methods are, however, suited only for assessing classification accuracy and disregard the reliability of land cover products. The reliability evaluation of land cover products should be undertaken to provide reliable land cover information. In addition, the lack of high-quality reference data often constrains validation and affects the reliability results of land cover products. This study proposes a validation schema to evaluate the reliability of land cover products, including two methods, namely, result reliability evaluation and process reliability evaluation. Result reliability evaluation computes the reliability of land cover products using seven reliability indicators. Process reliability evaluation analyzes the reliability propagation in the data production process to obtain the reliability of land cover products. Fuzzy fault tree analysis is introduced and improved in the reliability analysis of a data production process. Research results show that the proposed reliability evaluation scheme is reasonable and can be applied to validate land cover products. Through the analysis of the seven indicators of result reliability evaluation, more information on land cover can be obtained for strategic decision-making and planning, compared with traditional accuracy assessment methods. Process reliability evaluation without the need for reference data can facilitate the validation and reflect the change trends of reliabilities to some extent.

Comparison of three boosting methods in parent-offspring trios for genotype imputation using simulation study

Directory of Open Access Journals (Sweden)

Abbas Mikhchi

2016-01-01

Full Text Available Abstract Background Genotype imputation is an important process of predicting unknown genotypes, which uses reference population with dense genotypes to predict missing genotypes for both human and animal genetic variations at a low cost. Machine learning methods specially boosting methods have been used in genetic studies to explore the underlying genetic profile of disease and build models capable of predicting missing values of a marker. Methods In this study strategies and factors affecting the imputation accuracy of parent-offspring trios compared from lower-density SNP panels (5 K to high density (10 K SNP panel using three different Boosting methods namely TotalBoost (TB, LogitBoost (LB and AdaBoost (AB. The methods employed using simulated data to impute the un-typed SNPs in parent-offspring trios. Four different datasets of G1 (100 trios with 5 k SNPs, G2 (100 trios with 10 k SNPs, G3 (500 trios with 5 k SNPs, and G4 (500 trio with 10 k SNPs were simulated. In four datasets all parents were genotyped completely, and offspring genotyped with a lower density panel. Results Comparison of the three methods for imputation showed that the LB outperformed AB and TB for imputation accuracy. The time of computation were different between methods. The AB was the fastest algorithm. The higher SNP densities resulted the increase of the accuracy of imputation. Larger trios (i.e. 500 was better for performance of LB and TB. Conclusions The conclusion is that the three methods do well in terms of imputation accuracy also the dense chip is recommended for imputation of parent-offspring trios.

Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

Science.gov (United States)

Seaman, Shaun R; Hughes, Rachael A

2018-06-01

Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

A New Missing Data Imputation Algorithm Applied to Electrical Data Loggers

Directory of Open Access Journals (Sweden)

Concepción Crespo Turrado

2015-12-01

Full Text Available Nowadays, data collection is a key process in the study of electrical power networks when searching for harmonics and a lack of balance among phases. In this context, the lack of data of any of the main electrical variables (phase-to-neutral voltage, phase-to-phase voltage, and current in each phase and power factor adversely affects any time series study performed. When this occurs, a data imputation process must be accomplished in order to substitute the data that is missing for estimated values. This paper presents a novel missing data imputation method based on multivariate adaptive regression splines (MARS and compares it with the well-known technique called multivariate imputation by chained equations (MICE. The results obtained demonstrate how the proposed method outperforms the MICE algorithm.

Imputation of missing data in time series for air pollutants

Science.gov (United States)

Junger, W. L.; Ponce de Leon, A.

2015-02-01

Missing data are major concerns in epidemiological studies of the health effects of environmental air pollutants. This article presents an imputation-based method that is suitable for multivariate time series data, which uses the EM algorithm under the assumption of normal distribution. Different approaches are considered for filtering the temporal component. A simulation study was performed to assess validity and performance of proposed method in comparison with some frequently used methods. Simulations showed that when the amount of missing data was as low as 5%, the complete data analysis yielded satisfactory results regardless of the generating mechanism of the missing data, whereas the validity began to degenerate when the proportion of missing values exceeded 10%. The proposed imputation method exhibited good accuracy and precision in different settings with respect to the patterns of missing observations. Most of the imputations obtained valid results, even under missing not at random. The methods proposed in this study are implemented as a package called mtsdi for the statistical software system R.

Missing data treatments matter: an analysis of multiple imputation for anterior cervical discectomy and fusion procedures.

Science.gov (United States)

Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Cui, Jonathan J; Basques, Bryce A; Albert, Todd J; Grauer, Jonathan N

2018-04-09

The presence of missing data is a limitation of large datasets, including the National Surgical Quality Improvement Program (NSQIP). In addressing this issue, most studies use complete case analysis, which excludes cases with missing data, thus potentially introducing selection bias. Multiple imputation, a statistically rigorous approach that approximates missing data and preserves sample size, may be an improvement over complete case analysis. The present study aims to evaluate the impact of using multiple imputation in comparison with complete case analysis for assessing the associations between preoperative laboratory values and adverse outcomes following anterior cervical discectomy and fusion (ACDF) procedures. This is a retrospective review of prospectively collected data. Patients undergoing one-level ACDF were identified in NSQIP 2012-2015. Perioperative adverse outcome variables assessed included the occurrence of any adverse event, severe adverse events, and hospital readmission. Missing preoperative albumin and hematocrit values were handled using complete case analysis and multiple imputation. These preoperative laboratory levels were then tested for associations with 30-day postoperative outcomes using logistic regression. A total of 11,999 patients were included. Of this cohort, 63.5% of patients had missing preoperative albumin and 9.9% had missing preoperative hematocrit. When using complete case analysis, only 4,311 patients were studied. The removed patients were significantly younger, healthier, of a common body mass index, and male. Logistic regression analysis failed to identify either preoperative hypoalbuminemia or preoperative anemia as significantly associated with adverse outcomes. When employing multiple imputation, all 11,999 patients were included. Preoperative hypoalbuminemia was significantly associated with the occurrence of any adverse event and severe adverse events. Preoperative anemia was significantly associated with the

Nonparametric autocovariance estimation from censored time series by Gaussian imputation.

Science.gov (United States)

Park, Jung Wook; Genton, Marc G; Ghosh, Sujit K

2009-02-01

One of the most frequently used methods to model the autocovariance function of a second-order stationary time series is to use the parametric framework of autoregressive and moving average models developed by Box and Jenkins. However, such parametric models, though very flexible, may not always be adequate to model autocovariance functions with sharp changes. Furthermore, if the data do not follow the parametric model and are censored at a certain value, the estimation results may not be reliable. We develop a Gaussian imputation method to estimate an autocovariance structure via nonparametric estimation of the autocovariance function in order to address both censoring and incorrect model specification. We demonstrate the effectiveness of the technique in terms of bias and efficiency with simulations under various rates of censoring and underlying models. We describe its application to a time series of silicon concentrations in the Arctic.

PRIMAL: Fast and accurate pedigree-based imputation from sequence data in a founder population.

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Oren E Livne

2015-03-01

Full Text Available Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm, a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs, from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.

Multiple imputation of missing passenger boarding data in the national census of ferry operators

Science.gov (United States)

2008-08-01

This report presents findings from the 2006 National Census of Ferry Operators (NCFO) augmented with imputed values for passengers and passenger miles. Due to the imputation procedures used to calculate missing data, totals in Table 1 may not corresp...

Sequence imputation of HPV16 genomes for genetic association studies.

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Benjamin Smith

Full Text Available Human Papillomavirus type 16 (HPV16 causes over half of all cervical cancer and some HPV16 variants are more oncogenic than others. The genetic basis for the extraordinary oncogenic properties of HPV16 compared to other HPVs is unknown. In addition, we neither know which nucleotides vary across and within HPV types and lineages, nor which of the single nucleotide polymorphisms (SNPs determine oncogenicity.A reference set of 62 HPV16 complete genome sequences was established and used to examine patterns of evolutionary relatedness amongst variants using a pairwise identity heatmap and HPV16 phylogeny. A BLAST-based algorithm was developed to impute complete genome data from partial sequence information using the reference database. To interrogate the oncogenic risk of determined and imputed HPV16 SNPs, odds-ratios for each SNP were calculated in a case-control viral genome-wide association study (VWAS using biopsy confirmed high-grade cervix neoplasia and self-limited HPV16 infections from Guanacaste, Costa Rica.HPV16 variants display evolutionarily stable lineages that contain conserved diagnostic SNPs. The imputation algorithm indicated that an average of 97.5±1.03% of SNPs could be accurately imputed. The VWAS revealed specific HPV16 viral SNPs associated with variant lineages and elevated odds ratios; however, individual causal SNPs could not be distinguished with certainty due to the nature of HPV evolution.Conserved and lineage-specific SNPs can be imputed with a high degree of accuracy from limited viral polymorphic data due to the lack of recombination and the stochastic mechanism of variation accumulation in the HPV genome. However, to determine the role of novel variants or non-lineage-specific SNPs by VWAS will require direct sequence analysis. The investigation of patterns of genetic variation and the identification of diagnostic SNPs for lineages of HPV16 variants provides a valuable resource for future studies of HPV16

Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information

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R. Poyatos

2018-05-01

Full Text Available The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2. We simulated gaps at different missingness levels (10–80 % in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN, ordinary and regression kriging, and multivariate imputation using chained equations (MICE to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %, species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables

Reliability evaluation for offshore wind farms

DEFF Research Database (Denmark)

Zhao, Menghua; Blåbjerg, Frede; Chen, Zhe

2005-01-01

In this paper, a new reliability index - Loss Of Generation Ratio Probability (LOGRP) is proposed for evaluating the reliability of an electrical system for offshore wind farms, which emphasizes the design of wind farms rather than the adequacy for specific load demand. A practical method...... to calculate LOGRP of offshore wind farms is proposed and evaluated....

Imputation Accuracy from Low to Moderate Density Single Nucleotide Polymorphism Chips in a Thai Multibreed Dairy Cattle Population

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Danai Jattawa

2016-04-01

Full Text Available The objective of this study was to investigate the accuracy of imputation from low density (LDC to moderate density SNP chips (MDC in a Thai Holstein-Other multibreed dairy cattle population. Dairy cattle with complete pedigree information (n = 1,244 from 145 dairy farms were genotyped with GeneSeek GGP20K (n = 570, GGP26K (n = 540 and GGP80K (n = 134 chips. After checking for single nucleotide polymorphism (SNP quality, 17,779 SNP markers in common between the GGP20K, GGP26K, and GGP80K were used to represent MDC. Animals were divided into two groups, a reference group (n = 912 and a test group (n = 332. The SNP markers chosen for the test group were those located in positions corresponding to GeneSeek GGP9K (n = 7,652. The LDC to MDC genotype imputation was carried out using three different software packages, namely Beagle 3.3 (population-based algorithm, FImpute 2.2 (combined family- and population-based algorithms and Findhap 4 (combined family- and population-based algorithms. Imputation accuracies within and across chromosomes were calculated as ratios of correctly imputed SNP markers to overall imputed SNP markers. Imputation accuracy for the three software packages ranged from 76.79% to 93.94%. FImpute had higher imputation accuracy (93.94% than Findhap (84.64% and Beagle (76.79%. Imputation accuracies were similar and consistent across chromosomes for FImpute, but not for Findhap and Beagle. Most chromosomes that showed either high (73% or low (80% imputation accuracies were the same chromosomes that had above and below average linkage disequilibrium (LD; defined here as the correlation between pairs of adjacent SNP within chromosomes less than or equal to 1 Mb apart. Results indicated that FImpute was more suitable than Findhap and Beagle for genotype imputation in this Thai multibreed population. Perhaps additional increments in imputation accuracy could be achieved by increasing the completeness of pedigree information.

The utility of imputed matched sets. Analyzing probabilistically linked databases in a low information setting.

Science.gov (United States)

Thomas, A M; Cook, L J; Dean, J M; Olson, L M

2014-01-01

To compare results from high probability matched sets versus imputed matched sets across differing levels of linkage information. A series of linkages with varying amounts of available information were performed on two simulated datasets derived from multiyear motor vehicle crash (MVC) and hospital databases, where true matches were known. Distributions of high probability and imputed matched sets were compared against the true match population for occupant age, MVC county, and MVC hour. Regression models were fit to simulated log hospital charges and hospitalization status. High probability and imputed matched sets were not significantly different from occupant age, MVC county, and MVC hour in high information settings (p > 0.999). In low information settings, high probability matched sets were significantly different from occupant age and MVC county (p sets were not (p > 0.493). High information settings saw no significant differences in inference of simulated log hospital charges and hospitalization status between the two methods. High probability and imputed matched sets were significantly different from the outcomes in low information settings; however, imputed matched sets were more robust. The level of information available to a linkage is an important consideration. High probability matched sets are suitable for high to moderate information settings and for situations involving case-specific analysis. Conversely, imputed matched sets are preferable for low information settings when conducting population-based analyses.

Flexible Modeling of Survival Data with Covariates Subject to Detection Limits via Multiple Imputation.

Science.gov (United States)

Bernhardt, Paul W; Wang, Huixia Judy; Zhang, Daowen

2014-01-01

Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time model with a flexible seminonparametric error distribution. The consistency and asymptotic normality of the multiple imputation estimator are established and a consistent variance estimator is provided. An iterative version of the proposed multiple imputation algorithm that approximates the EM algorithm for maximum likelihood is also suggested. Simulation studies demonstrate that the proposed multiple imputation methods work well while alternative methods lead to estimates that are either biased or more variable. The proposed methods are applied to analyze the dataset from a recently-conducted GenIMS study.

A suggested approach for imputation of missing dietary data for young children in daycare.

Science.gov (United States)

Stevens, June; Ou, Fang-Shu; Truesdale, Kimberly P; Zeng, Donglin; Vaughn, Amber E; Pratt, Charlotte; Ward, Dianne S

2015-01-01

Parent-reported 24-h diet recalls are an accepted method of estimating intake in young children. However, many children eat while at childcare making accurate proxy reports by parents difficult. The goal of this study was to demonstrate a method to impute missing weekday lunch and daytime snack nutrient data for daycare children and to explore the concurrent predictive and criterion validity of the method. Data were from children aged 2-5 years in the My Parenting SOS project (n=308; 870 24-h diet recalls). Mixed models were used to simultaneously predict breakfast, dinner, and evening snacks (B+D+ES); lunch; and daytime snacks for all children after adjusting for age, sex, and body mass index (BMI). From these models, we imputed the missing weekday daycare lunches by interpolation using the mean lunch to B+D+ES [L/(B+D+ES)] ratio among non-daycare children on weekdays and the L/(B+D+ES) ratio for all children on weekends. Daytime snack data were used to impute snacks. The reported mean (± standard deviation) weekday intake was lower for daycare children [725 (±324) kcal] compared to non-daycare children [1,048 (±463) kcal]. Weekend intake for all children was 1,173 (±427) kcal. After imputation, weekday caloric intake for daycare children was 1,230 (±409) kcal. Daily intakes that included imputed data were associated with age and sex but not with BMI. This work indicates that imputation is a promising method for improving the precision of daily nutrient data from young children.

Limitations in Using Multiple Imputation to Harmonize Individual Participant Data for Meta-Analysis.

Science.gov (United States)

Siddique, Juned; de Chavez, Peter J; Howe, George; Cruden, Gracelyn; Brown, C Hendricks

2018-02-01

Individual participant data (IPD) meta-analysis is a meta-analysis in which the individual-level data for each study are obtained and used for synthesis. A common challenge in IPD meta-analysis is when variables of interest are measured differently in different studies. The term harmonization has been coined to describe the procedure of placing variables on the same scale in order to permit pooling of data from a large number of studies. Using data from an IPD meta-analysis of 19 adolescent depression trials, we describe a multiple imputation approach for harmonizing 10 depression measures across the 19 trials by treating those depression measures that were not used in a study as missing data. We then apply diagnostics to address the fit of our imputation model. Even after reducing the scale of our application, we were still unable to produce accurate imputations of the missing values. We describe those features of the data that made it difficult to harmonize the depression measures and provide some guidelines for using multiple imputation for harmonization in IPD meta-analysis.

UniFIeD Univariate Frequency-based Imputation for Time Series Data

OpenAIRE

Friese, Martina; Stork, Jörg; Ramos Guerra, Ricardo; Bartz-Beielstein, Thomas; Thaker, Soham; Flasch, Oliver; Zaefferer, Martin

2013-01-01

This paper introduces UniFIeD, a new data preprocessing method for time series. UniFIeD can cope with large intervals of missing data. A scalable test function generator, which allows the simulation of time series with different gap sizes, is presented additionally. An experimental study demonstrates that (i) UniFIeD shows a significant better performance than simple imputation methods and (ii) UniFIeD is able to handle situations, where advanced imputation methods fail. The results are indep...

Quick, “Imputation-free” meta-analysis with proxy-SNPs

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Meesters Christian

2012-09-01

Full Text Available Abstract Background Meta-analysis (MA is widely used to pool genome-wide association studies (GWASes in order to a increase the power to detect strong or weak genotype effects or b as a result verification method. As a consequence of differing SNP panels among genotyping chips, imputation is the method of choice within GWAS consortia to avoid losing too many SNPs in a MA. YAMAS (Yet Another Meta Analysis Software, however, enables cross-GWAS conclusions prior to finished and polished imputation runs, which eventually are time-consuming. Results Here we present a fast method to avoid forfeiting SNPs present in only a subset of studies, without relying on imputation. This is accomplished by using reference linkage disequilibrium data from 1,000 Genomes/HapMap projects to find proxy-SNPs together with in-phase alleles for SNPs missing in at least one study. MA is conducted by combining association effect estimates of a SNP and those of its proxy-SNPs. Our algorithm is implemented in the MA software YAMAS. Association results from GWAS analysis applications can be used as input files for MA, tremendously speeding up MA compared to the conventional imputation approach. We show that our proxy algorithm is well-powered and yields valuable ad hoc results, possibly providing an incentive for follow-up studies. We propose our method as a quick screening step prior to imputation-based MA, as well as an additional main approach for studies without available reference data matching the ethnicities of study participants. As a proof of principle, we analyzed six dbGaP Type II Diabetes GWAS and found that the proxy algorithm clearly outperforms naïve MA on the p-value level: for 17 out of 23 we observe an improvement on the p-value level by a factor of more than two, and a maximum improvement by a factor of 2127. Conclusions YAMAS is an efficient and fast meta-analysis program which offers various methods, including conventional MA as well as inserting proxy

Dealing with missing data in a multi-question depression scale: a comparison of imputation methods

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Stuart Heather

2006-12-01

Full Text Available Abstract Background Missing data present a challenge to many research projects. The problem is often pronounced in studies utilizing self-report scales, and literature addressing different strategies for dealing with missing data in such circumstances is scarce. The objective of this study was to compare six different imputation techniques for dealing with missing data in the Zung Self-reported Depression scale (SDS. Methods 1580 participants from a surgical outcomes study completed the SDS. The SDS is a 20 question scale that respondents complete by circling a value of 1 to 4 for each question. The sum of the responses is calculated and respondents are classified as exhibiting depressive symptoms when their total score is over 40. Missing values were simulated by randomly selecting questions whose values were then deleted (a missing completely at random simulation. Additionally, a missing at random and missing not at random simulation were completed. Six imputation methods were then considered; 1 multiple imputation, 2 single regression, 3 individual mean, 4 overall mean, 5 participant's preceding response, and 6 random selection of a value from 1 to 4. For each method, the imputed mean SDS score and standard deviation were compared to the population statistics. The Spearman correlation coefficient, percent misclassified and the Kappa statistic were also calculated. Results When 10% of values are missing, all the imputation methods except random selection produce Kappa statistics greater than 0.80 indicating 'near perfect' agreement. MI produces the most valid imputed values with a high Kappa statistic (0.89, although both single regression and individual mean imputation also produced favorable results. As the percent of missing information increased to 30%, or when unbalanced missing data were introduced, MI maintained a high Kappa statistic. The individual mean and single regression method produced Kappas in the 'substantial agreement' range

Learning-Based Adaptive Imputation Methodwith kNN Algorithm for Missing Power Data

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Minkyung Kim

2017-10-01

Full Text Available This paper proposes a learning-based adaptive imputation method (LAI for imputing missing power data in an energy system. This method estimates the missing power data by using the pattern that appears in the collected data. Here, in order to capture the patterns from past power data, we newly model a feature vector by using past data and its variations. The proposed LAI then learns the optimal length of the feature vector and the optimal historical length, which are significant hyper parameters of the proposed method, by utilizing intentional missing data. Based on a weighted distance between feature vectors representing a missing situation and past situation, missing power data are estimated by referring to the k most similar past situations in the optimal historical length. We further extend the proposed LAI to alleviate the effect of unexpected variation in power data and refer to this new approach as the extended LAI method (eLAI. The eLAI selects a method between linear interpolation (LI and the proposed LAI to improve accuracy under unexpected variations. Finally, from a simulation under various energy consumption profiles, we verify that the proposed eLAI achieves about a 74% reduction of the average imputation error in an energy system, compared to the existing imputation methods.

A suggested approach for imputation of missing dietary data for young children in daycare

Directory of Open Access Journals (Sweden)

June Stevens

2015-12-01

Full Text Available Background: Parent-reported 24-h diet recalls are an accepted method of estimating intake in young children. However, many children eat while at childcare making accurate proxy reports by parents difficult. Objective: The goal of this study was to demonstrate a method to impute missing weekday lunch and daytime snack nutrient data for daycare children and to explore the concurrent predictive and criterion validity of the method. Design: Data were from children aged 2-5 years in the My Parenting SOS project (n=308; 870 24-h diet recalls. Mixed models were used to simultaneously predict breakfast, dinner, and evening snacks (B+D+ES; lunch; and daytime snacks for all children after adjusting for age, sex, and body mass index (BMI. From these models, we imputed the missing weekday daycare lunches by interpolation using the mean lunch to B+D+ES [L/(B+D+ES] ratio among non-daycare children on weekdays and the L/(B+D+ES ratio for all children on weekends. Daytime snack data were used to impute snacks. Results: The reported mean (± standard deviation weekday intake was lower for daycare children [725 (±324 kcal] compared to non-daycare children [1,048 (±463 kcal]. Weekend intake for all children was 1,173 (±427 kcal. After imputation, weekday caloric intake for daycare children was 1,230 (±409 kcal. Daily intakes that included imputed data were associated with age and sex but not with BMI. Conclusion: This work indicates that imputation is a promising method for improving the precision of daily nutrient data from young children.

Inclusion of Population-specific Reference Panel from India to the 1000 Genomes Phase 3 Panel Improves Imputation Accuracy.

Science.gov (United States)

Ahmad, Meraj; Sinha, Anubhav; Ghosh, Sreya; Kumar, Vikrant; Davila, Sonia; Yajnik, Chittaranjan S; Chandak, Giriraj R

2017-07-27

Imputation is a computational method based on the principle of haplotype sharing allowing enrichment of genome-wide association study datasets. It depends on the haplotype structure of the population and density of the genotype data. The 1000 Genomes Project led to the generation of imputation reference panels which have been used globally. However, recent studies have shown that population-specific panels provide better enrichment of genome-wide variants. We compared the imputation accuracy using 1000 Genomes phase 3 reference panel and a panel generated from genome-wide data on 407 individuals from Western India (WIP). The concordance of imputed variants was cross-checked with next-generation re-sequencing data on a subset of genomic regions. Further, using the genome-wide data from 1880 individuals, we demonstrate that WIP works better than the 1000 Genomes phase 3 panel and when merged with it, significantly improves the imputation accuracy throughout the minor allele frequency range. We also show that imputation using only South Asian component of the 1000 Genomes phase 3 panel works as good as the merged panel, making it computationally less intensive job. Thus, our study stresses that imputation accuracy using 1000 Genomes phase 3 panel can be further improved by including population-specific reference panels from South Asia.

Increasing imputation and prediction accuracy for Chinese Holsteins using joint Chinese-Nordic reference population

DEFF Research Database (Denmark)

Ma, Peipei; Lund, Mogens Sandø; Ding, X

2015-01-01

This study investigated the effect of including Nordic Holsteins in the reference population on the imputation accuracy and prediction accuracy for Chinese Holsteins. The data used in this study include 85 Chinese Holstein bulls genotyped with both 54K chip and 777K (HD) chip, 2862 Chinese cows...... was improved slightly when using the marker data imputed based on the combined HD reference data, compared with using the marker data imputed based on the Chinese HD reference data only. On the other hand, when using the combined reference population including 4398 Nordic Holstein bulls, the accuracy...... to increase reference population rather than increasing marker density...

Factors associated with low birth weight in Nepal using multiple imputation

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Usha Singh

2017-02-01

Full Text Available Abstract Background Survey data from low income countries on birth weight usually pose a persistent problem. The studies conducted on birth weight have acknowledged missing data on birth weight, but they are not included in the analysis. Furthermore, other missing data presented on determinants of birth weight are not addressed. Thus, this study tries to identify determinants that are associated with low birth weight (LBW using multiple imputation to handle missing data on birth weight and its determinants. Methods The child dataset from Nepal Demographic and Health Survey (NDHS, 2011 was utilized in this study. A total of 5,240 children were born between 2006 and 2011, out of which 87% had at least one measured variable missing and 21% had no recorded birth weight. All the analyses were carried out in R version 3.1.3. Transform-then impute method was applied to check for interaction between explanatory variables and imputed missing data. Survey package was applied to each imputed dataset to account for survey design and sampling method. Survey logistic regression was applied to identify the determinants associated with LBW. Results The prevalence of LBW was 15.4% after imputation. Women with the highest autonomy on their own health compared to those with health decisions involving husband or others (adjusted odds ratio (OR 1.87, 95% confidence interval (95% CI = 1.31, 2.67, and husband and women together (adjusted OR 1.57, 95% CI = 1.05, 2.35 were less likely to give birth to LBW infants. Mothers using highly polluting cooking fuels (adjusted OR 1.49, 95% CI = 1.03, 2.22 were more likely to give birth to LBW infants than mothers using non-polluting cooking fuels. Conclusion The findings of this study suggested that obtaining the prevalence of LBW from only the sample of measured birth weight and ignoring missing data results in underestimation.

Evaluation criteria of structural steel reliability

International Nuclear Information System (INIS)

Zav'yalov, A.S.

1980-01-01

Different low-carbon and medium-carbon structural steels are investigated. It is stated that steel reliability evaluation criteria depend on the fracture mode, steel suffering from the brittle fracture under the influence of the stresses (despite their great variety) arising in articles during the production and operation. Fibrous steel fracture at the given temperature and article thickness says about its high ductility and toughness and brittle fractures are impossible. Brittle fractures take place in case of a crystalline and mixed fracture with a predominant crystalline component. Evaluation methods of article and sample steel structural strength differing greatly from real articles in a thickness (diameter) or used at temperatures higher than possible operation temperatures cannot be reliability evaluation criteria because at a great thickness (diameter) and lower operation temperatures steel fracture and its strain mode can change resulting in a sharp reliability degradation

Comparison of different methods for imputing genome-wide marker genotypes in Swedish and Finnish Red Cattle

DEFF Research Database (Denmark)

Ma, Peipei; Brøndum, Rasmus Froberg; Qin, Zahng

2013-01-01

This study investigated the imputation accuracy of different methods, considering both the minor allele frequency and relatedness between individuals in the reference and test data sets. Two data sets from the combined population of Swedish and Finnish Red Cattle were used to test the influence...... coefficient was lower when the minor allele frequency was lower. The results indicate that Beagle and IMPUTE2 provide the most robust and accurate imputation accuracies, but considering computing time and memory usage, FImpute is another alternative method....

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

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Wilson Barry Tyler

2013-01-01

Full Text Available Abstract The U.S. has been providing national-scale estimates of forest carbon (C stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon and spatial scales (e.g., sub-county to biome. Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations. In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area, with weaker agreement for detrital pools (e.g., standing dead trees. Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC and regional scales (e.g., Reducing Emissions from Deforestation and Forest

Reliability evaluation of power systems

CERN Document Server

Billinton, Roy

1996-01-01

The Second Edition of this well-received textbook presents over a decade of new research in power system reliability-while maintaining the general concept, structure, and style of the original volume. This edition features new chapters on the growing areas of Monte Carlo simulation and reliability economics. In addition, chapters cover the latest developments in techniques and their application to real problems. The text also explores the progress occurring in the structure, planning, and operation of real power systems due to changing ownership, regulation, and access. This work serves as a companion volume to Reliability Evaluation of Engineering Systems: Second Edition (1992).

TRANSPOSABLE REGULARIZED COVARIANCE MODELS WITH AN APPLICATION TO MISSING DATA IMPUTATION.

Science.gov (United States)

Allen, Genevera I; Tibshirani, Robert

2010-06-01

Missing data estimation is an important challenge with high-dimensional data arranged in the form of a matrix. Typically this data matrix is transposable , meaning that either the rows, columns or both can be treated as features. To model transposable data, we present a modification of the matrix-variate normal, the mean-restricted matrix-variate normal , in which the rows and columns each have a separate mean vector and covariance matrix. By placing additive penalties on the inverse covariance matrices of the rows and columns, these so called transposable regularized covariance models allow for maximum likelihood estimation of the mean and non-singular covariance matrices. Using these models, we formulate EM-type algorithms for missing data imputation in both the multivariate and transposable frameworks. We present theoretical results exploiting the structure of our transposable models that allow these models and imputation methods to be applied to high-dimensional data. Simulations and results on microarray data and the Netflix data show that these imputation techniques often outperform existing methods and offer a greater degree of flexibility.

Avoid Filling Swiss Cheese with Whipped Cream; Imputation Techniques and Evaluation Procedures for Cross-Country Time Series

OpenAIRE

Michael Weber; Michaela Denk

2011-01-01

International organizations collect data from national authorities to create multivariate cross-sectional time series for their analyses. As data from countries with not yet well-established statistical systems may be incomplete, the bridging of data gaps is a crucial challenge. This paper investigates data structures and missing data patterns in the cross-sectional time series framework, reviews missing value imputation techniques used for micro data in official statistics, and discusses the...

Imputation of missing genotypes within LD-blocks relying on the basic coalescent and beyond: consideration of population growth and structure.

Science.gov (United States)

Kabisch, Maria; Hamann, Ute; Lorenzo Bermejo, Justo

2017-10-17

Genotypes not directly measured in genetic studies are often imputed to improve statistical power and to increase mapping resolution. The accuracy of standard imputation techniques strongly depends on the similarity of linkage disequilibrium (LD) patterns in the study and reference populations. Here we develop a novel approach for genotype imputation in low-recombination regions that relies on the coalescent and permits to explicitly account for population demographic factors. To test the new method, study and reference haplotypes were simulated and gene trees were inferred under the basic coalescent and also considering population growth and structure. The reference haplotypes that first coalesced with study haplotypes were used as templates for genotype imputation. Computer simulations were complemented with the analysis of real data. Genotype concordance rates were used to compare the accuracies of coalescent-based and standard (IMPUTE2) imputation. Simulations revealed that, in LD-blocks, imputation accuracy relying on the basic coalescent was higher and less variable than with IMPUTE2. Explicit consideration of population growth and structure, even if present, did not practically improve accuracy. The advantage of coalescent-based over standard imputation increased with the minor allele frequency and it decreased with population stratification. Results based on real data indicated that, even in low-recombination regions, further research is needed to incorporate recombination in coalescence inference, in particular for studies with genetically diverse and admixed individuals. To exploit the full potential of coalescent-based methods for the imputation of missing genotypes in genetic studies, further methodological research is needed to reduce computer time, to take into account recombination, and to implement these methods in user-friendly computer programs. Here we provide reproducible code which takes advantage of publicly available software to facilitate

Improving accuracy of genomic prediction in Brangus cattle by adding animals with imputed low-density SNP genotypes.

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Lopes, F B; Wu, X-L; Li, H; Xu, J; Perkins, T; Genho, J; Ferretti, R; Tait, R G; Bauck, S; Rosa, G J M

2018-02-01

Reliable genomic prediction of breeding values for quantitative traits requires the availability of sufficient number of animals with genotypes and phenotypes in the training set. As of 31 October 2016, there were 3,797 Brangus animals with genotypes and phenotypes. These Brangus animals were genotyped using different commercial SNP chips. Of them, the largest group consisted of 1,535 animals genotyped by the GGP-LDV4 SNP chip. The remaining 2,262 genotypes were imputed to the SNP content of the GGP-LDV4 chip, so that the number of animals available for training the genomic prediction models was more than doubled. The present study showed that the pooling of animals with both original or imputed 40K SNP genotypes substantially increased genomic prediction accuracies on the ten traits. By supplementing imputed genotypes, the relative gains in genomic prediction accuracies on estimated breeding values (EBV) were from 12.60% to 31.27%, and the relative gain in genomic prediction accuracies on de-regressed EBV was slightly small (i.e. 0.87%-18.75%). The present study also compared the performance of five genomic prediction models and two cross-validation methods. The five genomic models predicted EBV and de-regressed EBV of the ten traits similarly well. Of the two cross-validation methods, leave-one-out cross-validation maximized the number of animals at the stage of training for genomic prediction. Genomic prediction accuracy (GPA) on the ten quantitative traits was validated in 1,106 newly genotyped Brangus animals based on the SNP effects estimated in the previous set of 3,797 Brangus animals, and they were slightly lower than GPA in the original data. The present study was the first to leverage currently available genotype and phenotype resources in order to harness genomic prediction in Brangus beef cattle. © 2018 Blackwell Verlag GmbH.

Accuracy of hemoglobin A1c imputation using fasting plasma glucose in diabetes research using electronic health records data

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Stanley Xu

2014-05-01

Full Text Available In studies that use electronic health record data, imputation of important data elements such as Glycated hemoglobin (A1c has become common. However, few studies have systematically examined the validity of various imputation strategies for missing A1c values. We derived a complete dataset using an incident diabetes population that has no missing values in A1c, fasting and random plasma glucose (FPG and RPG, age, and gender. We then created missing A1c values under two assumptions: missing completely at random (MCAR and missing at random (MAR. We then imputed A1c values, compared the imputed values to the true A1c values, and used these data to assess the impact of A1c on initiation of antihyperglycemic therapy. Under MCAR, imputation of A1c based on FPG 1 estimated a continuous A1c within ± 1.88% of the true A1c 68.3% of the time; 2 estimated a categorical A1c within ± one category from the true A1c about 50% of the time. Including RPG in imputation slightly improved the precision but did not improve the accuracy. Under MAR, including gender and age in addition to FPG improved the accuracy of imputed continuous A1c but not categorical A1c. Moreover, imputation of up to 33% of missing A1c values did not change the accuracy and precision and did not alter the impact of A1c on initiation of antihyperglycemic therapy. When using A1c values as a predictor variable, a simple imputation algorithm based only on age, sex, and fasting plasma glucose gave acceptable results.

Double sampling with multiple imputation to answer large sample meta-research questions: Introduction and illustration by evaluating adherence to two simple CONSORT guidelines

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Patrice L. Capers

2015-03-01

Full Text Available BACKGROUND: Meta-research can involve manual retrieval and evaluation of research, which is resource intensive. Creation of high throughput methods (e.g., search heuristics, crowdsourcing has improved feasibility of large meta-research questions, but possibly at the cost of accuracy. OBJECTIVE: To evaluate the use of double sampling combined with multiple imputation (DS+MI to address meta-research questions, using as an example adherence of PubMed entries to two simple Consolidated Standards of Reporting Trials (CONSORT guidelines for titles and abstracts. METHODS: For the DS large sample, we retrieved all PubMed entries satisfying the filters: RCT; human; abstract available; and English language (n=322,107. For the DS subsample, we randomly sampled 500 entries from the large sample. The large sample was evaluated with a lower rigor, higher throughput (RLOTHI method using search heuristics, while the subsample was evaluated using a higher rigor, lower throughput (RHITLO human rating method. Multiple imputation of the missing-completely-at-random RHITLO data for the large sample was informed by: RHITLO data from the subsample; RLOTHI data from the large sample; whether a study was an RCT; and country and year of publication. RESULTS: The RHITLO and RLOTHI methods in the subsample largely agreed (phi coefficients: title=1.00, abstract=0.92. Compliance with abstract and title criteria has increased over time, with non-US countries improving more rapidly. DS+MI logistic regression estimates were more precise than subsample estimates (e.g., 95% CI for change in title and abstract compliance by Year: subsample RHITLO 1.050-1.174 vs. DS+MI 1.082-1.151. As evidence of improved accuracy, DS+MI coefficient estimates were closer to RHITLO than the large sample RLOTHI. CONCLUSIONS: Our results support our hypothesis that DS+MI would result in improved precision and accuracy. This method is flexible and may provide a practical way to examine large corpora of

Scale Reliability Evaluation with Heterogeneous Populations

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Raykov, Tenko; Marcoulides, George A.

2015-01-01

A latent variable modeling approach for scale reliability evaluation in heterogeneous populations is discussed. The method can be used for point and interval estimation of reliability of multicomponent measuring instruments in populations representing mixtures of an unknown number of latent classes or subpopulations. The procedure is helpful also…

Evaluation for nuclear safety-critical software reliability of DCS

International Nuclear Information System (INIS)

Liu Ying

2015-01-01

With the development of control and information technology at NPPs, software reliability is important because software failure is usually considered as one form of common cause failures in Digital I and C Systems (DCS). The reliability analysis of DCS, particularly qualitative and quantitative evaluation on the nuclear safety-critical software reliability belongs to a great challenge. To solve this problem, not only comprehensive evaluation model and stage evaluation models are built in this paper, but also prediction and sensibility analysis are given to the models. It can make besement for evaluating the reliability and safety of DCS. (author)

Comparing strategies for selection of low-density SNPs for imputation-mediated genomic prediction in U. S. Holsteins.

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He, Jun; Xu, Jiaqi; Wu, Xiao-Lin; Bauck, Stewart; Lee, Jungjae; Morota, Gota; Kachman, Stephen D; Spangler, Matthew L

2018-04-01

SNP chips are commonly used for genotyping animals in genomic selection but strategies for selecting low-density (LD) SNPs for imputation-mediated genomic selection have not been addressed adequately. The main purpose of the present study was to compare the performance of eight LD (6K) SNP panels, each selected by a different strategy exploiting a combination of three major factors: evenly-spaced SNPs, increased minor allele frequencies, and SNP-trait associations either for single traits independently or for all the three traits jointly. The imputation accuracies from 6K to 80K SNP genotypes were between 96.2 and 98.2%. Genomic prediction accuracies obtained using imputed 80K genotypes were between 0.817 and 0.821 for daughter pregnancy rate, between 0.838 and 0.844 for fat yield, and between 0.850 and 0.863 for milk yield. The two SNP panels optimized on the three major factors had the highest genomic prediction accuracy (0.821-0.863), and these accuracies were very close to those obtained using observed 80K genotypes (0.825-0.868). Further exploration of the underlying relationships showed that genomic prediction accuracies did not respond linearly to imputation accuracies, but were significantly affected by genotype (imputation) errors of SNPs in association with the traits to be predicted. SNPs optimal for map coverage and MAF were favorable for obtaining accurate imputation of genotypes whereas trait-associated SNPs improved genomic prediction accuracies. Thus, optimal LD SNP panels were the ones that combined both strengths. The present results have practical implications on the design of LD SNP chips for imputation-enabled genomic prediction.

MOV reliability evaluation and periodic verification scheduling

Energy Technology Data Exchange (ETDEWEB)

Bunte, B.D.

1996-12-01

The purpose of this paper is to establish a periodic verification testing schedule based on the expected long term reliability of gate or globe motor operated valves (MOVs). The methodology in this position paper determines the nominal (best estimate) design margin for any MOV based on the best available information pertaining to the MOVs design requirements, design parameters, existing hardware design, and present setup. The uncertainty in this margin is then determined using statistical means. By comparing the nominal margin to the uncertainty, the reliability of the MOV is estimated. The methodology is appropriate for evaluating the reliability of MOVs in the GL 89-10 program. It may be used following periodic testing to evaluate and trend MOV performance and reliability. It may also be used to evaluate the impact of proposed modifications and maintenance activities such as packing adjustments. In addition, it may be used to assess the impact of new information of a generic nature which impacts safety related MOVs.

MOV reliability evaluation and periodic verification scheduling

International Nuclear Information System (INIS)

Bunte, B.D.

1996-01-01

The purpose of this paper is to establish a periodic verification testing schedule based on the expected long term reliability of gate or globe motor operated valves (MOVs). The methodology in this position paper determines the nominal (best estimate) design margin for any MOV based on the best available information pertaining to the MOVs design requirements, design parameters, existing hardware design, and present setup. The uncertainty in this margin is then determined using statistical means. By comparing the nominal margin to the uncertainty, the reliability of the MOV is estimated. The methodology is appropriate for evaluating the reliability of MOVs in the GL 89-10 program. It may be used following periodic testing to evaluate and trend MOV performance and reliability. It may also be used to evaluate the impact of proposed modifications and maintenance activities such as packing adjustments. In addition, it may be used to assess the impact of new information of a generic nature which impacts safety related MOVs

Design of a bovine low-density SNP array optimized for imputation.

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Didier Boichard

Full Text Available The Illumina BovineLD BeadChip was designed to support imputation to higher density genotypes in dairy and beef breeds by including single-nucleotide polymorphisms (SNPs that had a high minor allele frequency as well as uniform spacing across the genome except at the ends of the chromosome where densities were increased. The chip also includes SNPs on the Y chromosome and mitochondrial DNA loci that are useful for determining subspecies classification and certain paternal and maternal breed lineages. The total number of SNPs was 6,909. Accuracy of imputation to Illumina BovineSNP50 genotypes using the BovineLD chip was over 97% for most dairy and beef populations. The BovineLD imputations were about 3 percentage points more accurate than those from the Illumina GoldenGate Bovine3K BeadChip across multiple populations. The improvement was greatest when neither parent was genotyped. The minor allele frequencies were similar across taurine beef and dairy breeds as was the proportion of SNPs that were polymorphic. The new BovineLD chip should facilitate low-cost genomic selection in taurine beef and dairy cattle.

iVAR: a program for imputing missing data in multivariate time series using vector autoregressive models.

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Liu, Siwei; Molenaar, Peter C M

2014-12-01

This article introduces iVAR, an R program for imputing missing data in multivariate time series on the basis of vector autoregressive (VAR) models. We conducted a simulation study to compare iVAR with three methods for handling missing data: listwise deletion, imputation with sample means and variances, and multiple imputation ignoring time dependency. The results showed that iVAR produces better estimates for the cross-lagged coefficients than do the other three methods. We demonstrate the use of iVAR with an empirical example of time series electrodermal activity data and discuss the advantages and limitations of the program.

Use of Multiple Imputation Method to Improve Estimation of Missing Baseline Serum Creatinine in Acute Kidney Injury Research

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Peterson, Josh F.; Eden, Svetlana K.; Moons, Karel G.; Ikizler, T. Alp; Matheny, Michael E.

2013-01-01

Summary Background and objectives Baseline creatinine (BCr) is frequently missing in AKI studies. Common surrogate estimates can misclassify AKI and adversely affect the study of related outcomes. This study examined whether multiple imputation improved accuracy of estimating missing BCr beyond current recommendations to apply assumed estimated GFR (eGFR) of 75 ml/min per 1.73 m2 (eGFR 75). Design, setting, participants, & measurements From 41,114 unique adult admissions (13,003 with and 28,111 without BCr data) at Vanderbilt University Hospital between 2006 and 2008, a propensity score model was developed to predict likelihood of missing BCr. Propensity scoring identified 6502 patients with highest likelihood of missing BCr among 13,003 patients with known BCr to simulate a “missing” data scenario while preserving actual reference BCr. Within this cohort (n=6502), the ability of various multiple-imputation approaches to estimate BCr and classify AKI were compared with that of eGFR 75. Results All multiple-imputation methods except the basic one more closely approximated actual BCr than did eGFR 75. Total AKI misclassification was lower with multiple imputation (full multiple imputation + serum creatinine) (9.0%) than with eGFR 75 (12.3%; Pcreatinine) (15.3%) versus eGFR 75 (40.5%; P<0.001). Multiple imputation improved specificity and positive predictive value for detecting AKI at the expense of modestly decreasing sensitivity relative to eGFR 75. Conclusions Multiple imputation can improve accuracy in estimating missing BCr and reduce misclassification of AKI beyond currently proposed methods. PMID:23037980

Multiple Imputation of Predictor Variables Using Generalized Additive Models

NARCIS (Netherlands)

de Jong, Roel; van Buuren, Stef; Spiess, Martin

2016-01-01

The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

Mapping wildland fuels and forest structure for land management: a comparison of nearest neighbor imputation and other methods

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Kenneth B. Pierce; Janet L. Ohmann; Michael C. Wimberly; Matthew J. Gregory; Jeremy S. Fried

2009-01-01

Land managers need consistent information about the geographic distribution of wildland fuels and forest structure over large areas to evaluate fire risk and plan fuel treatments. We compared spatial predictions for 12 fuel and forest structure variables across three regions in the western United States using gradient nearest neighbor (GNN) imputation, linear models (...

The use of multiple imputation for the accurate measurements of individual feed intake by electronic feeders.

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Jiao, S; Tiezzi, F; Huang, Y; Gray, K A; Maltecca, C

2016-02-01

Obtaining accurate individual feed intake records is the key first step in achieving genetic progress toward more efficient nutrient utilization in pigs. Feed intake records collected by electronic feeding systems contain errors (erroneous and abnormal values exceeding certain cutoff criteria), which are due to feeder malfunction or animal-feeder interaction. In this study, we examined the use of a novel data-editing strategy involving multiple imputation to minimize the impact of errors and missing values on the quality of feed intake data collected by an electronic feeding system. Accuracy of feed intake data adjustment obtained from the conventional linear mixed model (LMM) approach was compared with 2 alternative implementations of multiple imputation by chained equation, denoted as MI (multiple imputation) and MICE (multiple imputation by chained equation). The 3 methods were compared under 3 scenarios, where 5, 10, and 20% feed intake error rates were simulated. Each of the scenarios was replicated 5 times. Accuracy of the alternative error adjustment was measured as the correlation between the true daily feed intake (DFI; daily feed intake in the testing period) or true ADFI (the mean DFI across testing period) and the adjusted DFI or adjusted ADFI. In the editing process, error cutoff criteria are used to define if a feed intake visit contains errors. To investigate the possibility that the error cutoff criteria may affect any of the 3 methods, the simulation was repeated with 2 alternative error cutoff values. Multiple imputation methods outperformed the LMM approach in all scenarios with mean accuracies of 96.7, 93.5, and 90.2% obtained with MI and 96.8, 94.4, and 90.1% obtained with MICE compared with 91.0, 82.6, and 68.7% using LMM for DFI. Similar results were obtained for ADFI. Furthermore, multiple imputation methods consistently performed better than LMM regardless of the cutoff criteria applied to define errors. In conclusion, multiple imputation

Effects of Different Missing Data Imputation Techniques on the Performance of Undiagnosed Diabetes Risk Prediction Models in a Mixed-Ancestry Population of South Africa.

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Katya L Masconi

Full Text Available Imputation techniques used to handle missing data are based on the principle of replacement. It is widely advocated that multiple imputation is superior to other imputation methods, however studies have suggested that simple methods for filling missing data can be just as accurate as complex methods. The objective of this study was to implement a number of simple and more complex imputation methods, and assess the effect of these techniques on the performance of undiagnosed diabetes risk prediction models during external validation.Data from the Cape Town Bellville-South cohort served as the basis for this study. Imputation methods and models were identified via recent systematic reviews. Models' discrimination was assessed and compared using C-statistic and non-parametric methods, before and after recalibration through simple intercept adjustment.The study sample consisted of 1256 individuals, of whom 173 were excluded due to previously diagnosed diabetes. Of the final 1083 individuals, 329 (30.4% had missing data. Family history had the highest proportion of missing data (25%. Imputation of the outcome, undiagnosed diabetes, was highest in stochastic regression imputation (163 individuals. Overall, deletion resulted in the lowest model performances while simple imputation yielded the highest C-statistic for the Cambridge Diabetes Risk model, Kuwaiti Risk model, Omani Diabetes Risk model and Rotterdam Predictive model. Multiple imputation only yielded the highest C-statistic for the Rotterdam Predictive model, which were matched by simpler imputation methods.Deletion was confirmed as a poor technique for handling missing data. However, despite the emphasized disadvantages of simpler imputation methods, this study showed that implementing these methods results in similar predictive utility for undiagnosed diabetes when compared to multiple imputation.

Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation.

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Silva, Carlos Alberto; Klauberg, Carine; Hudak, Andrew T; Vierling, Lee A; Liesenberg, Veraldo; Bernett, Luiz G; Scheraiber, Clewerson F; Schoeninger, Emerson R

2018-01-01

Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM) and tree density (TD) of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR) data and the non- k-nearest neighbor (k-NN) imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more effective for retrieving height than tree density. The model coefficients of determination (adj.R2) and a root mean squared difference (RMSD) for HD, HM and TD were 0.90, 0.94, 0.38m and 6.99, 5.70, 12.92%, respectively. Our results show that LiDAR and k-NN imputation can be used to predict stand heights with high accuracy in Pinus taeda. However, furthers studies need to be realized to improve the accuracy prediction of TD and to evaluate and compare the cost of acquisition and processing of LiDAR data against the conventional inventory procedures.

A reliability evaluation method for NPP safety DCS application software

International Nuclear Information System (INIS)

Li Yunjian; Zhang Lei; Liu Yuan

2014-01-01

In the field of nuclear power plant (NPP) digital i and c application, reliability evaluation for safety DCS application software is a key obstacle to be removed. In order to quantitatively evaluate reliability of NPP safety DCS application software, this paper propose a reliability evaluating method based on software development life cycle every stage's v and v defects density characteristics, by which the operating reliability level of the software can be predicted before its delivery, and helps to improve the reliability of NPP safety important software. (authors)

Analyzing the changing gender wage gap based on multiply imputed right censored wages

OpenAIRE

Gartner, Hermann; Rässler, Susanne

2005-01-01

"In order to analyze the gender wage gap with the German IAB-employment register we have to solve the problem of censored wages at the upper limit of the social security system. We treat this problem as a missing data problem. We regard the missingness mechanism as not missing at random (NMAR, according to Little and Rubin, 1987, 2002) as well as missing by design. The censored wages are multiply imputed by draws of a random variable from a truncated distribution. The multiple imputation is b...

Traffic speed data imputation method based on tensor completion.

Science.gov (United States)

Ran, Bin; Tan, Huachun; Feng, Jianshuai; Liu, Ying; Wang, Wuhong

2015-01-01

Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

Multiple imputation to account for missing data in a survey: estimating the prevalence of osteoporosis.

Science.gov (United States)

Kmetic, Andrew; Joseph, Lawrence; Berger, Claudie; Tenenhouse, Alan

2002-07-01

Nonresponse bias is a concern in any epidemiologic survey in which a subset of selected individuals declines to participate. We reviewed multiple imputation, a widely applicable and easy to implement Bayesian methodology to adjust for nonresponse bias. To illustrate the method, we used data from the Canadian Multicentre Osteoporosis Study, a large cohort study of 9423 randomly selected Canadians, designed in part to estimate the prevalence of osteoporosis. Although subjects were randomly selected, only 42% of individuals who were contacted agreed to participate fully in the study. The study design included a brief questionnaire for those invitees who declined further participation in order to collect information on the major risk factors for osteoporosis. These risk factors (which included age, sex, previous fractures, family history of osteoporosis, and current smoking status) were then used to estimate the missing osteoporosis status for nonparticipants using multiple imputation. Both ignorable and nonignorable imputation models are considered. Our results suggest that selection bias in the study is of concern, but only slightly, in very elderly (age 80+ years), both women and men. Epidemiologists should consider using multiple imputation more often than is current practice.

Imputation of microsatellite alleles from dense SNP genotypes for parental verification

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Matthew eMcclure

2012-08-01

Full Text Available Microsatellite (MS markers have recently been used for parental verification and are still the international standard despite higher cost, error rate, and turnaround time compared with Single Nucleotide Polymorphisms (SNP-based assays. Despite domestic and international interest from producers and research communities, no viable means currently exist to verify parentage for an individual unless all familial connections were analyzed using the same DNA marker type (MS or SNP. A simple and cost-effective method was devised to impute MS alleles from SNP haplotypes within breeds. For some MS, imputation results may allow inference across breeds. A total of 347 dairy cattle representing 4 dairy breeds (Brown Swiss, Guernsey, Holstein, and Jersey were used to generate reference haplotypes. This approach has been verified (>98% accurate for imputing the International Society of Animal Genetics (ISAG recommended panel of 12 MS for cattle parentage verification across a validation set of 1,307 dairy animals.. Implementation of this method will allow producers and breed associations to transition to SNP-based parentage verification utilizing MS genotypes from historical data on parents where SNP genotypes are missing. This approach may be applicable to additional cattle breeds and other species that wish to migrate from MS- to SNP- based parental verification.

ParaHaplo 3.0: A program package for imputation and a haplotype-based whole-genome association study using hybrid parallel computing

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Kamatani Naoyuki

2011-05-01

Full Text Available Abstract Background Use of missing genotype imputations and haplotype reconstructions are valuable in genome-wide association studies (GWASs. By modeling the patterns of linkage disequilibrium in a reference panel, genotypes not directly measured in the study samples can be imputed and used for GWASs. Since millions of single nucleotide polymorphisms need to be imputed in a GWAS, faster methods for genotype imputation and haplotype reconstruction are required. Results We developed a program package for parallel computation of genotype imputation and haplotype reconstruction. Our program package, ParaHaplo 3.0, is intended for use in workstation clusters using the Intel Message Passing Interface. We compared the performance of ParaHaplo 3.0 on the Japanese in Tokyo, Japan and Han Chinese in Beijing, and Chinese in the HapMap dataset. A parallel version of ParaHaplo 3.0 can conduct genotype imputation 20 times faster than a non-parallel version of ParaHaplo. Conclusions ParaHaplo 3.0 is an invaluable tool for conducting haplotype-based GWASs. The need for faster genotype imputation and haplotype reconstruction using parallel computing will become increasingly important as the data sizes of such projects continue to increase. ParaHaplo executable binaries and program sources are available at http://en.sourceforge.jp/projects/parallelgwas/releases/.

Combining Fourier and lagged k-nearest neighbor imputation for biomedical time series data.

Science.gov (United States)

Rahman, Shah Atiqur; Huang, Yuxiao; Claassen, Jan; Heintzman, Nathaniel; Kleinberg, Samantha

2015-12-01

Most clinical and biomedical data contain missing values. A patient's record may be split across multiple institutions, devices may fail, and sensors may not be worn at all times. While these missing values are often ignored, this can lead to bias and error when the data are mined. Further, the data are not simply missing at random. Instead the measurement of a variable such as blood glucose may depend on its prior values as well as that of other variables. These dependencies exist across time as well, but current methods have yet to incorporate these temporal relationships as well as multiple types of missingness. To address this, we propose an imputation method (FLk-NN) that incorporates time lagged correlations both within and across variables by combining two imputation methods, based on an extension to k-NN and the Fourier transform. This enables imputation of missing values even when all data at a time point is missing and when there are different types of missingness both within and across variables. In comparison to other approaches on three biological datasets (simulated and actual Type 1 diabetes datasets, and multi-modality neurological ICU monitoring) the proposed method has the highest imputation accuracy. This was true for up to half the data being missing and when consecutive missing values are a significant fraction of the overall time series length. Copyright © 2015 Elsevier Inc. All rights reserved.

Human Reliability Data Bank: evaluation results

International Nuclear Information System (INIS)

Comer, M.K.; Donovan, M.D.; Gaddy, C.D.

1985-01-01

The US Nuclear Regulatory Commission (NRC), Sandia National Laboratories (SNL), and General Physics Corporation are conducting a research program to determine the practicality, acceptability, and usefulness of a Human Reliability Data Bank for nuclear power industry probabilistic risk assessment (PRA). As part of this program, a survey was conducted of existing human reliability data banks from other industries, and a detailed concept of a Data Bank for the nuclear industry was developed. Subsequently, a detailed specification for implementing the Data Bank was developed. An evaluation of this specification was conducted and is described in this report. The evaluation tested data treatment, storage, and retrieval using the Data Bank structure, as modified from NUREG/CR-2744, and detailed procedures for data processing and retrieval, developed prior to this evaluation and documented in the test specification. The evaluation consisted of an Operability Demonstration and Evaluation of the data processing procedures, a Data Retrieval Demonstration and Evaluation, a Retrospective Analysis that included a survey of organizations currently operating data banks for the nuclear power industry, and an Internal Analysis of the current Data Bank System

Simple nuclear norm based algorithms for imputing missing data and forecasting in time series

OpenAIRE

Butcher, Holly Louise; Gillard, Jonathan William

2017-01-01

There has been much recent progress on the use of the nuclear norm for the so-called matrix completion problem (the problem of imputing missing values of a matrix). In this paper we investigate the use of the nuclear norm for modelling time series, with particular attention to imputing missing data and forecasting. We introduce a simple alternating projections type algorithm based on the nuclear norm for these tasks, and consider a number of practical examples.

Randomly and Non-Randomly Missing Renal Function Data in the Strong Heart Study: A Comparison of Imputation Methods.

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Nawar Shara

Full Text Available Kidney and cardiovascular disease are widespread among populations with high prevalence of diabetes, such as American Indians participating in the Strong Heart Study (SHS. Studying these conditions simultaneously in longitudinal studies is challenging, because the morbidity and mortality associated with these diseases result in missing data, and these data are likely not missing at random. When such data are merely excluded, study findings may be compromised. In this article, a subset of 2264 participants with complete renal function data from Strong Heart Exams 1 (1989-1991, 2 (1993-1995, and 3 (1998-1999 was used to examine the performance of five methods used to impute missing data: listwise deletion, mean of serial measures, adjacent value, multiple imputation, and pattern-mixture. Three missing at random models and one non-missing at random model were used to compare the performance of the imputation techniques on randomly and non-randomly missing data. The pattern-mixture method was found to perform best for imputing renal function data that were not missing at random. Determining whether data are missing at random or not can help in choosing the imputation method that will provide the most accurate results.

Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data.

Science.gov (United States)

Sehgal, Muhammad Shoaib B; Gondal, Iqbal; Dooley, Laurence S

2005-05-15

Microarray data are used in a range of application areas in biology, although often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible before using these algorithms. While many imputation algorithms have been proposed, more robust techniques need to be developed so that further analysis of biological data can be accurately undertaken. In this paper, an innovative missing value imputation algorithm called collateral missing value estimation (CMVE) is presented which uses multiple covariance-based imputation matrices for the final prediction of missing values. The matrices are computed and optimized using least square regression and linear programming methods. The new CMVE algorithm has been compared with existing estimation techniques including Bayesian principal component analysis imputation (BPCA), least square impute (LSImpute) and K-nearest neighbour (KNN). All these methods were rigorously tested to estimate missing values in three separate non-time series (ovarian cancer based) and one time series (yeast sporulation) dataset. Each method was quantitatively analyzed using the normalized root mean square (NRMS) error measure, covering a wide range of randomly introduced missing value probabilities from 0.01 to 0.2. Experiments were also undertaken on the yeast dataset, which comprised 1.7% actual missing values, to test the hypothesis that CMVE performed better not only for randomly occurring but also for a real distribution of missing values. The results confirmed that CMVE consistently demonstrated superior and robust estimation capability of missing values compared with other methods for both series types of data, for the same order of computational complexity. A concise theoretical framework has also been formulated to validate the improved performance of the CMVE

A spatial haplotype copying model with applications to genotype imputation.

Science.gov (United States)

Yang, Wen-Yun; Hormozdiari, Farhad; Eskin, Eleazar; Pasaniuc, Bogdan

2015-05-01

Ever since its introduction, the haplotype copy model has proven to be one of the most successful approaches for modeling genetic variation in human populations, with applications ranging from ancestry inference to genotype phasing and imputation. Motivated by coalescent theory, this approach assumes that any chromosome (haplotype) can be modeled as a mosaic of segments copied from a set of chromosomes sampled from the same population. At the core of the model is the assumption that any chromosome from the sample is equally likely to contribute a priori to the copying process. Motivated by recent works that model genetic variation in a geographic continuum, we propose a new spatial-aware haplotype copy model that jointly models geography and the haplotype copying process. We extend hidden Markov models of haplotype diversity such that at any given location, haplotypes that are closest in the genetic-geographic continuum map are a priori more likely to contribute to the copying process than distant ones. Through simulations starting from the 1000 Genomes data, we show that our model achieves superior accuracy in genotype imputation over the standard spatial-unaware haplotype copy model. In addition, we show the utility of our model in selecting a small personalized reference panel for imputation that leads to both improved accuracy as well as to a lower computational runtime than the standard approach. Finally, we show our proposed model can be used to localize individuals on the genetic-geographical map on the basis of their genotype data.

Data Editing and Imputation in Business Surveys Using “R”

Directory of Open Access Journals (Sweden)

Elena Romascanu

2014-06-01

Full Text Available Purpose – Missing data are a recurring problem that can cause bias or lead to inefficient analyses. The objective of this paper is a direct comparison between the two statistical software features R and SPSS, in order to take full advantage of the existing automated methods for data editing process and imputation in business surveys (with a proper design of consistency rules as a partial alternative to the manual editing of data. Approach – The comparison of different methods on editing surveys data, in R with the ‘editrules’ and ‘survey’ packages because inside those, exist commonly used transformations in official statistics, as visualization of missing values pattern using ‘Amelia’ and ‘VIM’ packages, imputation approaches for longitudinal data using ‘VIMGUI’ and a comparison of another statistical software performance on the same features, such as SPSS. Findings – Data on business statistics received by NIS’s (National Institute of Statistics are not ready to be used for direct analysis due to in-record inconsistencies, errors and missing values from the collected data sets. The appropriate automatic methods from R packages, offers the ability to set the erroneous fields in edit-violating records, to verify the results after the imputation of missing values providing for users a flexible, less time consuming approach and easy to perform automation in R than in SPSS Macros syntax situations, when macros are very handy.

Reliability evaluation of deregulated electric power systems for planning applications

International Nuclear Information System (INIS)

Ehsani, A.; Ranjbar, A.M.; Jafari, A.; Fotuhi-Firuzabad, M.

2008-01-01

In a deregulated electric power utility industry in which a competitive electricity market can influence system reliability, market risks cannot be ignored. This paper (1) proposes an analytical probabilistic model for reliability evaluation of competitive electricity markets and (2) develops a methodology for incorporating the market reliability problem into HLII reliability studies. A Markov state space diagram is employed to evaluate the market reliability. Since the market is a continuously operated system, the concept of absorbing states is applied to it in order to evaluate the reliability. The market states are identified by using market performance indices and the transition rates are calculated by using historical data. The key point in the proposed method is the concept that the reliability level of a restructured electric power system can be calculated using the availability of the composite power system (HLII) and the reliability of the electricity market. Two case studies are carried out over Roy Billinton Test System (RBTS) to illustrate interesting features of the proposed methodology

Combining item response theory with multiple imputation to equate health assessment questionnaires.

Science.gov (United States)

Gu, Chenyang; Gutman, Roee

2017-09-01

The assessment of patients' functional status across the continuum of care requires a common patient assessment tool. However, assessment tools that are used in various health care settings differ and cannot be easily contrasted. For example, the Functional Independence Measure (FIM) is used to evaluate the functional status of patients who stay in inpatient rehabilitation facilities, the Minimum Data Set (MDS) is collected for all patients who stay in skilled nursing facilities, and the Outcome and Assessment Information Set (OASIS) is collected if they choose home health care provided by home health agencies. All three instruments or questionnaires include functional status items, but the specific items, rating scales, and instructions for scoring different activities vary between the different settings. We consider equating different health assessment questionnaires as a missing data problem, and propose a variant of predictive mean matching method that relies on Item Response Theory (IRT) models to impute unmeasured item responses. Using real data sets, we simulated missing measurements and compared our proposed approach to existing methods for missing data imputation. We show that, for all of the estimands considered, and in most of the experimental conditions that were examined, the proposed approach provides valid inferences, and generally has better coverages, relatively smaller biases, and shorter interval estimates. The proposed method is further illustrated using a real data set. © 2016, The International Biometric Society.

Reliability Evaluation for Clustered WSNs under Malware Propagation

Science.gov (United States)

Shen, Shigen; Huang, Longjun; Liu, Jianhua; Champion, Adam C.; Yu, Shui; Cao, Qiying

2016-01-01

We consider a clustered wireless sensor network (WSN) under epidemic-malware propagation conditions and solve the problem of how to evaluate its reliability so as to ensure efficient, continuous, and dependable transmission of sensed data from sensor nodes to the sink. Facing the contradiction between malware intention and continuous-time Markov chain (CTMC) randomness, we introduce a strategic game that can predict malware infection in order to model a successful infection as a CTMC state transition. Next, we devise a novel measure to compute the Mean Time to Failure (MTTF) of a sensor node, which represents the reliability of a sensor node continuously performing tasks such as sensing, transmitting, and fusing data. Since clustered WSNs can be regarded as parallel-serial-parallel systems, the reliability of a clustered WSN can be evaluated via classical reliability theory. Numerical results show the influence of parameters such as the true positive rate and the false positive rate on a sensor node’s MTTF. Furthermore, we validate the method of reliability evaluation for a clustered WSN according to the number of sensor nodes in a cluster, the number of clusters in a route, and the number of routes in the WSN. PMID:27294934

Reliability Evaluation for Clustered WSNs under Malware Propagation.

Science.gov (United States)

Shen, Shigen; Huang, Longjun; Liu, Jianhua; Champion, Adam C; Yu, Shui; Cao, Qiying

2016-06-10

We consider a clustered wireless sensor network (WSN) under epidemic-malware propagation conditions and solve the problem of how to evaluate its reliability so as to ensure efficient, continuous, and dependable transmission of sensed data from sensor nodes to the sink. Facing the contradiction between malware intention and continuous-time Markov chain (CTMC) randomness, we introduce a strategic game that can predict malware infection in order to model a successful infection as a CTMC state transition. Next, we devise a novel measure to compute the Mean Time to Failure (MTTF) of a sensor node, which represents the reliability of a sensor node continuously performing tasks such as sensing, transmitting, and fusing data. Since clustered WSNs can be regarded as parallel-serial-parallel systems, the reliability of a clustered WSN can be evaluated via classical reliability theory. Numerical results show the influence of parameters such as the true positive rate and the false positive rate on a sensor node's MTTF. Furthermore, we validate the method of reliability evaluation for a clustered WSN according to the number of sensor nodes in a cluster, the number of clusters in a route, and the number of routes in the WSN.

Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation

Directory of Open Access Journals (Sweden)

CARLOS ALBERTO SILVA

Full Text Available ABSTRACT Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM and tree density (TD of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR data and the non- k-nearest neighbor (k-NN imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more effective for retrieving height than tree density. The model coefficients of determination (adj.R2 and a root mean squared difference (RMSD for HD, HM and TD were 0.90, 0.94, 0.38m and 6.99, 5.70, 12.92%, respectively. Our results show that LiDAR and k-NN imputation can be used to predict stand heights with high accuracy in Pinus taeda. However, furthers studies need to be realized to improve the accuracy prediction of TD and to evaluate and compare the cost of acquisition and processing of LiDAR data against the conventional inventory procedures.

Trend in BMI z-score among Private Schools’ Students in Delhi using Multiple Imputation for Growth Curve Model

Directory of Open Access Journals (Sweden)

Vinay K Gupta

2016-06-01

Full Text Available Objective: The aim of the study is to assess the trend in mean BMI z-score among private schools’ students from their anthropometric records when there were missing values in the outcome. Methodology: The anthropometric measurements of student from class 1 to 12 were taken from the records of two private schools in Delhi, India from 2005 to 2010. These records comprise of an unbalanced longitudinal data that is not all the students had measurements recorded at each year. The trend in mean BMI z-score was estimated through growth curve model. Prior to that, missing values of BMI z-score were imputed through multiple imputation using the same model. A complete case analysis was also performed after excluding missing values to compare the results with those obtained from analysis of multiply imputed data. Results: The mean BMI z-score among school student significantly decreased over time in imputed data (β= -0.2030, se=0.0889, p=0.0232 after adjusting age, gender, class and school. Complete case analysis also shows a decrease in mean BMI z-score though it was not statistically significant (β= -0.2861, se=0.0987, p=0.065. Conclusions: The estimates obtained from multiple imputation analysis were better than those of complete data after excluding missing values in terms of lower standard errors. We showed that anthropometric measurements from schools records can be used to monitor the weight status of children and adolescents and multiple imputation using growth curve model can be useful while analyzing such data

Traffic Speed Data Imputation Method Based on Tensor Completion

Directory of Open Access Journals (Sweden)

Bin Ran

2015-01-01

Full Text Available Traffic speed data plays a key role in Intelligent Transportation Systems (ITS; however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS. In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC, an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

Automation of reliability evaluation procedures through CARE - The computer-aided reliability estimation program.

Science.gov (United States)

Mathur, F. P.

1972-01-01

Description of an on-line interactive computer program called CARE (Computer-Aided Reliability Estimation) which can model self-repair and fault-tolerant organizations and perform certain other functions. Essentially CARE consists of a repository of mathematical equations defining the various basic redundancy schemes. These equations, under program control, are then interrelated to generate the desired mathematical model to fit the architecture of the system under evaluation. The mathematical model is then supplied with ground instances of its variables and is then evaluated to generate values for the reliability-theoretic functions applied to the model.

BRITS: Bidirectional Recurrent Imputation for Time Series

OpenAIRE

Cao, Wei; Wang, Dong; Li, Jian; Zhou, Hao; Li, Lei; Li, Yitan

2018-01-01

Time series are widely used as signals in many classification/regression tasks. It is ubiquitous that time series contains many missing values. Given multiple correlated time series data, how to fill in missing values and to predict their class labels? Existing imputation methods often impose strong assumptions of the underlying data generating process, such as linear dynamics in the state space. In this paper, we propose BRITS, a novel method based on recurrent neural networks for missing va...

Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis

NARCIS (Netherlands)

Eekhout, I.; Wiel, M.A. van de; Heymans, M.W.

2017-01-01

Background. Multiple imputation is a recommended method to handle missing data. For significance testing after multiple imputation, Rubin’s Rules (RR) are easily applied to pool parameter estimates. In a logistic regression model, to consider whether a categorical covariate with more than two levels

Fast Monte Carlo reliability evaluation using support vector machine

International Nuclear Information System (INIS)

Rocco, Claudio M.; Moreno, Jose Ali

2002-01-01

This paper deals with the feasibility of using support vector machine (SVM) to build empirical models for use in reliability evaluation. The approach takes advantage of the speed of SVM in the numerous model calculations typically required to perform a Monte Carlo reliability evaluation. The main idea is to develop an estimation algorithm, by training a model on a restricted data set, and replace system performance evaluation by a simpler calculation, which provides reasonably accurate model outputs. The proposed approach is illustrated by several examples. Excellent system reliability results are obtained by training a SVM with a small amount of information

An evaluation of the multi-state node networks reliability using the traditional binary-state networks reliability algorithm

International Nuclear Information System (INIS)

Yeh, W.-C.

2003-01-01

A system where the components and system itself are allowed to have a number of performance levels is called the Multi-state system (MSS). A multi-state node network (MNN) is a generalization of the MSS without satisfying the flow conservation law. Evaluating the MNN reliability arises at the design and exploitation stage of many types of technical systems. Up to now, the known existing methods can only evaluate a special MNN reliability called the multi-state node acyclic network (MNAN) in which no cyclic is allowed. However, no method exists for evaluating the general MNN reliability. The main purpose of this article is to show first that each MNN reliability can be solved using any the traditional binary-state networks (TBSN) reliability algorithm with a special code for the state probability. A simple heuristic SDP algorithm based on minimal cuts (MC) for estimating the MNN reliability is presented as an example to show how the TBSN reliability algorithm is revised to solve the MNN reliability problem. To the author's knowledge, this study is the first to discuss the relationships between MNN and TBSN and also the first to present methods to solve the exact and approximated MNN reliability. One example is illustrated to show how the exact MNN reliability is obtained using the proposed algorithm

A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods.

Science.gov (United States)

Ratcliffe, B; El-Dien, O G; Klápště, J; Porth, I; Chen, C; Jaquish, B; El-Kassaby, Y A

2015-12-01

Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3-40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31-0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04-0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesCπ (BCπ) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated.

Reliability evaluation of a natural circulation system

International Nuclear Information System (INIS)

Jafari, Jalil; D'Auria, Francesco; Kazeminejad, Hossein; Davilu, Hadi

2003-01-01

This paper discusses a reliability study performed with reference to a passive thermohydraulic natural circulation (NC) system, named TTL-1. A methodology based on probabilistic techniques has been applied with the main purpose to optimize the system design. The obtained results have been adopted to estimate the thermal-hydraulic reliability (TH-R) of the same system. A total of 29 relevant parameters (including nominal values and plausible ranges of variations) affecting the design and the NC performance of the TTL-1 loop are identified and a probability of occurrence is assigned for each value based on expert judgment. Following procedures established for the uncertainty evaluation of thermal-hydraulic system codes results, 137 system configurations have been selected and each configuration has been analyzed via the Relap5 best-estimate code. The reference system configuration and the failure criteria derived from the 'mission' of the passive system are adopted for the evaluation of the system TH-R. Four different definitions of a less-than-unity 'reliability-values' (where unity represents the maximum achievable reliability) are proposed for the performance of the selected passive system. This is normally considered fully reliable, i.e. reliability-value equal one, in typical Probabilistic Safety Assessment (PSA) applications in nuclear reactor safety. The two 'point' TH-R values for the considered NC system were found equal to 0.70 and 0.85, i.e. values comparable with the reliability of a pump installed in an 'equivalent' forced circulation (active) system having the same 'mission'. The design optimization study was completed by a regression analysis addressing the output of the 137 calculations: heat losses, undetected leakage, loop length, riser diameter, and equivalent diameter of the test section have been found as the most important parameters bringing to the optimal system design and affecting the TH-R. As added values for this work, the comparison has

Reliability Evaluation for Clustered WSNs under Malware Propagation

Directory of Open Access Journals (Sweden)

Shigen Shen

2016-06-01

Full Text Available We consider a clustered wireless sensor network (WSN under epidemic-malware propagation conditions and solve the problem of how to evaluate its reliability so as to ensure efficient, continuous, and dependable transmission of sensed data from sensor nodes to the sink. Facing the contradiction between malware intention and continuous-time Markov chain (CTMC randomness, we introduce a strategic game that can predict malware infection in order to model a successful infection as a CTMC state transition. Next, we devise a novel measure to compute the Mean Time to Failure (MTTF of a sensor node, which represents the reliability of a sensor node continuously performing tasks such as sensing, transmitting, and fusing data. Since clustered WSNs can be regarded as parallel-serial-parallel systems, the reliability of a clustered WSN can be evaluated via classical reliability theory. Numerical results show the influence of parameters such as the true positive rate and the false positive rate on a sensor node’s MTTF. Furthermore, we validate the method of reliability evaluation for a clustered WSN according to the number of sensor nodes in a cluster, the number of clusters in a route, and the number of routes in the WSN.

RIDDLE: Race and ethnicity Imputation from Disease history with Deep LEarning

KAUST Repository

Kim, Ji-Sung; Gao, Xin; Rzhetsky, Andrey

2018-01-01

are predictive of race and ethnicity. We used these characterizations of informative features to perform a systematic comparison of differential disease patterns by race and ethnicity. The fact that clinical histories are informative for imputing race

Imputation by the mean score should be avoided when validating a Patient Reported Outcomes questionnaire by a Rasch model in presence of informative missing data

LENUS (Irish Health Repository)

Hardouin, Jean-Benoit

2011-07-14

Abstract Background Nowadays, more and more clinical scales consisting in responses given by the patients to some items (Patient Reported Outcomes - PRO), are validated with models based on Item Response Theory, and more specifically, with a Rasch model. In the validation sample, presence of missing data is frequent. The aim of this paper is to compare sixteen methods for handling the missing data (mainly based on simple imputation) in the context of psychometric validation of PRO by a Rasch model. The main indexes used for validation by a Rasch model are compared. Methods A simulation study was performed allowing to consider several cases, notably the possibility for the missing values to be informative or not and the rate of missing data. Results Several imputations methods produce bias on psychometrical indexes (generally, the imputation methods artificially improve the psychometric qualities of the scale). In particular, this is the case with the method based on the Personal Mean Score (PMS) which is the most commonly used imputation method in practice. Conclusions Several imputation methods should be avoided, in particular PMS imputation. From a general point of view, it is important to use an imputation method that considers both the ability of the patient (measured for example by his\\/her score), and the difficulty of the item (measured for example by its rate of favourable responses). Another recommendation is to always consider the addition of a random process in the imputation method, because such a process allows reducing the bias. Last, the analysis realized without imputation of the missing data (available case analyses) is an interesting alternative to the simple imputation in this context.

Evaluation of mobile ad hoc network reliability using propagation-based link reliability model

International Nuclear Information System (INIS)

Padmavathy, N.; Chaturvedi, Sanjay K.

2013-01-01

A wireless mobile ad hoc network (MANET) is a collection of solely independent nodes (that can move randomly around the area of deployment) making the topology highly dynamic; nodes communicate with each other by forming a single hop/multi-hop network and maintain connectivity in decentralized manner. MANET is modelled using geometric random graphs rather than random graphs because the link existence in MANET is a function of the geometric distance between the nodes and the transmission range of the nodes. Among many factors that contribute to the MANET reliability, the reliability of these networks also depends on the robustness of the link between the mobile nodes of the network. Recently, the reliability of such networks has been evaluated for imperfect nodes (transceivers) with binary model of communication links based on the transmission range of the mobile nodes and the distance between them. However, in reality, the probability of successful communication decreases as the signal strength deteriorates due to noise, fading or interference effects even up to the nodes' transmission range. Hence, in this paper, using a propagation-based link reliability model rather than a binary-model with nodes following a known failure distribution to evaluate the network reliability (2TR m , ATR m and AoTR m ) of MANET through Monte Carlo Simulation is proposed. The method is illustrated with an application and some imperative results are also presented

Are Validity and Reliability "Relevant" in Qualitative Evaluation Research?

Science.gov (United States)

Goodwin, Laura D.; Goodwin, William L.

1984-01-01

The views of prominant qualitative methodologists on the appropriateness of validity and reliability estimation for the measurement strategies employed in qualitative evaluations are summarized. A case is made for the relevance of validity and reliability estimation. Definitions of validity and reliability for qualitative measurement are presented…

Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies.

Science.gov (United States)

Lazar, Cosmin; Gatto, Laurent; Ferro, Myriam; Bruley, Christophe; Burger, Thomas

2016-04-01

Missing values are a genuine issue in label-free quantitative proteomics. Recent works have surveyed the different statistical methods to conduct imputation and have compared them on real or simulated data sets and recommended a list of missing value imputation methods for proteomics application. Although insightful, these comparisons do not account for two important facts: (i) depending on the proteomics data set, the missingness mechanism may be of different natures and (ii) each imputation method is devoted to a specific type of missingness mechanism. As a result, we believe that the question at stake is not to find the most accurate imputation method in general but instead the most appropriate one. We describe a series of comparisons that support our views: For instance, we show that a supposedly "under-performing" method (i.e., giving baseline average results), if applied at the "appropriate" time in the data-processing pipeline (before or after peptide aggregation) on a data set with the "appropriate" nature of missing values, can outperform a blindly applied, supposedly "better-performing" method (i.e., the reference method from the state-of-the-art). This leads us to formulate few practical guidelines regarding the choice and the application of an imputation method in a proteomics context.

Reliability Evaluation of Machine Center Components Based on Cascading Failure Analysis

Science.gov (United States)

Zhang, Ying-Zhi; Liu, Jin-Tong; Shen, Gui-Xiang; Long, Zhe; Sun, Shu-Guang

2017-07-01

In order to rectify the problems that the component reliability model exhibits deviation, and the evaluation result is low due to the overlook of failure propagation in traditional reliability evaluation of machine center components, a new reliability evaluation method based on cascading failure analysis and the failure influenced degree assessment is proposed. A direct graph model of cascading failure among components is established according to cascading failure mechanism analysis and graph theory. The failure influenced degrees of the system components are assessed by the adjacency matrix and its transposition, combined with the Pagerank algorithm. Based on the comprehensive failure probability function and total probability formula, the inherent failure probability function is determined to realize the reliability evaluation of the system components. Finally, the method is applied to a machine center, it shows the following: 1) The reliability evaluation values of the proposed method are at least 2.5% higher than those of the traditional method; 2) The difference between the comprehensive and inherent reliability of the system component presents a positive correlation with the failure influenced degree of the system component, which provides a theoretical basis for reliability allocation of machine center system.

Construction and application of a Korean reference panel for imputing classical alleles and amino acids of human leukocyte antigen genes.

Science.gov (United States)

Kim, Kwangwoo; Bang, So-Young; Lee, Hye-Soon; Bae, Sang-Cheol

2014-01-01

Genetic variations of human leukocyte antigen (HLA) genes within the major histocompatibility complex (MHC) locus are strongly associated with disease susceptibility and prognosis for many diseases, including many autoimmune diseases. In this study, we developed a Korean HLA reference panel for imputing classical alleles and amino acid residues of several HLA genes. An HLA reference panel has potential for use in identifying and fine-mapping disease associations with the MHC locus in East Asian populations, including Koreans. A total of 413 unrelated Korean subjects were analyzed for single nucleotide polymorphisms (SNPs) at the MHC locus and six HLA genes, including HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1. The HLA reference panel was constructed by phasing the 5,858 MHC SNPs, 233 classical HLA alleles, and 1,387 amino acid residue markers from 1,025 amino acid positions as binary variables. The imputation accuracy of the HLA reference panel was assessed by measuring concordance rates between imputed and genotyped alleles of the HLA genes from a subset of the study subjects and East Asian HapMap individuals. Average concordance rates were 95.6% and 91.1% at 2-digit and 4-digit allele resolutions, respectively. The imputation accuracy was minimally affected by SNP density of a test dataset for imputation. In conclusion, the Korean HLA reference panel we developed was highly suitable for imputing HLA alleles and amino acids from MHC SNPs in East Asians, including Koreans.

Construction and application of a Korean reference panel for imputing classical alleles and amino acids of human leukocyte antigen genes.

Directory of Open Access Journals (Sweden)

Kwangwoo Kim

Full Text Available Genetic variations of human leukocyte antigen (HLA genes within the major histocompatibility complex (MHC locus are strongly associated with disease susceptibility and prognosis for many diseases, including many autoimmune diseases. In this study, we developed a Korean HLA reference panel for imputing classical alleles and amino acid residues of several HLA genes. An HLA reference panel has potential for use in identifying and fine-mapping disease associations with the MHC locus in East Asian populations, including Koreans. A total of 413 unrelated Korean subjects were analyzed for single nucleotide polymorphisms (SNPs at the MHC locus and six HLA genes, including HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1. The HLA reference panel was constructed by phasing the 5,858 MHC SNPs, 233 classical HLA alleles, and 1,387 amino acid residue markers from 1,025 amino acid positions as binary variables. The imputation accuracy of the HLA reference panel was assessed by measuring concordance rates between imputed and genotyped alleles of the HLA genes from a subset of the study subjects and East Asian HapMap individuals. Average concordance rates were 95.6% and 91.1% at 2-digit and 4-digit allele resolutions, respectively. The imputation accuracy was minimally affected by SNP density of a test dataset for imputation. In conclusion, the Korean HLA reference panel we developed was highly suitable for imputing HLA alleles and amino acids from MHC SNPs in East Asians, including Koreans.

A Review on VSC-HVDC Reliability Modeling and Evaluation Techniques

Science.gov (United States)

Shen, L.; Tang, Q.; Li, T.; Wang, Y.; Song, F.

2017-05-01

With the fast development of power electronics, voltage-source converter (VSC) HVDC technology presents cost-effective ways for bulk power transmission. An increasing number of VSC-HVDC projects has been installed worldwide. Their reliability affects the profitability of the system and therefore has a major impact on the potential investors. In this paper, an overview of the recent advances in the area of reliability evaluation for VSC-HVDC systems is provided. Taken into account the latest multi-level converter topology, the VSC-HVDC system is categorized into several sub-systems and the reliability data for the key components is discussed based on sources with academic and industrial backgrounds. The development of reliability evaluation methodologies is reviewed and the issues surrounding the different computation approaches are briefly analysed. A general VSC-HVDC reliability evaluation procedure is illustrated in this paper.

DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

OpenAIRE

Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

2017-01-01

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...

Using mi impute chained to fit ANCOVA models in randomized trials with censored dependent and independent variables

DEFF Research Database (Denmark)

Andersen, Andreas; Rieckmann, Andreas

2016-01-01

In this article, we illustrate how to use mi impute chained with intreg to fit an analysis of covariance analysis of censored and nondetectable immunological concentrations measured in a randomized pretest–posttest design.......In this article, we illustrate how to use mi impute chained with intreg to fit an analysis of covariance analysis of censored and nondetectable immunological concentrations measured in a randomized pretest–posttest design....

Reliability evaluation of an impedance-source PV microconverter

DEFF Research Database (Denmark)

Shen, Yanfeng; Liivik, Elizaveta; Blaabjerg, Frede

2018-01-01

The reliability of an impedance-source PV microconverter is evaluated based on the real-field mission profile. As part of a PV microinverter, the dc-dc microconverter is firstly described. Then the electro-thermal and lifetime models are built for the most reliability-critical components, i...

Evaluation and improvement of nondestructive evaluation reliability for inservice inspection of light water reactors

International Nuclear Information System (INIS)

Bates, D.J.; Deffenbaugh, J.D.; Good, M.S.; Heasler, P.G.; Mart, G.A.; Simonen, F.A.; Spanner, J.C.; Taylor, T.T.; Van Fleet, L.G.

1987-01-01

The Evaluation and Improvement of NDE Reliability for Inservice Inspection (ISI) of Light Water Reactors (NDE Reliability) Program at Pacific Northwest Laboratory (PNL) was established to determine the reliability of current ISI techniques and to develop recommendations that will ensure a suitably high inspection reliability. The objectives of this NRC program are to: determine the reliability of ultrasonic ISI performed on commercial light-water reactor (LWR) primary systems, using probabilistic fracture mechanics analysis, determine the impact of NDE unreliability on system safety and determine the level of inspection reliability required to ensure a suitably low failure probability, evaluate the degree of reliability improvement that could be achieved using improved and advanced NDE techniques, based on material properties, service conditions, and NDE uncertainties, recommend revisions to ASME Code, Section XI, and Regulatory Requirements that will ensure suitably low failure probabilities. The scope of this program is limited to ISI of primary systems; the results and recommendations may also be applicable to Class II piping systems

Reliability evaluation of microgrid considering incentive-based demand response

Science.gov (United States)

Huang, Ting-Cheng; Zhang, Yong-Jun

2017-07-01

Incentive-based demand response (IBDR) can guide customers to adjust their behaviour of electricity and curtail load actively. Meanwhile, distributed generation (DG) and energy storage system (ESS) can provide time for the implementation of IBDR. The paper focus on the reliability evaluation of microgrid considering IBDR. Firstly, the mechanism of IBDR and its impact on power supply reliability are analysed. Secondly, the IBDR dispatch model considering customer’s comprehensive assessment and the customer response model are developed. Thirdly, the reliability evaluation method considering IBDR based on Monte Carlo simulation is proposed. Finally, the validity of the above models and method is studied through numerical tests on modified RBTS Bus6 test system. Simulation results demonstrated that IBDR can improve the reliability of microgrid.

Reliability Evaluation of Bridges Based on Nonprobabilistic Response Surface Limit Method

Directory of Open Access Journals (Sweden)

Xuyong Chen

2017-01-01

Full Text Available Due to many uncertainties in nonprobabilistic reliability assessment of bridges, the limit state function is generally unknown. The traditional nonprobabilistic response surface method is a lengthy and oscillating iteration process and leads to difficultly solving the nonprobabilistic reliability index. This article proposes a nonprobabilistic response surface limit method based on the interval model. The intention of this method is to solve the upper and lower limits of the nonprobabilistic reliability index and to narrow the range of the nonprobabilistic reliability index. If the range of the reliability index reduces to an acceptable accuracy, the solution will be considered convergent, and the nonprobabilistic reliability index will be obtained. The case study indicates that using the proposed method can avoid oscillating iteration process, make iteration process stable and convergent, reduce iteration steps significantly, and improve computational efficiency and precision significantly compared with the traditional nonprobabilistic response surface method. Finally, the nonprobabilistic reliability evaluation process of bridge will be built through evaluating the reliability of one PC continuous rigid frame bridge with three spans using the proposed method, which appears to be more simple and reliable when lack of samples and parameters in the bridge nonprobabilistic reliability evaluation is present.

The Data Evaluation for Obtaining Accuracy and Reliability

International Nuclear Information System (INIS)

Kim, Chang Geun; Chae, Kyun Shik; Lee, Sang Tae; Bhang, Gun Woong

2012-01-01

Nemours scientific measurement results are flooded from the paper, data book, etc. as fast growing of internet. We meet many different measurement results on the same measurand. In this moment, we are face to choose most reliable one out of them. But it is not easy to choose and use the accurate and reliable data as we do at an ice cream parlor. Even expert users feel difficult to distinguish the accurate and reliable scientific data from huge amount of measurement results. For this reason, the data evaluation is getting more important as the fast growing of internet and globalization. Furthermore the expressions of measurement results are not in standardi-zation. As these need, the international movement has been enhanced. At the first step, the global harmonization of terminology used in metrology and the expression of uncertainty in measurement were published in ISO. These methods are wide spread to many area of science on their measurement to obtain the accuracy and reliability. In this paper, it is introduced that the GUM, SRD and data evaluation on atomic collisions.

FCMPSO: An Imputation for Missing Data Features in Heart Disease Classification

Science.gov (United States)

Salleh, Mohd Najib Mohd; Ashikin Samat, Nurul

2017-08-01

The application of data mining and machine learning in directing clinical research into possible hidden knowledge is becoming greatly influential in medical areas. Heart Disease is a killer disease around the world, and early prevention through efficient methods can help to reduce the mortality number. Medical data may contain many uncertainties, as they are fuzzy and vague in nature. Nonetheless, imprecise features data such as no values and missing values can affect quality of classification results. Nevertheless, the other complete features are still capable to give information in certain features. Therefore, an imputation approach based on Fuzzy C-Means and Particle Swarm Optimization (FCMPSO) is developed in preprocessing stage to help fill in the missing values. Then, the complete dataset is trained in classification algorithm, Decision Tree. The experiment is trained with Heart Disease dataset and the performance is analysed using accuracy, precision, and ROC values. Results show that the performance of Decision Tree is increased after the application of FCMSPO for imputation.

Practical considerations for sensitivity analysis after multiple imputation applied to epidemiological studies with incomplete data

Science.gov (United States)

2012-01-01

Background Multiple Imputation as usually implemented assumes that data are Missing At Random (MAR), meaning that the underlying missing data mechanism, given the observed data, is independent of the unobserved data. To explore the sensitivity of the inferences to departures from the MAR assumption, we applied the method proposed by Carpenter et al. (2007). This approach aims to approximate inferences under a Missing Not At random (MNAR) mechanism by reweighting estimates obtained after multiple imputation where the weights depend on the assumed degree of departure from the MAR assumption. Methods The method is illustrated with epidemiological data from a surveillance system of hepatitis C virus (HCV) infection in France during the 2001–2007 period. The subpopulation studied included 4343 HCV infected patients who reported drug use. Risk factors for severe liver disease were assessed. After performing complete-case and multiple imputation analyses, we applied the sensitivity analysis to 3 risk factors of severe liver disease: past excessive alcohol consumption, HIV co-infection and infection with HCV genotype 3. Results In these data, the association between severe liver disease and HIV was underestimated, if given the observed data the chance of observing HIV status is high when this is positive. Inference for two other risk factors were robust to plausible local departures from the MAR assumption. Conclusions We have demonstrated the practical utility of, and advocate, a pragmatic widely applicable approach to exploring plausible departures from the MAR assumption post multiple imputation. We have developed guidelines for applying this approach to epidemiological studies. PMID:22681630

Novel approach for evaluation of service reliability for electricity customers

Institute of Scientific and Technical Information of China (English)

JIANG; John; N

2009-01-01

Understanding reliability value for electricity customer is important to market-based reliability management. This paper proposes a novel approach to evaluate the reliability for electricity customers by using indifference curve between economic compensation for power interruption and service reliability of electricity. Indifference curve is formed by calculating different planning schemes of network expansion for different reliability requirements of customers, which reveals the information about economic values for different reliability levels for electricity customers, so that the reliability based on market supply demand mechanism can be established and economic signals can be provided for reliability management and enhancement.

A quantitative calculation for software reliability evaluation

Energy Technology Data Exchange (ETDEWEB)

Lee, Young-Jun; Lee, Jang-Soo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2016-10-15

To meet these regulatory requirements, the software used in the nuclear safety field has been ensured through the development, validation, safety analysis, and quality assurance activities throughout the entire process life cycle from the planning phase to the installation phase. A variety of activities, such as the quality assurance activities are also required to improve the quality of a software. However, there are limitations to ensure that the quality is improved enough. Therefore, the effort to calculate the reliability of the software continues for a quantitative evaluation instead of a qualitative evaluation. In this paper, we propose a quantitative calculation method for the software to be used for a specific operation of the digital controller in an NPP. After injecting random faults in the internal space of a developed controller and calculating the ability to detect the injected faults using diagnostic software, we can evaluate the software reliability of a digital controller in an NPP. We tried to calculate the software reliability of the controller in an NPP using a new method that differs from a traditional method. It calculates the fault detection coverage after injecting the faults into the software memory space rather than the activity through the life cycle process. We attempt differentiation by creating a new definition of the fault, imitating the software fault using the hardware, and giving a consideration and weights for injection faults.

Missing outcome data in a naturalistic psychodynamic group therapy study

DEFF Research Database (Denmark)

Jensen, Hans Henrik; Mortensen, Erik Lykke; Lotz, Martin

2017-01-01

might have had a reliable improvement in GSI. The SPSS standard statistical imputations procedure estimated that 48.6% of the patients reliably improved in GSI, and 50.2% when therapist evaluations were not included. It is concluded that therapist evaluations are essential in order to avoid bias...

A novel reliability evaluation method for large engineering systems

Directory of Open Access Journals (Sweden)

Reda Farag

2016-06-01

Full Text Available A novel reliability evaluation method for large nonlinear engineering systems excited by dynamic loading applied in time domain is presented. For this class of problems, the performance functions are expected to be function of time and implicit in nature. Available first- or second-order reliability method (FORM/SORM will be challenging to estimate reliability of such systems. Because of its inefficiency, the classical Monte Carlo simulation (MCS method also cannot be used for large nonlinear dynamic systems. In the proposed approach, only tens instead of hundreds or thousands of deterministic evaluations at intelligently selected points are used to extract the reliability information. A hybrid approach, consisting of the stochastic finite element method (SFEM developed by the author and his research team using FORM, response surface method (RSM, an interpolation scheme, and advanced factorial schemes, is proposed. The method is clarified with the help of several numerical examples.

A technical survey on issues of the quantitative evaluation of software reliability

International Nuclear Information System (INIS)

Park, J. K; Sung, T. Y.; Eom, H. S.; Jeong, H. S.; Park, J. H.; Kang, H. G.; Lee, K. Y.; Park, J. K.

2000-04-01

To develop the methodology for evaluating the software reliability included in digital instrumentation and control system (I and C), many kinds of methodologies/techniques that have been proposed from the software reliability engineering fuel are analyzed to identify the strong and week points of them. According to analysis results, methodologies/techniques that can be directly applied for the evaluation of the software reliability are not exist. Thus additional researches to combine the most appropriate methodologies/techniques from existing ones would be needed to evaluate the software reliability. (author)

Composite reliability evaluation for transmission network planning

Directory of Open Access Journals (Sweden)

Jiashen Teh

2018-01-01

Full Text Available As the penetration of wind power into the power system increases, the ability to assess the reliability impact of such interaction becomes more important. The composite reliability evaluations involving wind energy provide ample opportunities for assessing the benefits of different wind farm connection points. A connection to the weak area of the transmission network will require network reinforcement for absorbing the additional wind energy. Traditionally, the reinforcements are performed by constructing new transmission corridors. However, a new state-of-art technology such as the dynamic thermal rating (DTR system, provides new reinforcement strategy and this requires new reliability assessment method. This paper demonstrates a methodology for assessing the cost and the reliability of network reinforcement strategies by considering the DTR systems when large scale wind farms are connected to the existing power network. Sequential Monte Carlo simulations were performed and all DTRs and wind speed were simulated using the auto-regressive moving average (ARMA model. Various reinforcement strategies were assessed from their cost and reliability aspects. Practical industrial standards are used as guidelines when assessing costs. Due to this, the proposed methodology in this paper is able to determine the optimal reinforcement strategies when both the cost and reliability requirements are considered.

Accident Sequence Evaluation Program: Human reliability analysis procedure

International Nuclear Information System (INIS)

Swain, A.D.

1987-02-01

This document presents a shortened version of the procedure, models, and data for human reliability analysis (HRA) which are presented in the Handbook of Human Reliability Analysis With emphasis on Nuclear Power Plant Applications (NUREG/CR-1278, August 1983). This shortened version was prepared and tried out as part of the Accident Sequence Evaluation Program (ASEP) funded by the US Nuclear Regulatory Commission and managed by Sandia National Laboratories. The intent of this new HRA procedure, called the ''ASEP HRA Procedure,'' is to enable systems analysts, with minimal support from experts in human reliability analysis, to make estimates of human error probabilities and other human performance characteristics which are sufficiently accurate for many probabilistic risk assessments. The ASEP HRA Procedure consists of a Pre-Accident Screening HRA, a Pre-Accident Nominal HRA, a Post-Accident Screening HRA, and a Post-Accident Nominal HRA. The procedure in this document includes changes made after tryout and evaluation of the procedure in four nuclear power plants by four different systems analysts and related personnel, including human reliability specialists. The changes consist of some additional explanatory material (including examples), and more detailed definitions of some of the terms. 42 refs

Reliability model analysis and primary experimental evaluation of laser triggered pulse trigger

International Nuclear Information System (INIS)

Chen Debiao; Yang Xinglin; Li Yuan; Li Jin

2012-01-01

High performance pulse trigger can enhance performance and stability of the PPS. It is necessary to evaluate the reliability of the LTGS pulse trigger, so we establish the reliability analysis model of this pulse trigger based on CARMES software, the reliability evaluation is accord with the statistical results. (authors)

Reliability Evaluation and Improvement Approach of Chemical Production Man - Machine - Environment System

Science.gov (United States)

Miao, Yongchun; Kang, Rongxue; Chen, Xuefeng

2017-12-01

In recent years, with the gradual extension of reliability research, the study of production system reliability has become the hot topic in various industries. Man-machine-environment system is a complex system composed of human factors, machinery equipment and environment. The reliability of individual factor must be analyzed in order to gradually transit to the research of three-factor reliability. Meanwhile, the dynamic relationship among man-machine-environment should be considered to establish an effective blurry evaluation mechanism to truly and effectively analyze the reliability of such systems. In this paper, based on the system engineering, fuzzy theory, reliability theory, human error, environmental impact and machinery equipment failure theory, the reliabilities of human factor, machinery equipment and environment of some chemical production system were studied by the method of fuzzy evaluation. At last, the reliability of man-machine-environment system was calculated to obtain the weighted result, which indicated that the reliability value of this chemical production system was 86.29. Through the given evaluation domain it can be seen that the reliability of man-machine-environment integrated system is in a good status, and the effective measures for further improvement were proposed according to the fuzzy calculation results.

Auxiliary variables in multiple imputation in regression with missing X: a warning against including too many in small sample research

Directory of Open Access Journals (Sweden)

Hardt Jochen

2012-12-01

Full Text Available Abstract Background Multiple imputation is becoming increasingly popular. Theoretical considerations as well as simulation studies have shown that the inclusion of auxiliary variables is generally of benefit. Methods A simulation study of a linear regression with a response Y and two predictors X1 and X2 was performed on data with n = 50, 100 and 200 using complete cases or multiple imputation with 0, 10, 20, 40 and 80 auxiliary variables. Mechanisms of missingness were either 100% MCAR or 50% MAR + 50% MCAR. Auxiliary variables had low (r=.10 vs. moderate correlations (r=.50 with X’s and Y. Results The inclusion of auxiliary variables can improve a multiple imputation model. However, inclusion of too many variables leads to downward bias of regression coefficients and decreases precision. When the correlations are low, inclusion of auxiliary variables is not useful. Conclusion More research on auxiliary variables in multiple imputation should be performed. A preliminary rule of thumb could be that the ratio of variables to cases with complete data should not go below 1 : 3.

Evaluation of ECT reliability for axial ODSCC in steam generator tubes

International Nuclear Information System (INIS)

Lee, Jae Bong; Park, Jai Hak; Kim, Hong Deok; Chung, Han Sub

2010-01-01

The integrity of steam generator tubes is usually evaluated based on eddy current test (ECT) results. Because detection capacity of the ECT is not perfect, all of the physical flaws, which actually exist in steam generator tubes, cannot be detected by ECT inspection. Therefore it is very important to analyze ECT reliability in the integrity assessment of steam generators. The reliability of an ECT inspection system is divided into reliability of inspection technique and reliability of quality of analyst. And the reliability of ECT results is also divided into reliability of size and reliability of detection. The reliability of ECT sizing is often characterized as a linear regression model relating true flaw size data to measured flaw size data. The reliability of detection is characterized in terms of probability of detection (POD), which is expressed as a function of flaw size. In this paper the reliability of an ECT inspection system is analyzed quantitatively. POD of the ECT inspection system for axial outside diameter stress corrosion cracks (ODSCC) in steam generator tubes is evaluated. Using a log-logistic regression model, POD is evaluated from hit (detection) and miss (no detection) binary data obtained from destructive and non-destructive inspections of cracked tubes. Crack length and crack depth are considered as variables in multivariate log-logistic regression and their effects on detection capacity are assessed using two-dimensional POD (2-D POD) surface. The reliability of detection is also analyzed using POD for inspection technique (POD T ) and POD for analyst (POD A ).

Improved Correction of Misclassification Bias With Bootstrap Imputation.

Science.gov (United States)

van Walraven, Carl

2018-07-01

Diagnostic codes used in administrative database research can create bias due to misclassification. Quantitative bias analysis (QBA) can correct for this bias, requires only code sensitivity and specificity, but may return invalid results. Bootstrap imputation (BI) can also address misclassification bias but traditionally requires multivariate models to accurately estimate disease probability. This study compared misclassification bias correction using QBA and BI. Serum creatinine measures were used to determine severe renal failure status in 100,000 hospitalized patients. Prevalence of severe renal failure in 86 patient strata and its association with 43 covariates was determined and compared with results in which renal failure status was determined using diagnostic codes (sensitivity 71.3%, specificity 96.2%). Differences in results (misclassification bias) were then corrected with QBA or BI (using progressively more complex methods to estimate disease probability). In total, 7.4% of patients had severe renal failure. Imputing disease status with diagnostic codes exaggerated prevalence estimates [median relative change (range), 16.6% (0.8%-74.5%)] and its association with covariates [median (range) exponentiated absolute parameter estimate difference, 1.16 (1.01-2.04)]. QBA produced invalid results 9.3% of the time and increased bias in estimates of both disease prevalence and covariate associations. BI decreased misclassification bias with increasingly accurate disease probability estimates. QBA can produce invalid results and increase misclassification bias. BI avoids invalid results and can importantly decrease misclassification bias when accurate disease probability estimates are used.

Reliability evaluation of the ECCS of LWR No.2

International Nuclear Information System (INIS)

Tsujimura, Yasuhiro; Suzuki, Eiji

1987-01-01

In this paper, a new characteristic function of probability importance is proposed and discussed. The function represents overall characteristics of the system reliability relating to a failure probability of each system component. Further, results of evaluation brought about by the method for practical system reliability design are shown. (author)

Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

Science.gov (United States)

Song, Minsun; Wheeler, William; Caporaso, Neil E; Landi, Maria Teresa; Chatterjee, Nilanjan

2018-03-01

Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package. © 2017 WILEY PERIODICALS, INC.

Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

Science.gov (United States)

Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

2018-06-01

Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Evaluation of aileron actuator reliability with censored data

Directory of Open Access Journals (Sweden)

Li Huaiyuan

2015-08-01

Full Text Available For the purpose of enhancing reliability of aileron of Airbus new-generation A350XWB, an evaluation of aileron reliability on the basis of maintenance data is presented in this paper. Practical maintenance data contains large number of censoring samples, information uncertainty of which makes it hard to evaluate reliability of aileron actuator. Considering that true lifetime of censoring sample has identical distribution with complete sample, if censoring sample is transformed into complete sample, conversion frequency of censoring sample can be estimated according to frequency of complete sample. On the one hand, standard life table estimation and product limit method are improved on the basis of such conversion frequency, enabling accurate estimation of various censoring samples. On the other hand, by taking such frequency as one of the weight factors and integrating variance of order statistics under standard distribution, weighted least square estimation is formed for accurately estimating various censoring samples. Large amounts of experiments and simulations show that reliabilities of improved life table and improved product limit method are closer to the true value and more conservative; moreover, weighted least square estimate (WLSE, with conversion frequency of censoring sample and variances of order statistics as the weights, can still estimate accurately with high proportion of censored data in samples. Algorithm in this paper has good effect and can accurately estimate the reliability of aileron actuator even with small sample and high censoring rate. This research has certain significance in theory and engineering practice.

Accident Sequence Evaluation Program: Human reliability analysis procedure

Energy Technology Data Exchange (ETDEWEB)

Swain, A.D.

1987-02-01

This document presents a shortened version of the procedure, models, and data for human reliability analysis (HRA) which are presented in the Handbook of Human Reliability Analysis With emphasis on Nuclear Power Plant Applications (NUREG/CR-1278, August 1983). This shortened version was prepared and tried out as part of the Accident Sequence Evaluation Program (ASEP) funded by the US Nuclear Regulatory Commission and managed by Sandia National Laboratories. The intent of this new HRA procedure, called the ''ASEP HRA Procedure,'' is to enable systems analysts, with minimal support from experts in human reliability analysis, to make estimates of human error probabilities and other human performance characteristics which are sufficiently accurate for many probabilistic risk assessments. The ASEP HRA Procedure consists of a Pre-Accident Screening HRA, a Pre-Accident Nominal HRA, a Post-Accident Screening HRA, and a Post-Accident Nominal HRA. The procedure in this document includes changes made after tryout and evaluation of the procedure in four nuclear power plants by four different systems analysts and related personnel, including human reliability specialists. The changes consist of some additional explanatory material (including examples), and more detailed definitions of some of the terms. 42 refs.

Applying an efficient K-nearest neighbor search to forest attribute imputation

Science.gov (United States)

Andrew O. Finley; Ronald E. McRoberts; Alan R. Ek

2006-01-01

This paper explores the utility of an efficient nearest neighbor (NN) search algorithm for applications in multi-source kNN forest attribute imputation. The search algorithm reduces the number of distance calculations between a given target vector and each reference vector, thereby, decreasing the time needed to discover the NN subset. Results of five trials show gains...

Missing data in clinical trials: control-based mean imputation and sensitivity analysis.

Science.gov (United States)

Mehrotra, Devan V; Liu, Fang; Permutt, Thomas

2017-09-01

In some randomized (drug versus placebo) clinical trials, the estimand of interest is the between-treatment difference in population means of a clinical endpoint that is free from the confounding effects of "rescue" medication (e.g., HbA1c change from baseline at 24 weeks that would be observed without rescue medication regardless of whether or when the assigned treatment was discontinued). In such settings, a missing data problem arises if some patients prematurely discontinue from the trial or initiate rescue medication while in the trial, the latter necessitating the discarding of post-rescue data. We caution that the commonly used mixed-effects model repeated measures analysis with the embedded missing at random assumption can deliver an exaggerated estimate of the aforementioned estimand of interest. This happens, in part, due to implicit imputation of an overly optimistic mean for "dropouts" (i.e., patients with missing endpoint data of interest) in the drug arm. We propose an alternative approach in which the missing mean for the drug arm dropouts is explicitly replaced with either the estimated mean of the entire endpoint distribution under placebo (primary analysis) or a sequence of increasingly more conservative means within a tipping point framework (sensitivity analysis); patient-level imputation is not required. A supplemental "dropout = failure" analysis is considered in which a common poor outcome is imputed for all dropouts followed by a between-treatment comparison using quantile regression. All analyses address the same estimand and can adjust for baseline covariates. Three examples and simulation results are used to support our recommendations. Copyright © 2017 John Wiley & Sons, Ltd.

Relativity evaluation of reliability on operation in nuclear power plant

International Nuclear Information System (INIS)

Inata, Takashi

1987-01-01

The report presents a quantitative method for evaluating the reliability of operations conducted in nuclear power plants. The quantitative reliability evaluation method is based on the 'detailed block diagram analysis (De-BDA)'. All units of a series of operations are separately displayed for each block and combined sequentially. Then, calculation is performed to evaluate the reliability. Basically, De-BDA calculation is made for pairs of operation labels, which are connected in parallel or in series at different subordination levels. The applicability of the De-BDA method is demonstrated by carrying out calculation for three model cases: operations in the event of malfunction of the control valve in the main water supply system for PWR, switching from an electrically-operated water supply pump to a turbin-operated water supply pump, and isolation and water removal operation for a low-pressure condensate pump. It is shown that the relative importance of each unit of a series of operations can be evaluated, making it possible to extract those units of greater importance, and that the priority among the factors which affect the reliability of operations can be determined. Results of the De-BDA calculation can serve to find important points to be considered in developing an operation manual, conducting education and training, and improving facilities. (Nogami, K.)

Random Forest as an Imputation Method for Education and Psychology Research: Its Impact on Item Fit and Difficulty of the Rasch Model

Science.gov (United States)

Golino, Hudson F.; Gomes, Cristiano M. A.

2016-01-01

This paper presents a non-parametric imputation technique, named random forest, from the machine learning field. The random forest procedure has two main tuning parameters: the number of trees grown in the prediction and the number of predictors used. Fifty experimental conditions were created in the imputation procedure, with different…

Construction and Evaluation of Reliability and Validity of Reasoning Ability Test

Science.gov (United States)

Bhat, Mehraj A.

2014-01-01

This paper is based on the construction and evaluation of reliability and validity of reasoning ability test at secondary school students. In this paper an attempt was made to evaluate validity, reliability and to determine the appropriate standards to interpret the results of reasoning ability test. The test includes 45 items to measure six types…

Imputation of the rare HOXB13 G84E mutation and cancer risk in a large population-based cohort.

Directory of Open Access Journals (Sweden)

Thomas J Hoffmann

2015-01-01

Full Text Available An efficient approach to characterizing the disease burden of rare genetic variants is to impute them into large well-phenotyped cohorts with existing genome-wide genotype data using large sequenced referenced panels. The success of this approach hinges on the accuracy of rare variant imputation, which remains controversial. For example, a recent study suggested that one cannot adequately impute the HOXB13 G84E mutation associated with prostate cancer risk (carrier frequency of 0.0034 in European ancestry participants in the 1000 Genomes Project. We show that by utilizing the 1000 Genomes Project data plus an enriched reference panel of mutation carriers we were able to accurately impute the G84E mutation into a large cohort of 83,285 non-Hispanic White participants from the Kaiser Permanente Research Program on Genes, Environment and Health Genetic Epidemiology Research on Adult Health and Aging cohort. Imputation authenticity was confirmed via a novel classification and regression tree method, and then empirically validated analyzing a subset of these subjects plus an additional 1,789 men from Kaiser specifically genotyped for the G84E mutation (r2 = 0.57, 95% CI = 0.37–0.77. We then show the value of this approach by using the imputed data to investigate the impact of the G84E mutation on age-specific prostate cancer risk and on risk of fourteen other cancers in the cohort. The age-specific risk of prostate cancer among G84E mutation carriers was higher than among non-carriers. Risk estimates from Kaplan-Meier curves were 36.7% versus 13.6% by age 72, and 64.2% versus 24.2% by age 80, for G84E mutation carriers and non-carriers, respectively (p = 3.4x10-12. The G84E mutation was also associated with an increase in risk for the fourteen other most common cancers considered collectively (p = 5.8x10-4 and more so in cases diagnosed with multiple cancer types, both those including and not including prostate cancer, strongly suggesting

How reliable are forensic evaluations of legal sanity?

Science.gov (United States)

Gowensmith, W Neil; Murrie, Daniel C; Boccaccini, Marcus T

2013-04-01

When different clinicians evaluate the same criminal defendant's legal sanity, do they reach the same conclusion? Because Hawaii law requires multiple, independent evaluations when questions about legal sanity arise, Hawaii allows for the first contemporary study of the reliability of legal sanity opinions in routine practice in the United States. We examined 483 evaluation reports, addressing 165 criminal defendants, in which up to three forensic psychiatrists or psychologists offered independent opinions on a defendant's legal sanity. Evaluators reached unanimous agreement regarding legal sanity in only 55.1% of cases. Evaluators tended to disagree more often when a defendant was under the influence of drugs or alcohol at the time of the offense. But evaluators tended to agree more often when they agreed about diagnosing a psychotic disorder, or when the defendant had been psychiatrically hospitalized shortly before the offense. In court, judges followed the majority opinion among evaluators in 91% of cases. But when judges disagreed with the majority opinion, they usually did so to find defendants legally sane, rather than insane. Overall, this study indicates that reliability among practicing forensic evaluators addressing legal sanity may be poorer than the field has tended to assume. Although agreement appears more likely in some cases than others, the frequent disagreements suggest a need for improved training and practice.

Failure mechanism dependence and reliability evaluation of non-repairable system

International Nuclear Information System (INIS)

Chen, Ying; Yang, Liu; Ye, Cui; Kang, Rui

2015-01-01

Reliability study of electronic system with the physics-of-failure method has been promoted due to the increase knowledge of electronic failure mechanisms. System failure initiates from independent failure mechanisms, have effect on or affect by other failure mechanisms and finally result in system failure. Failure mechanisms in a non-repairable system have many kinds of correlation. One failure mechanism developing to a certain degree will trigger, accelerate or inhibit another or many other failure mechanisms, some kind of failure mechanisms may have the same effect on the failure site, component or system. The destructive effect will be accumulated and result in early failure. This paper presents a reliability evaluation method considering correlativity among failure mechanisms, which includes trigger, acceleration, inhibition, accumulation, and competition. Based on fundamental rule of physics of failure, decoupling methods of these correlations are discussed. With a case, reliability of electronic system is evaluated considering failure mechanism dependence. - Highlights: • Five types of failure mechanism correlations are described. • Decoupling methods of these correlations are discussed. • A reliability evaluation method considering mechanism dependence is proposed. • Results are quite different to results under failure independence assumption

GACT: a Genome build and Allele definition Conversion Tool for SNP imputation and meta-analysis in genetic association studies.

Science.gov (United States)

Sulovari, Arvis; Li, Dawei

2014-07-19

Genome-wide association studies (GWAS) have successfully identified genes associated with complex human diseases. Although much of the heritability remains unexplained, combining single nucleotide polymorphism (SNP) genotypes from multiple studies for meta-analysis will increase the statistical power to identify new disease-associated variants. Meta-analysis requires same allele definition (nomenclature) and genome build among individual studies. Similarly, imputation, commonly-used prior to meta-analysis, requires the same consistency. However, the genotypes from various GWAS are generated using different genotyping platforms, arrays or SNP-calling approaches, resulting in use of different genome builds and allele definitions. Incorrect assumptions of identical allele definition among combined GWAS lead to a large portion of discarded genotypes or incorrect association findings. There is no published tool that predicts and converts among all major allele definitions. In this study, we have developed a tool, GACT, which stands for Genome build and Allele definition Conversion Tool, that predicts and inter-converts between any of the common SNP allele definitions and between the major genome builds. In addition, we assessed several factors that may affect imputation quality, and our results indicated that inclusion of singletons in the reference had detrimental effects while ambiguous SNPs had no measurable effect. Unexpectedly, exclusion of genotypes with missing rate > 0.001 (40% of study SNPs) showed no significant decrease of imputation quality (even significantly higher when compared to the imputation with singletons in the reference), especially for rare SNPs. GACT is a new, powerful, and user-friendly tool with both command-line and interactive online versions that can accurately predict, and convert between any of the common allele definitions and between genome builds for genome-wide meta-analysis and imputation of genotypes from SNP-arrays or deep

Alternate ways for automation of evaluating nuclear physical data reliability from primary literature

International Nuclear Information System (INIS)

Golashvili, T.V.; Tsvetaev, S.M.

1983-01-01

Methods, possible ways, criteria and algorithms for organizing an automated system for evaluating nuclear physical data reliability from primary literature are discussed. It is noted that automation of data reliability evaluation does not substitute for a scientist dealing with data evaluation. It only releases him from hard, monotonous and tedious work not requiring erudition or profound knowledge. Computers will facilitate and accelerate the work of the expert and, hence, leat to a sharp increase of a bulk of works on evaluation of data reliability

Study on evaluation of construction reliability for engineering project based on fuzzy language operator

Science.gov (United States)

Shi, Yu-Fang; Ma, Yi-Yi; Song, Ping-Ping

2018-03-01

System Reliability Theory is a research hotspot of management science and system engineering in recent years, and construction reliability is useful for quantitative evaluation of project management level. According to reliability theory and target system of engineering project management, the defination of construction reliability appears. Based on fuzzy mathematics theory and language operator, value space of construction reliability is divided into seven fuzzy subsets and correspondingly, seven membership function and fuzzy evaluation intervals are got with the operation of language operator, which provides the basis of corresponding method and parameter for the evaluation of construction reliability. This method is proved to be scientific and reasonable for construction condition and an useful attempt for theory and method research of engineering project system reliability.

Evaluation of Network Reliability for Computer Networks with Multiple Sources

Directory of Open Access Journals (Sweden)

Yi-Kuei Lin

2012-01-01

Full Text Available Evaluating the reliability of a network with multiple sources to multiple sinks is a critical issue from the perspective of quality management. Due to the unrealistic definition of paths of network models in previous literature, existing models are not appropriate for real-world computer networks such as the Taiwan Advanced Research and Education Network (TWAREN. This paper proposes a modified stochastic-flow network model to evaluate the network reliability of a practical computer network with multiple sources where data is transmitted through several light paths (LPs. Network reliability is defined as being the probability of delivering a specified amount of data from the sources to the sink. It is taken as a performance index to measure the service level of TWAREN. This paper studies the network reliability of the international portion of TWAREN from two sources (Taipei and Hsinchu to one sink (New York that goes through a submarine and land surface cable between Taiwan and the United States.

Differential network analysis with multiply imputed lipidomic data.

Directory of Open Access Journals (Sweden)

Maiju Kujala

Full Text Available The importance of lipids for cell function and health has been widely recognized, e.g., a disorder in the lipid composition of cells has been related to atherosclerosis caused cardiovascular disease (CVD. Lipidomics analyses are characterized by large yet not a huge number of mutually correlated variables measured and their associations to outcomes are potentially of a complex nature. Differential network analysis provides a formal statistical method capable of inferential analysis to examine differences in network structures of the lipids under two biological conditions. It also guides us to identify potential relationships requiring further biological investigation. We provide a recipe to conduct permutation test on association scores resulted from partial least square regression with multiple imputed lipidomic data from the LUdwigshafen RIsk and Cardiovascular Health (LURIC study, particularly paying attention to the left-censored missing values typical for a wide range of data sets in life sciences. Left-censored missing values are low-level concentrations that are known to exist somewhere between zero and a lower limit of quantification. To make full use of the LURIC data with the missing values, we utilize state of the art multiple imputation techniques and propose solutions to the challenges that incomplete data sets bring to differential network analysis. The customized network analysis helps us to understand the complexities of the underlying biological processes by identifying lipids and lipid classes that interact with each other, and by recognizing the most important differentially expressed lipids between two subgroups of coronary artery disease (CAD patients, the patients that had a fatal CVD event and the ones who remained stable during two year follow-up.

Multiple imputation for multivariate data with missing and below-threshold measurements: time-series concentrations of pollutants in the Arctic.

Science.gov (United States)

Hopke, P K; Liu, C; Rubin, D B

2001-03-01

Many chemical and environmental data sets are complicated by the existence of fully missing values or censored values known to lie below detection thresholds. For example, week-long samples of airborne particulate matter were obtained at Alert, NWT, Canada, between 1980 and 1991, where some of the concentrations of 24 particulate constituents were coarsened in the sense of being either fully missing or below detection limits. To facilitate scientific analysis, it is appealing to create complete data by filling in missing values so that standard complete-data methods can be applied. We briefly review commonly used strategies for handling missing values and focus on the multiple-imputation approach, which generally leads to valid inferences when faced with missing data. Three statistical models are developed for multiply imputing the missing values of airborne particulate matter. We expect that these models are useful for creating multiple imputations in a variety of incomplete multivariate time series data sets.

Handling missing data for the identification of charged particles in a multilayer detector: A comparison between different imputation methods

Energy Technology Data Exchange (ETDEWEB)

Riggi, S., E-mail: sriggi@oact.inaf.it [INAF - Osservatorio Astrofisico di Catania (Italy); Riggi, D. [Keras Strategy - Milano (Italy); Riggi, F. [Dipartimento di Fisica e Astronomia - Università di Catania (Italy); INFN, Sezione di Catania (Italy)

2015-04-21

Identification of charged particles in a multilayer detector by the energy loss technique may also be achieved by the use of a neural network. The performance of the network becomes worse when a large fraction of information is missing, for instance due to detector inefficiencies. Algorithms which provide a way to impute missing information have been developed over the past years. Among the various approaches, we focused on normal mixtures’ models in comparison with standard mean imputation and multiple imputation methods. Further, to account for the intrinsic asymmetry of the energy loss data, we considered skew-normal mixture models and provided a closed form implementation in the Expectation-Maximization (EM) algorithm framework to handle missing patterns. The method has been applied to a test case where the energy losses of pions, kaons and protons in a six-layers’ Silicon detector are considered as input neurons to a neural network. Results are given in terms of reconstruction efficiency and purity of the various species in different momentum bins.

Which DTW Method Applied to Marine Univariate Time Series Imputation

OpenAIRE

Phan , Thi-Thu-Hong; Caillault , Émilie; Lefebvre , Alain; Bigand , André

2017-01-01

International audience; Missing data are ubiquitous in any domains of applied sciences. Processing datasets containing missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Therefore, the aim of this paper is to build a framework for filling missing values in univariate time series and to perform a comparison of different similarity metrics used for the imputation task. This allows to suggest the most suitable methods for the imp...

Towards a more efficient representation of imputation operators in TPOT

OpenAIRE

Garciarena, Unai; Mendiburu, Alexander; Santana, Roberto

2018-01-01

Automated Machine Learning encompasses a set of meta-algorithms intended to design and apply machine learning techniques (e.g., model selection, hyperparameter tuning, model assessment, etc.). TPOT, a software for optimizing machine learning pipelines based on genetic programming (GP), is a novel example of this kind of applications. Recently we have proposed a way to introduce imputation methods as part of TPOT. While our approach was able to deal with problems with missing data, it can prod...

Assessing the Reliability of Student Evaluations of Teaching: Choosing the Right Coefficient

Science.gov (United States)

Morley, Donald

2014-01-01

Many of the studies used to support the claim that student evaluations of teaching are reliable measures of teaching effectiveness have frequently calculated inappropriate reliability coefficients. This paper points to three coefficients that would be appropriate depending on if student evaluations were used for formative or summative purposes.…

Reliability evaluation programmable logic devices

International Nuclear Information System (INIS)

Srivani, L.; Murali, N.; Thirugnana Murthy, D.; Satya Murty, S.A.V.

2014-01-01

Programmable Logic Devices (PLD) are widely used as basic building modules in high integrity systems, considering their robust features such as gate density, performance, speed etc. PLDs are used to implement digital design such as bus interface logic, control logic, sequencing logic, glue logic etc. Due to semiconductor evolution, new PLDs with state-of-the-art features are arriving to the market. Since these devices are reliable as per the manufacturer's specification, they were used in the design of safety systems. But due to their reduced market life, the availability of performance data is limited. So evaluating the PLD before deploying in a safety system is very important. This paper presents a survey on the use of PLDs in the nuclear domain and the steps involved in the evaluation of PLD using Quantitative Accelerated Life Testing. (author)

Reliability of the AMA Guides to the Evaluation of Permanent Impairment.

Science.gov (United States)

Forst, Linda; Friedman, Lee; Chukwu, Abraham

2010-12-01

AMA's Guides to the Evaluation of Permanent Impairment is used to rate loss of function and determine compensation and ability to work after injury or illness; however, there are few studies that evaluate reliability or construct validity. To evaluate the reliability of the fifth and sixth editions for back injury; to determine best methods for further study. Intra-class correlation coefficients within and between raters were relatively high. There was wider variability for individual cases. Impairment ratings were lower and correlated less well for the sixth edition, though confidence intervals overlapped. The sixth edition may not be an improvement over the fifth. A research agenda should include investigations of reliability and construct validity for different body sites and organ systems along the entire rating scale and among different categories of raters.

Nearest neighbor imputation using spatial-temporal correlations in wireless sensor networks.

Science.gov (United States)

Li, YuanYuan; Parker, Lynne E

2014-01-01

Missing data is common in Wireless Sensor Networks (WSNs), especially with multi-hop communications. There are many reasons for this phenomenon, such as unstable wireless communications, synchronization issues, and unreliable sensors. Unfortunately, missing data creates a number of problems for WSNs. First, since most sensor nodes in the network are battery-powered, it is too expensive to have the nodes retransmit missing data across the network. Data re-transmission may also cause time delays when detecting abnormal changes in an environment. Furthermore, localized reasoning techniques on sensor nodes (such as machine learning algorithms to classify states of the environment) are generally not robust enough to handle missing data. Since sensor data collected by a WSN is generally correlated in time and space, we illustrate how replacing missing sensor values with spatially and temporally correlated sensor values can significantly improve the network's performance. However, our studies show that it is important to determine which nodes are spatially and temporally correlated with each other. Simple techniques based on Euclidean distance are not sufficient for complex environmental deployments. Thus, we have developed a novel Nearest Neighbor (NN) imputation method that estimates missing data in WSNs by learning spatial and temporal correlations between sensor nodes. To improve the search time, we utilize a k d-tree data structure, which is a non-parametric, data-driven binary search tree. Instead of using traditional mean and variance of each dimension for k d-tree construction, and Euclidean distance for k d-tree search, we use weighted variances and weighted Euclidean distances based on measured percentages of missing data. We have evaluated this approach through experiments on sensor data from a volcano dataset collected by a network of Crossbow motes, as well as experiments using sensor data from a highway traffic monitoring application. Our experimental

Treatments of Missing Values in Large National Data Affect Conclusions: The Impact of Multiple Imputation on Arthroplasty Research.

Science.gov (United States)

Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Su, Edwin P; Grauer, Jonathan N

2018-03-01

Despite the advantages of large, national datasets, one continuing concern is missing data values. Complete case analysis, where only cases with complete data are analyzed, is commonly used rather than more statistically rigorous approaches such as multiple imputation. This study characterizes the potential selection bias introduced using complete case analysis and compares the results of common regressions using both techniques following unicompartmental knee arthroplasty. Patients undergoing unicompartmental knee arthroplasty were extracted from the 2005 to 2015 National Surgical Quality Improvement Program. As examples, the demographics of patients with and without missing preoperative albumin and hematocrit values were compared. Missing data were then treated with both complete case analysis and multiple imputation (an approach that reproduces the variation and associations that would have been present in a full dataset) and the conclusions of common regressions for adverse outcomes were compared. A total of 6117 patients were included, of which 56.7% were missing at least one value. Younger, female, and healthier patients were more likely to have missing preoperative albumin and hematocrit values. The use of complete case analysis removed 3467 patients from the study in comparison with multiple imputation which included all 6117 patients. The 2 methods of handling missing values led to differing associations of low preoperative laboratory values with commonly studied adverse outcomes. The use of complete case analysis can introduce selection bias and may lead to different conclusions in comparison with the statistically rigorous multiple imputation approach. Joint surgeons should consider the methods of handling missing values when interpreting arthroplasty research. Copyright © 2017 Elsevier Inc. All rights reserved.

Incorporating Cyber Layer Failures in Composite Power System Reliability Evaluations

Directory of Open Access Journals (Sweden)

Yuqi Han

2015-08-01

Full Text Available This paper proposes a novel approach to analyze the impacts of cyber layer failures (i.e., protection failures and monitoring failures on the reliability evaluation of composite power systems. The reliability and availability of the cyber layer and its protection and monitoring functions with various topologies are derived based on a reliability block diagram method. The availability of the physical layer components are modified via a multi-state Markov chain model, in which the component protection and monitoring strategies, as well as the cyber layer topology, are simultaneously considered. Reliability indices of composite power systems are calculated through non-sequential Monte-Carlo simulation. Case studies demonstrate that operational reliability downgrades in cyber layer function failure situations. Moreover, protection function failures have more significant impact on the downgraded reliability than monitoring function failures do, and the reliability indices are especially sensitive to the change of the cyber layer function availability in the range from 0.95 to 1.

Evaluation of Stock Management Strategies Reliability at Dependent Demand

Directory of Open Access Journals (Sweden)

Lukinskiy Valery

2017-03-01

Full Text Available For efficiently increasing the logistic systems, the core specialists’ attention has to be directed to reducing costs and increasing supply chains reliability. A decent attention to costs reduction has already been paid, so it can be stated that in this way there is a significant progress. But the problem of reliability evaluation is still insufficiently explored, particularly, in such an important sphere as inventory management at the dependent demand.

System reliability evaluation of a touch panel manufacturing system with defect rate and reworking

International Nuclear Information System (INIS)

Lin, Yi-Kuei; Huang, Cheng-Fu; Chang, Ping-Chen

2013-01-01

In recent years, portable consumer electronic products, such as cell phone, GPS, digital camera, tablet PC, and notebook are using touch panel as interface. With the demand of touch panel increases, performance assessment is essential for touch panel production. This paper develops a method to evaluate system reliability of a touch panel manufacturing system (TPMS) with defect rate of each workstation and takes reworking actions into account. The system reliability which evaluates the possibility of demand satisfaction can provide to managers with an understanding of the system capability and can indicate possible improvements. First, we construct a capacitated manufacturing network (CMN) for a TPMS. Second, a decomposition technique is developed to determine the input flow of each workstation based on the CMN. Finally, we generate the minimal capacity vectors that should be provided to satisfy the demand. The system reliability is subsequently evaluated in terms of the minimal capacity vectors. A further decision making issue is discussed to decide a reliable production strategy. -- Graphical abstract: The proposed procedure to evaluate system reliability of the touch panel manufacturing system (TPMS). Highlights: • The system reliability of a touch panel manufacturing system (TPMS) is evaluated. • The reworking actions are taken into account in the TPMS. • A capacitated manufacturing network is constructed for the TPMS. • A procedure is proposed to evaluate system reliability of TPMS

Imputation of genotypes from low density (50,000 markers) to high density (700,000 markers) of cows from research herds in Europe, North America, and Australasia using 2 reference populations

DEFF Research Database (Denmark)

Pryce, J E; Johnston, J; Hayes, B J

2014-01-01

detection in genome-wide association studies and the accuracy of genomic selection may increase when the low-density genotypes are imputed to higher density. Genotype data were available from 10 research herds: 5 from Europe [Denmark, Germany, Ireland, the Netherlands, and the United Kingdom (UK)], 2 from...... reference populations. Although it was not possible to use a combined reference population, which would probably result in the highest accuracies of imputation, differences arising from using 2 high-density reference populations on imputing 50,000-marker genotypes of 583 animals (from the UK) were...... information exploited. The UK animals were also included in the North American data set (n = 1,579) that was imputed to high density using a reference population of 2,018 bulls. After editing, 591,213 genotypes on 5,999 animals from 10 research herds remained. The correlation between imputed allele...

Interim reliability evaluation program, Browns Ferry fault trees

International Nuclear Information System (INIS)

Stewart, M.E.

1981-01-01

An abbreviated fault tree method is used to evaluate and model Browns Ferry systems in the Interim Reliability Evaluation programs, simplifying the recording and displaying of events, yet maintaining the system of identifying faults. The level of investigation is not changed. The analytical thought process inherent in the conventional method is not compromised. But the abbreviated method takes less time, and the fault modes are much more visible

A New Tool for Nutrition App Quality Evaluation (AQEL): Development, Validation, and Reliability Testing.

Science.gov (United States)

DiFilippo, Kristen Nicole; Huang, Wenhao; Chapman-Novakofski, Karen M

2017-10-27

The extensive availability and increasing use of mobile apps for nutrition-based health interventions makes evaluation of the quality of these apps crucial for integration of apps into nutritional counseling. The goal of this research was the development, validation, and reliability testing of the app quality evaluation (AQEL) tool, an instrument for evaluating apps' educational quality and technical functionality. Items for evaluating app quality were adapted from website evaluations, with additional items added to evaluate the specific characteristics of apps, resulting in 79 initial items. Expert panels of nutrition and technology professionals and app users reviewed items for face and content validation. After recommended revisions, nutrition experts completed a second AQEL review to ensure clarity. On the basis of 150 sets of responses using the revised AQEL, principal component analysis was completed, reducing AQEL into 5 factors that underwent reliability testing, including internal consistency, split-half reliability, test-retest reliability, and interrater reliability (IRR). Two additional modifiable constructs for evaluating apps based on the age and needs of the target audience as selected by the evaluator were also tested for construct reliability. IRR testing using intraclass correlations (ICC) with all 7 constructs was conducted, with 15 dietitians evaluating one app. Development and validation resulted in the 51-item AQEL. These were reduced to 25 items in 5 factors after principal component analysis, plus 9 modifiable items in two constructs that were not included in principal component analysis. Internal consistency and split-half reliability of the following constructs derived from principal components analysis was good (Cronbach alpha >.80, Spearman-Brown coefficient >.80): behavior change potential, support of knowledge acquisition, app function, and skill development. App purpose split half-reliability was .65. Test-retest reliability showed no

Test-retest and interrater reliability of the functional lower extremity evaluation.

Science.gov (United States)

Haitz, Karyn; Shultz, Rebecca; Hodgins, Melissa; Matheson, Gordon O

2014-12-01

Repeated-measures clinical measurement reliability study. To establish the reliability and face validity of the Functional Lower Extremity Evaluation (FLEE). The FLEE is a 45-minute battery of 8 standardized functional performance tests that measures 3 components of lower extremity function: control, power, and endurance. The reliability and normative values for the FLEE in healthy athletes are unknown. A face validity survey for the FLEE was sent to sports medicine personnel to evaluate the level of importance and frequency of clinical usage of each test included in the FLEE. The FLEE was then administered and rated for 40 uninjured athletes. To assess test-retest reliability, each athlete was tested twice, 1 week apart, by the same rater. To assess interrater reliability, 3 raters scored each athlete during 1 of the testing sessions. Intraclass correlation coefficients were used to assess the test-retest and interrater reliability of each of the FLEE tests. In the face validity survey, the FLEE tests were rated as highly important by 58% to 71% of respondents but frequently used by only 26% to 45% of respondents. Interrater reliability intraclass correlation coefficients ranged from 0.83 to 1.00, and test-retest reliability ranged from 0.71 to 0.95. The FLEE tests are considered clinically important for assessing lower extremity function by sports medicine personnel but are underused. The FLEE also is a reliable assessment tool. Future studies are required to determine if use of the FLEE to make return-to-play decisions may reduce reinjury rates.

Ultrasound evaluation of the abductor hallucis muscle: Reliability study

Directory of Open Access Journals (Sweden)

Hing Wayne A

2008-09-01

Full Text Available Abstract Background The Abductor hallucis muscle (AbdH plays an integral role during gait and is often affected in pathological foot conditions. The aim of this study was to evaluate the within and between-session intra-tester reliability using diagnostic ultrasound of the dorso-plantar thickness, medio-lateral width and cross-sectional area, of the AbdH in asymptomatic adults. Methods The AbdH muscles of thirty asymptomatic subjects were imaged and then measured using a Philips HD11 Ultrasound machine. Interclass correlation coefficients (ICC with 95% confidence intervals (CI were used to calculate both within and between session intra-tester reliability. Results The within-session reliability results demonstrated for dorso-plantar thickness an ICC of 0.97 (95% CI: 0.99–0.99; medio-lateral width an ICC: of 0.97 (95% CI: 0.92–0.97 and cross-sectional area an ICC of 0.98 (95% CI: 0.98–0.99. Between-session reliability results demonstrated for dorso-plantar thickness an ICC of 0.97 (95% CI: 0.95 to 0.98; medio-lateral width an ICC of 0.94 (95% CI 0.90 to 0.96 and for cross-sectional area an ICC of 0.79 (95% CI 0.65 to 0.88. Conclusion Diagnostic ultrasound has the potential to be a reliable tool for evaluating the AbdH muscle in asymptomatic subjects. Subsequent studies may be conducted to provide a better understanding of the AbdH function in foot and ankle pathologies.

Composite system reliability evaluation by stochastic calculation of system operation

Energy Technology Data Exchange (ETDEWEB)

Haubrick, H -J; Hinz, H -J; Landeck, E [Dept. of Power Systems and Power Economics (Germany)

1994-12-31

This report describes a new developed probabilistic approach for steady-state composite system reliability evaluation and its exemplary application to a bulk power test system. The new computer program called PHOENIX takes into consideration transmission limitations, outages of lines and power stations and, as a central element, a highly sophisticated model to the dispatcher performing remedial actions after disturbances. The kernel of the new method is a procedure for optimal power flow calculation that has been specially adapted for the use in reliability evaluations under the above mentioned conditions. (author) 11 refs., 8 figs., 1 tab.

EVALUATION OF HUMAN RELIABILITY IN SELECTED ACTIVITIES IN THE RAILWAY INDUSTRY

Directory of Open Access Journals (Sweden)

Erika SUJOVÁ

2016-07-01

Full Text Available The article focuses on evaluation of human reliability in the human – machine system in the railway industry. Based on a survey of a train dispatcher and of selected activities, we have identified risk factors affecting the dispatcher‘s work and the evaluated risk level of their influence on the reliability and safety of preformed activities. The research took place at the authors‘ work place between 2012-2013. A survey method was used. With its help, authors were able to identify selected work activities of train dispatcher’s risk factors that affect his/her work and the evaluated seriousness of its in-fluence on the reliability and safety of performed activities. Amongst the most important finding fall expressions of un-clear and complicated internal regulations and work processes, a feeling of being overworked, fear for one’s safety at small, insufficiently protected stations.

SPSS Macros for Assessing the Reliability and Agreement of Student Evaluations of Teaching

Science.gov (United States)

Morley, Donald D.

2009-01-01

This article reports and demonstrates two SPSS macros for calculating Krippendorff's alpha and intraclass reliability coefficients in repetitive situations where numerous coefficients are needed. Specifically, the reported SPSS macros were used to evaluate the interrater agreement and reliability of student evaluations of teaching in thousands of…

Mapping change of older forest with nearest-neighbor imputation and Landsat time-series

Science.gov (United States)

Janet L. Ohmann; Matthew J. Gregory; Heather M. Roberts; Warren B. Cohen; Robert E. Kennedy; Zhiqiang. Yang

2012-01-01

The Northwest Forest Plan (NWFP), which aims to conserve late-successional and old-growth forests (older forests) and associated species, established new policies on federal lands in the Pacific Northwest USA. As part of monitoring for the NWFP, we tested nearest-neighbor imputation for mapping change in older forest, defined by threshold values for forest attributes...

Inference for multivariate regression model based on multiply imputed synthetic data generated via posterior predictive sampling

Science.gov (United States)

Moura, Ricardo; Sinha, Bimal; Coelho, Carlos A.

2017-06-01

The recent popularity of the use of synthetic data as a Statistical Disclosure Control technique has enabled the development of several methods of generating and analyzing such data, but almost always relying in asymptotic distributions and in consequence being not adequate for small sample datasets. Thus, a likelihood-based exact inference procedure is derived for the matrix of regression coefficients of the multivariate regression model, for multiply imputed synthetic data generated via Posterior Predictive Sampling. Since it is based in exact distributions this procedure may even be used in small sample datasets. Simulation studies compare the results obtained from the proposed exact inferential procedure with the results obtained from an adaptation of Reiters combination rule to multiply imputed synthetic datasets and an application to the 2000 Current Population Survey is discussed.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Antônio Dâmaso

2017-11-01

Full Text Available Power consumption is a primary interest in Wireless Sensor Networks (WSNs, and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

Science.gov (United States)

Dâmaso, Antônio; Maciel, Paulo

2017-01-01

Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way. PMID:29113078

The evaluation of operator reliability factors on power reactor

International Nuclear Information System (INIS)

Karlina, Itjeu; Supriatna, Piping; W, Suharyo; Santosa, Kussigit; Darlis; S, Bambang; Y, Sasongko

1999-01-01

The sophisticated technology system was not assured the reliability system itself because it has contained a part of human dependence affected successfully of reactor operation either how work smoothly and safe or failure ac cured and then accident appears promptly. The evaluation of operator reliability factor on ABWR power reactor has been carried out which consist of criterion skill and workload according to NUREG/CR-2254, NUREG/CR-4016 and NUREG-0835 the reactor operation reliability emphasize to the operator are synergic between skill and workload themselves. The employee's skill will affect to the type and level of their tasks. The operator's skill depend on education and experiences, position or responsibility of tasks, physical conditions (age uninvalid of physic/mental

Evaluation of reliability assurance approaches to operational nuclear safety

International Nuclear Information System (INIS)

Mueller, C.J.; Bezella, W.A.

1984-01-01

This report discusses the results of research to evaluate existing and/or recommended safety/reliability assurance activities among nuclear and other high technology industries for potential nuclear industry implementation. Since the Three Mile Island (TMI) accident, there has been increased interest in the use of reliability programs (RP) to assure the performance of nuclear safety systems throughout the plant's lifetime. Recently, several Nuclear Regulatory Commission (NRC) task forces or safety issue review groups have recommended RPs for assuring the continuing safety of nuclear reactor plants. 18 references

A New Method of Reliability Evaluation Based on Wavelet Information Entropy for Equipment Condition Identification

International Nuclear Information System (INIS)

He, Z J; Zhang, X L; Chen, X F

2012-01-01

Aiming at reliability evaluation of condition identification of mechanical equipment, it is necessary to analyze condition monitoring information. A new method of reliability evaluation based on wavelet information entropy extracted from vibration signals of mechanical equipment is proposed. The method is quite different from traditional reliability evaluation models that are dependent on probability statistics analysis of large number sample data. The vibration signals of mechanical equipment were analyzed by means of second generation wavelet package (SGWP). We take relative energy in each frequency band of decomposed signal that equals a percentage of the whole signal energy as probability. Normalized information entropy (IE) is obtained based on the relative energy to describe uncertainty of a system instead of probability. The reliability degree is transformed by the normalized wavelet information entropy. A successful application has been achieved to evaluate the assembled quality reliability for a kind of dismountable disk-drum aero-engine. The reliability degree indicates the assembled quality satisfactorily.

The REPAS approach to the evaluation of passive safety systems reliability

International Nuclear Information System (INIS)

Bianchi, F.; Burgazzi, L.; D'Auria, F.; Ricotti, M.E.

2002-01-01

Scope of this research, carried out by ENEA in collaboration with University of Pisa and Polytechnic of Milano since 1999, is the identification of a methodology allowing the evaluation of the reliability of passive systems as a whole, in a more physical and phenomenal way. The paper describe the study, named REPAS (Reliability Evaluation of Passive Safety systems), carried out by the partners and finalised to the development and validation of such a procedure. The strategy of engagement moves from the consideration that a passive system should be theoretically more reliable than an active one. In fact it does not need any external input or energy to operate and it relies only upon natural physical laws (e.g. gravity, natural circulation, internally stored energy, etc.) and/or 'intelligent' use of the energy inherently available in the system (e.g. chemical reaction, decay heat, etc.). Nevertheless the passive system may fail its mission not only as a consequence of classical mechanical failure of components, but also for deviation from the expected behaviour, due to physical phenomena mainly related to thermal-hydraulics or due to different boundary and initial conditions. The main sources of physical failure are identified and a probability of occurrence is assigned. The reliability analysis is performed on a passive system which operates in two-phase, natural circulation. The selected system is a loop including a heat source and a heat sink where the condensation occurs. The system behaviour under different configurations has been simulated via best-estimate code (Relap5 mod3.2). The results are shown and can be treated in such a way to give qualitative and quantitative information on the system reliability. Main routes of development of the methodology are also depicted. The analysis of the results shows that the procedure is suitable to evaluate the performance of a passive system on a probabilistic / deterministic basis. Important information can also be

Evaluation and improvement in nondestructive examination (NDE) reliability for in-service inspection of light water reactors

International Nuclear Information System (INIS)

Deffenbaugh, J.D.; Good, M.S.; Green, E.R.; Heasler, P.G.; Simonen, F.A.; Spanner, J.C.; Taylor, T.T.

1988-01-01

The evaluation and improvement of NDE Reliability for In-service Inspection (ISI) of Light Water Reactors (NDE Reliability) Program at Pacific Northwest Laboratory (PNL) was established to determine the reliability of current ISI techniques and to develop recommendations that will ensure a suitably high inspection reliability. The objectives of this NRC program are to: determine the reliability of ultrasonic ISI performed on commercial light-water reactor (LWR) primary systems; determine the impact of NDE unreliability on system safety and determine the level of inspection reliability required to ensure a suitably low failure probability using probabilistic fracture mechanics analysis; evaluate the degree of reliability improvement that could be achieved using improved and advanced NDE technique; and recommend revisions to ASME Code, Section XI, and Regulatory Requirements, based on material properties, service conditions, and NDE uncertainties, that will ensure suitably low failure probabilities. The program consists of three basic tasks: a Piping task, a Pressure Vessel task, and an Evaluation and Improvement in NDE Reliability task. The major efforts were concentrated in the Piping task and the Evaluation and Improvement in NDE Reliability task

Evaluation of Reliability Parameters in Micro-grid

Directory of Open Access Journals (Sweden)

H. Hasanzadeh Fard

2015-06-01

Full Text Available Evaluation of the reliability parameters in micro-grids based on renewable energy sources is one of the main problems that are investigated in this paper. Renewable energy sources such as solar and wind energy, battery as an energy storage system and fuel cell as a backup system are used to provide power to the electrical loads of the micro-grid. Loads in the micro-grid consist of interruptible and uninterruptible loads. In addition to the reliability parameters, Forced Outage Rate of each component and also uncertainty of wind power, PV power and demand are considered for micro-grid. In this paper, the problem is formulated as a nonlinear integer minimization problem which minimizes the sum of the total capital, operational, maintenance and replacement cost of DERs. This paper proposes PSO for solving this minimization problem.

Multiple imputation to account for measurement error in marginal structural models

Science.gov (United States)

Edwards, Jessie K.; Cole, Stephen R.; Westreich, Daniel; Crane, Heidi; Eron, Joseph J.; Mathews, W. Christopher; Moore, Richard; Boswell, Stephen L.; Lesko, Catherine R.; Mugavero, Michael J.

2015-01-01

Background Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and non-differential measurement error in a marginal structural model. Methods We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. Results In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality [hazard ratio (HR): 1.2 (95% CI: 0.6, 2.3)]. The HR for current smoking and therapy (0.4 (95% CI: 0.2, 0.7)) was similar to the HR for no smoking and therapy (0.4; 95% CI: 0.2, 0.6). Conclusions Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies. PMID:26214338

Multiple Imputation to Account for Measurement Error in Marginal Structural Models.

Science.gov (United States)

Edwards, Jessie K; Cole, Stephen R; Westreich, Daniel; Crane, Heidi; Eron, Joseph J; Mathews, W Christopher; Moore, Richard; Boswell, Stephen L; Lesko, Catherine R; Mugavero, Michael J

2015-09-01

Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and nondifferential measurement error in a marginal structural model. We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3,686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality (hazard ratio [HR]: 1.2 [95% confidence interval [CI] = 0.6, 2.3]). The HR for current smoking and therapy [0.4 (95% CI = 0.2, 0.7)] was similar to the HR for no smoking and therapy (0.4; 95% CI = 0.2, 0.6). Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies.

Reliability Evaluation of Distribution System Considering Sequential Characteristics of Distributed Generation

Directory of Open Access Journals (Sweden)

Sheng Wanxing

2016-01-01

Full Text Available In allusion to the randomness of output power of distributed generation (DG, a reliability evaluation model based on sequential Monte Carlo simulation (SMCS for distribution system with DG is proposed. Operating states of the distribution system can be sampled by SMCS in chronological order thus the corresponding output power of DG can be generated. The proposed method has been tested on feeder F4 of IEEE-RBTS Bus 6. The results show that reliability evaluation of distribution system considering the uncertainty of output power of DG can be effectively implemented by SMCS.

Evaluation of research reactor fuel reliability in support of regulatory requirements

International Nuclear Information System (INIS)

Sokolov, Eugene N.

2005-01-01

This standards, codes and practices survey is devoted to the problem of reliability of R and D especially research reactor fuel (RRF) performance-related processes. Regulatory R and D evaluations were based on one standard and just few of them provide correlation to other relative standards whereas synthetic process approach reflects actual status of particular R and D practices. Fuel performance regulatory parameters are based on quality standards. A reliability process-based method similar to PSA/FMEA is proposed to evaluate RRF performance- related parameters in terms of reactor safety. (author)

Evaluation of research reactor fuel reliability in support of regulatory requirements

Energy Technology Data Exchange (ETDEWEB)

Sokolov, Eugene N [Chalk River Laboratories, AECL, Chalk River, ON, K0J 1J0 (Canada)

2005-07-01

This standards, codes and practices survey is devoted to the problem of reliability of R and D especially research reactor fuel (RRF) performance-related processes. Regulatory R and D evaluations were based on one standard and just few of them provide correlation to other relative standards whereas synthetic process approach reflects actual status of particular R and D practices. Fuel performance regulatory parameters are based on quality standards. A reliability process-based method similar to PSA/FMEA is proposed to evaluate RRF performance- related parameters in terms of reactor safety. (author)

Estimation of Tree Lists from Airborne Laser Scanning Using Tree Model Clustering and k-MSN Imputation

Directory of Open Access Journals (Sweden)

Jörgen Wallerman

2013-04-01

Full Text Available Individual tree crowns may be delineated from airborne laser scanning (ALS data by segmentation of surface models or by 3D analysis. Segmentation of surface models benefits from using a priori knowledge about the proportions of tree crowns, which has not yet been utilized for 3D analysis to any great extent. In this study, an existing surface segmentation method was used as a basis for a new tree model 3D clustering method applied to ALS returns in 104 circular field plots with 12 m radius in pine-dominated boreal forest (64°14'N, 19°50'E. For each cluster below the tallest canopy layer, a parabolic surface was fitted to model a tree crown. The tree model clustering identified more trees than segmentation of the surface model, especially smaller trees below the tallest canopy layer. Stem attributes were estimated with k-Most Similar Neighbours (k-MSN imputation of the clusters based on field-measured trees. The accuracy at plot level from the k-MSN imputation (stem density root mean square error or RMSE 32.7%; stem volume RMSE 28.3% was similar to the corresponding results from the surface model (stem density RMSE 33.6%; stem volume RMSE 26.1% with leave-one-out cross-validation for one field plot at a time. Three-dimensional analysis of ALS data should also be evaluated in multi-layered forests since it identified a larger number of small trees below the tallest canopy layer.

thermal power stations' reliability evaluation in a hydrothermal system

African Journals Online (AJOL)

Dr Obe

A quantitative tool for the evaluation of thermal power stations reliability in a hydrothermal system is presented. ... (solar power); wind (wind power) and the rest, thermal power and ... probability of a system performing its function adequately for ...

Environmental education curriculum evaluation questionnaire: A reliability and validity study

Science.gov (United States)

Minner, Daphne Diane

The intention of this research project was to bridge the gap between social science research and application to the environmental domain through the development of a theoretically derived instrument designed to give educators a template by which to evaluate environmental education curricula. The theoretical base for instrument development was provided by several developmental theories such as Piaget's theory of cognitive development, Developmental Systems Theory, Life-span Perspective, as well as curriculum research within the area of environmental education. This theoretical base fueled the generation of a list of components which were then translated into a questionnaire with specific questions relevant to the environmental education domain. The specific research question for this project is: Can a valid assessment instrument based largely on human development and education theory be developed that reliably discriminates high, moderate, and low quality in environmental education curricula? The types of analyses conducted to answer this question were interrater reliability (percent agreement, Cohen's Kappa coefficient, Pearson's Product-Moment correlation coefficient), test-retest reliability (percent agreement, correlation), and criterion-related validity (correlation). Face validity and content validity were also assessed through thorough reviews. Overall results indicate that 29% of the questions on the questionnaire demonstrated a high level of interrater reliability and 43% of the questions demonstrated a moderate level of interrater reliability. Seventy-one percent of the questions demonstrated a high test-retest reliability and 5% a moderate level. Fifty-five percent of the questions on the questionnaire were reliable (high or moderate) both across time and raters. Only eight questions (8%) did not show either interrater or test-retest reliability. The global overall rating of high, medium, or low quality was reliable across both coders and time, indicating

Reliability Evaluation for the Surface to Air Missile Weapon Based on Cloud Model

Directory of Open Access Journals (Sweden)

Deng Jianjun

2015-01-01

Full Text Available The fuzziness and randomness is integrated by using digital characteristics, such as Expected value, Entropy and Hyper entropy. The cloud model adapted to reliability evaluation is put forward based on the concept of the surface to air missile weapon. The cloud scale of the qualitative evaluation is constructed, and the quantitative variable and the qualitative variable in the system reliability evaluation are corresponded. The practical calculation result shows that it is more effective to analyze the reliability of the surface to air missile weapon by this way. The practical calculation result also reflects the model expressed by cloud theory is more consistent with the human thinking style of uncertainty.

A Note on the Effect of Data Clustering on the Multiple-Imputation Variance Estimator: A Theoretical Addendum to the Lewis et al. article in JOS 2014

Directory of Open Access Journals (Sweden)

He Yulei

2016-03-01

Full Text Available Multiple imputation is a popular approach to handling missing data. Although it was originally motivated by survey nonresponse problems, it has been readily applied to other data settings. However, its general behavior still remains unclear when applied to survey data with complex sample designs, including clustering. Recently, Lewis et al. (2014 compared single- and multiple-imputation analyses for certain incomplete variables in the 2008 National Ambulatory Medicare Care Survey, which has a nationally representative, multistage, and clustered sampling design. Their study results suggested that the increase of the variance estimate due to multiple imputation compared with single imputation largely disappears for estimates with large design effects. We complement their empirical research by providing some theoretical reasoning. We consider data sampled from an equally weighted, single-stage cluster design and characterize the process using a balanced, one-way normal random-effects model. Assuming that the missingness is completely at random, we derive analytic expressions for the within- and between-multiple-imputation variance estimators for the mean estimator, and thus conveniently reveal the impact of design effects on these variance estimators. We propose approximations for the fraction of missing information in clustered samples, extending previous results for simple random samples. We discuss some generalizations of this research and its practical implications for data release by statistical agencies.

Reliability of early radiographic evaluations for canine hip dysplasia obtained from the standard ventrodorsal radiographic projection

International Nuclear Information System (INIS)

Corley, E.A.; Keller, G.G.; Lattimer, J.C.; Ellersieck, M.R.

1997-01-01

To determine reliability of preliminary evaluations for canine hip dysplasia (CHD) performed by the Orthopedic Foundation for Animals on dogs between 3 and 18 months of age. Retrospective analysis of data from the Orthopedic Foundation for Animals database. 2,332 Golden Retrievers, Labrador Retrievers, German Shepherd Dogs, and Rottweilers for which preliminary evaluation had been performed between 3 and 18 months of age and for which results of a definitive evaluation performed after 24 months of age were available. Each radiograph was evaluated, and hip joint status was graded as excellent, good, fair, or borderline phenotype or mild, moderate, or severe dysplasia. Preliminary evaluations were performed by 1 radiologist; definitive evaluations were the consensus of 3 radiologists. Reliability of preliminary evaluations was calculated as the percentage of definitive evaluations (normal vs dysplastic) that were unchanged from preliminary evaluations. Reliability of a preliminary evaluation of normal hip joint phenotype decreased significantly as the preliminary evaluation changed from excellent (100%) to good (97.9%) to fair (76.9%) phenotype. Reliability of a preliminary evaluation of CHD increased significantly as the preliminary evaluation changed from mild (84.4%) to moderate (97.4%) CHD. Reliability of preliminary evaluations increased significantly as age at the time of preliminary evaluation increased, regardless of whether dogs received a preliminary evaluation of normal phenotype or CHD. Results suggest that preliminary evaluations of hip joint status in dogs are generally reliable. However, dogs that receive a preliminary evaluation of fair phenotype of mild CHD should be reevaluated after 24 months of age

Advancing Usability Evaluation through Human Reliability Analysis

International Nuclear Information System (INIS)

Ronald L. Boring; David I. Gertman

2005-01-01

This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probability of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues

evaluation of willingness to pay for reliable and sustainable ...

African Journals Online (AJOL)

Osondu

evaluate the WTP for reliable and sustainable service delivery. The findings of the study .... In doing this, the revenue base and cost recovery will as well be enhanced in ..... delays at traffic warden controlled urban intersections: case study of ...

Reliability Evaluation of Power Capacitors in a Wind Turbine System

DEFF Research Database (Denmark)

Zhou, Dao; Blaabjerg, Frede

2018-01-01

With the increasing penetration of wind power, reliable and cost-effective wind energy production is of more and more importance. The doubly-fed induction generator based partial-scale wind power converter is still dominating in the existing wind farms. In this paper, the reliability assessment...... block diagram is used to bridge the gap between the Weibull distribution based component-level individual capacitor and the capacitor bank. A case study of a 2 MW wind power converter shows that the lifetime is significantly reduced from the individual capacitor to the capacitor bank. Besides, the dc...... of power capacitors is studied considering the annual mission profile. According to an electro-thermal stress evaluation, the time-to-failure distribution of both the dc-link capacitor and ac-side filter capacitor is detailed investigated. Aiming for the systemlevel reliability analysis, a reliability...

Monte Carlo simulation based reliability evaluation in a multi-bilateral contracts market

International Nuclear Information System (INIS)

Goel, L.; Viswanath, P.A.; Wang, P.

2004-01-01

This paper presents a time sequential Monte Carlo simulation technique to evaluate customer load point reliability in multi-bilateral contracts market. The effects of bilateral transactions, reserve agreements, and the priority commitments of generating companies on customer load point reliability have been investigated. A generating company with bilateral contracts is modelled as an equivalent time varying multi-state generation (ETMG). A procedure to determine load point reliability based on ETMG has been developed. The developed procedure is applied to a reliability test system to illustrate the technique. Representing each bilateral contract by an ETMG provides flexibility in determining the reliability at various customer load points. (authors)

Inter-rater reliability of the Sødring Motor Evaluation of Stroke patients (SMES).

Science.gov (United States)

Halsaa, K E; Sødring, K M; Bjelland, E; Finsrud, K; Bautz-Holter, E

1999-12-01

The Sødring Motor Evaluation of Stroke patients is an instrument for physiotherapists to evaluate motor function and activities in stroke patients. The rating reflects quality as well as quantity of the patient's unassisted performance within three domains: leg, arm and gross function. The inter-rater reliability of the method was studied in a sample of 30 patients admitted to a stroke rehabilitation unit. Three therapists were involved in the study; two therapists assessed the same patient on two consecutive days in a balanced design. Cohen's weighted kappa and McNemar's test of symmetry were used as measures of item reliability, and the intraclass correlation coefficient was used to express the reliability of the sumscores. For 24 out of 32 items the weighted kappa statistic was excellent (0.75-0.98), while 7 items had a kappa statistic within the range 0.53-0.74 (fair to good). The reliability of one item was poor (0.13). The intraclass correlation coefficient for the three sumscores was 0.97, 0.91 and 0.97. We conclude that the Sødring Motor Evaluation of Stroke patients is a reliable measure of motor function in stroke patients undergoing rehabilitation.

Reliability evaluation of nuclear power plants by fault tree analysis

International Nuclear Information System (INIS)

Iwao, H.; Otsuka, T.; Fujita, I.

1993-01-01

As a work sponsored by the Ministry of International Trade and Industry, the Safety Information Research Center of NUPEC, using reliability data based on the operational experience of the domestic LWR Plants, has implemented FTA for the standard PWRs and BWRs in Japan with reactor scram due to system failures being at the top event. Up to this point, we have obtained the FT chart and minimal cut set for each type of system failure for qualitative evaluation, and we have estimated system unavailability, Fussell-Vesely importance and risk worth for components for quantitative evaluation. As the second stage of a series in our reliability evaluation work, another program was started to establish a support system. The aim of this system is to assist foreign and domestic plants in creating countermeasures when incidents occur, by providing them with the necessary information using the above analytical method and its results. (author)

Use of reliability data for QA program evaluation

International Nuclear Information System (INIS)

Guarro, S.B.

1985-01-01

Possible analytical approaches for evaluation of the effectiveness in the operation of US commercial nuclear power plants are discussed. These approaches may be based on key plant component performance comparisons, correlation models, or comprehensive cost-benefit evaluation frameworks. As plant availability and reliability data must be used to quantify the models, the quality of these data conditions the amount of information that can ultimately be extracted. The potential impact of uncertainties in the data must be considered carefully, especially before application of the more complex models. 10 refs., 4 tabs

A human reliability based usability evaluation method for safety-critical software

International Nuclear Information System (INIS)

Boring, R. L.; Tran, T. Q.; Gertman, D. I.; Ragsdale, A.

2006-01-01

Boring and Gertman (2005) introduced a novel method that augments heuristic usability evaluation methods with that of the human reliability analysis method of SPAR-H. By assigning probabilistic modifiers to individual heuristics, it is possible to arrive at the usability error probability (UEP). Although this UEP is not a literal probability of error, it nonetheless provides a quantitative basis to heuristic evaluation. This method allows one to seamlessly prioritize and identify usability issues (i.e., a higher UEP requires more immediate fixes). However, the original version of this method required the usability evaluator to assign priority weights to the final UEP, thus allowing the priority of a usability issue to differ among usability evaluators. The purpose of this paper is to explore an alternative approach to standardize the priority weighting of the UEP in an effort to improve the method's reliability. (authors)

Determination of reliability of express forecasting evaluation of radiometric enriching ability of non-ferrous ores

International Nuclear Information System (INIS)

Kirpishchikov, S.P.

1991-01-01

Use of the data of nuclear physical methods of sampling and logging enables to improve reliability of evaluation of radiometric enriching ability of ores, as well as to evaluate quantitatively this reliability. This problem may be solved by using some concepts of geostatistics. The presented results enable to conclude, that the data of nuclear-physical methods of sampling and logging can provide high reliability of evaluation of radiometric enriching ability of non-ferrous ores and their geometrization by technological types

Interim reliability evaluation program (IREP)

International Nuclear Information System (INIS)

Carlson, D.D.; Murphy, J.A.

1981-01-01

The Interim Reliability Evaluation Program (IREP), sponsored by the Office of Nuclear Regulatory Research of the US Nuclear Regulatory Commission, is currently applying probabilistic risk analysis techniques to two PWR and two BWR type power plants. Emphasis was placed on the systems analysis portion of the risk assessment, as opposed to accident phenomenology or consequence analysis, since the identification of risk significant plant features was of primary interest. Traditional event tree/fault tree modeling was used for the analysis. However, the study involved a more thorough investigation of transient initiators and of support system faults than studies in the past and substantially improved techniques were used to quantify accident sequence frequencies. This study also attempted to quantify the potential for operator recovery actions in the course of each significant accident

Reliability Evaluation of Service-Oriented Architecture Systems Considering Fault-Tolerance Designs

Directory of Open Access Journals (Sweden)

Kuan-Li Peng

2014-01-01

strategies. Sensitivity analysis of SOA at both coarse and fine grain levels is also studied, which can be used to efficiently identify the critical parts within the system. Two SOA system scenarios based on real industrial practices are studied. Experimental results show that the proposed SOA model can be used to accurately depict the behavior of SOA systems. Additionally, a sensitivity analysis that quantizes the effects of system structure as well as fault tolerance on the overall reliability is also studied. On the whole, the proposed reliability modeling and analysis framework may help the SOA system service provider to evaluate the overall system reliability effectively and also make smarter improvement plans by focusing resources on enhancing reliability-sensitive parts within the system.

Is missing geographic positioning system data in accelerometry studies a problem, and is imputation the solution?

DEFF Research Database (Denmark)

Meseck, Kristin; Jankowska, Marta M; Schipperijn, Jasper

2016-01-01

The main purpose of the present study was to assess the impact of global positioning system (GPS) signal lapse on physical activity analyses, discover any existing associations between missing GPS data and environmental and demographics attributes, and to determine whether imputation is an accurate...

Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

NARCIS (Netherlands)

van Leeuwen, E.M.; Karssen, L.C.; Deelen, J.; Isaacs, A.; Medina-Gomez, C.; Mbarek, H.; Kanterakis, A.; Trompet, S.; Postmus, I.; Verweij, N.; van Enckevort, D.; Huffman, J.E.; White, C.C.; Feitosa, M.F.; Bartz, T.M.; Manichaikul, A.; Joshi, P.K.; Peloso, G.M.; Deelen, P.; Dijk, F.; Willemsen, G.; de Geus, E.J.C.; Milaneschi, Y.; Penninx, B.W.J.H.; Francioli, L.C.; Menelaou, A.; Pulit, S.L.; Rivadeneira, F.; Hofman, A.; Oostra, B.A.; Franco, O.H.; Mateo Leach, I.; Beekman, M.; de Craen, A.J.; Uh, H.W.; Trochet, H.; Hocking, L.J.; Porteous, D.J.; Sattar, N.; Packard, C.J.; Buckley, B.M.; Brody, J.A.; Bis, J.C.; Rotter, J.I.; Mychaleckyj, J.C.; Campbell, H.; Duan, Q.; Lange, L.A.; Wilson, J.F.; Hayward, C.; Polasek, O.; Vitart, V.; Rudan, I.; Wright, A.F.; Rich, S.S.; Psaty, B.M.; Borecki, I.B.; Kearney, P.M.; Stott, D.J.; Cupples, L.A.; Jukema, J.W.; van der Harst, P.; Sijbrands, E.J.; Hottenga, J.J.; Uitterlinden, A.G.; Swertz, M.A.; van Ommen, G.J.B; Bakker, P.I.W.; Slagboom, P.E.; Boomsma, D.I.; Wijmenga, C.; van Duijn, C.M.

2015-01-01

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (∼35,000 samples) with the population-specific reference panel created

RELIABILITY OF CERTAIN TESTS FOR EVALUATION OF JUDO TECHNIQUES

Directory of Open Access Journals (Sweden)

Slavko Obadov

2007-05-01

Full Text Available The sample included 106 judokas. Assessment of the level of mastership of judo techniques was carried out by evaluation of fi ve competent studies. Each subject performed a technique three times and each performance was evaluated by the judges. In order to evaluate measurement of each technique, Cronbach’s coeffi cient of reliability  was calculated. During the procedure the subjects's results were also transformed to factor scores i.e. the results of each performer at the main component of evaluation in the fi ve studies. These factor scores could be used in the subsequent procedure of multivariant statistical analysis.

Interim Reliability Evaluation Program procedures guide

International Nuclear Information System (INIS)

Carlson, D.D.; Gallup, D.R.; Kolaczkowski, A.M.; Kolb, G.J.; Stack, D.W.; Lofgren, E.; Horton, W.H.; Lobner, P.R.

1983-01-01

This document presents procedures for conducting analyses of a scope similar to those performed in Phase II of the Interim Reliability Evaluation Program (IREP). It documents the current state of the art in performing the plant systems analysis portion of a probabilistic risk assessment. Insights gained into managing such an analysis are discussed. Step-by-step procedures and methodological guidance constitute the major portion of the document. While not to be viewed as a cookbook, the procedures set forth the principal steps in performing an IREP analysis. Guidance for resolving the problems encountered in previous analyses is offered. Numerous examples and representative products from previous analyses clarify the discussion

Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel

NARCIS (Netherlands)

J. Huang (Jie); B. Howie (Bryan); S. McCarthy (Shane); Y. Memari (Yasin); K. Walter (Klaudia); J.L. Min (Josine L.); P. Danecek (Petr); G. Malerba (Giovanni); E. Trabetti (Elisabetta); H.-F. Zheng (Hou-Feng); G. Gambaro (Giovanni); J.B. Richards (Brent); R. Durbin (Richard); N.J. Timpson (Nicholas); J. Marchini (Jonathan); N. Soranzo (Nicole); S.H. Al Turki (Saeed); A. Amuzu (Antoinette); C. Anderson (Carl); R. Anney (Richard); D. Antony (Dinu); M.S. Artigas; M. Ayub (Muhammad); S. Bala (Senduran); J.C. Barrett (Jeffrey); I.E. Barroso (Inês); P.L. Beales (Philip); M. Benn (Marianne); J. Bentham (Jamie); S. Bhattacharya (Shoumo); E. Birney (Ewan); D.H.R. Blackwood (Douglas); M. Bobrow (Martin); E. Bochukova (Elena); P.F. Bolton (Patrick F.); R. Bounds (Rebecca); C. Boustred (Chris); G. Breen (Gerome); M. Calissano (Mattia); K. Carss (Keren); J.P. Casas (Juan Pablo); J.C. Chambers (John C.); R. Charlton (Ruth); K. Chatterjee (Krishna); L. Chen (Lu); A. Ciampi (Antonio); S. Cirak (Sebahattin); P. Clapham (Peter); G. Clement (Gail); G. Coates (Guy); M. Cocca (Massimiliano); D.A. Collier (David); C. Cosgrove (Catherine); T. Cox (Tony); N.J. Craddock (Nick); L. Crooks (Lucy); S. Curran (Sarah); D. Curtis (David); A. Daly (Allan); I.N.M. Day (Ian N.M.); A.G. Day-Williams (Aaron); G.V. Dedoussis (George); T. Down (Thomas); Y. Du (Yuanping); C.M. van Duijn (Cornelia); I. Dunham (Ian); T. Edkins (Ted); R. Ekong (Rosemary); P. Ellis (Peter); D.M. Evans (David); I.S. Farooqi (I. Sadaf); D.R. Fitzpatrick (David R.); P. Flicek (Paul); J. Floyd (James); A.R. Foley (A. Reghan); C.S. Franklin (Christopher S.); M. Futema (Marta); L. Gallagher (Louise); P. Gasparini (Paolo); T.R. Gaunt (Tom); M. Geihs (Matthias); D. Geschwind (Daniel); C.M.T. Greenwood (Celia); H. Griffin (Heather); D. Grozeva (Detelina); X. Guo (Xiaosen); X. Guo (Xueqin); H. Gurling (Hugh); D. Hart (Deborah); A.E. Hendricks (Audrey E.); P.A. Holmans (Peter A.); L. Huang (Liren); T. Hubbard (Tim); S.E. Humphries (Steve E.); M.E. Hurles (Matthew); P.G. Hysi (Pirro); V. Iotchkova (Valentina); A. Isaacs (Aaron); D.K. Jackson (David K.); Y. Jamshidi (Yalda); J. Johnson (Jon); C. Joyce (Chris); K.J. Karczewski (Konrad); J. Kaye (Jane); T. Keane (Thomas); J.P. Kemp (John); K. Kennedy (Karen); A. Kent (Alastair); J. Keogh (Julia); F. Khawaja (Farrah); M.E. Kleber (Marcus); M. Van Kogelenberg (Margriet); A. Kolb-Kokocinski (Anja); J.S. Kooner (Jaspal S.); G. Lachance (Genevieve); C. Langenberg (Claudia); C. Langford (Cordelia); D. Lawson (Daniel); I. Lee (Irene); E.M. van Leeuwen (Elisa); M. Lek (Monkol); R. Li (Rui); Y. Li (Yingrui); J. Liang (Jieqin); H. Lin (Hong); R. Liu (Ryan); J. Lönnqvist (Jouko); L.R. Lopes (Luis R.); M.C. Lopes (Margarida); J. Luan; D.G. MacArthur (Daniel G.); M. Mangino (Massimo); G. Marenne (Gaëlle); W. März (Winfried); J. Maslen (John); A. Matchan (Angela); I. Mathieson (Iain); P. McGuffin (Peter); A.M. McIntosh (Andrew); A.G. McKechanie (Andrew G.); A. McQuillin (Andrew); S. Metrustry (Sarah); N. Migone (Nicola); H.M. Mitchison (Hannah M.); A. Moayyeri (Alireza); J. Morris (James); R. Morris (Richard); D. Muddyman (Dawn); F. Muntoni; B.G. Nordestgaard (Børge G.); K. Northstone (Kate); M.C. O'donovan (Michael); S. O'Rahilly (Stephen); A. Onoufriadis (Alexandros); K. Oualkacha (Karim); M.J. Owen (Michael J.); A. Palotie (Aarno); K. Panoutsopoulou (Kalliope); V. Parker (Victoria); J.R. Parr (Jeremy R.); L. Paternoster (Lavinia); T. Paunio (Tiina); F. Payne (Felicity); S.J. Payne (Stewart J.); J.R.B. Perry (John); O.P.H. Pietiläinen (Olli); V. Plagnol (Vincent); R.C. Pollitt (Rebecca C.); S. Povey (Sue); M.A. Quail (Michael A.); L. Quaye (Lydia); L. Raymond (Lucy); K. Rehnström (Karola); C.K. Ridout (Cheryl K.); S.M. Ring (Susan); G.R.S. Ritchie (Graham R.S.); N. Roberts (Nicola); R.L. Robinson (Rachel L.); D.B. Savage (David); P.J. Scambler (Peter); S. Schiffels (Stephan); M. Schmidts (Miriam); N. Schoenmakers (Nadia); R.H. Scott (Richard H.); R.A. Scott (Robert); R.K. Semple (Robert K.); E. Serra (Eva); S.I. Sharp (Sally I.); A.C. Shaw (Adam C.); H.A. Shihab (Hashem A.); S.-Y. Shin (So-Youn); D. Skuse (David); K.S. Small (Kerrin); C. Smee (Carol); G.D. Smith; L. Southam (Lorraine); O. Spasic-Boskovic (Olivera); T.D. Spector (Timothy); D. St. Clair (David); B. St Pourcain (Beate); J. Stalker (Jim); E. Stevens (Elizabeth); J. Sun (Jianping); G. Surdulescu (Gabriela); J. Suvisaari (Jaana); P. Syrris (Petros); I. Tachmazidou (Ioanna); R. Taylor (Rohan); J. Tian (Jing); M.D. Tobin (Martin); D. Toniolo (Daniela); M. Traglia (Michela); A. Tybjaerg-Hansen; A.M. Valdes; A.M. Vandersteen (Anthony M.); A. Varbo (Anette); P. Vijayarangakannan (Parthiban); P.M. Visscher (Peter); L.V. Wain (Louise); J.T. Walters (James); G. Wang (Guangbiao); J. Wang (Jun); Y. Wang (Yu); K. Ward (Kirsten); E. Wheeler (Eleanor); P.H. Whincup (Peter); T. Whyte (Tamieka); H.J. Williams (Hywel J.); K.A. Williamson (Kathleen); C. Wilson (Crispian); S.G. Wilson (Scott); K. Wong (Kim); C. Xu (Changjiang); J. Yang (Jian); G. Zaza (Gianluigi); E. Zeggini (Eleftheria); F. Zhang (Feng); P. Zhang (Pingbo); W. Zhang (Weihua)

2015-01-01

textabstractImputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced

Students' Evaluation Strategies in a Web Research Task: Are They Sensitive to Relevance and Reliability?

Science.gov (United States)

Rodicio, Héctor García

2015-01-01

When searching and using resources on the Web, students have to evaluate Web pages in terms of relevance and reliability. This evaluation can be done in a more or less systematic way, by either considering deep or superficial cues of relevance and reliability. The goal of this study was to examine how systematic students are when evaluating Web…

JUPITER PROJECT - JOINT UNIVERSAL PARAMETER IDENTIFICATION AND EVALUATION OF RELIABILITY

Science.gov (United States)

The JUPITER (Joint Universal Parameter IdenTification and Evaluation of Reliability) project builds on the technology of two widely used codes for sensitivity analysis, data assessment, calibration, and uncertainty analysis of environmental models: PEST and UCODE.

Development of Tsunami Trace Database with reliability evaluation on Japan coasts

International Nuclear Information System (INIS)

Iwabuchi, Yoko; Sugino, Hideharu; Imamura, Fumihiko; Imai, Kentaro; Tsuji, Yoshinobu; Matsuoka, Yuya; Shuto, Nobuo

2012-01-01

The purpose of this research is to develop a Tsunami Trace Database by collecting historical materials as well as documents concerning tsunamis which had hit Japan and, of which the reliability of tsunami run-up and related data is taken into account. Based on acquisition and surveying of references, tsunami trace data over past 400 years of Japan has collected into a database, and reliability of each trace data was evaluated according to categorization of Japan Society of Civil Engineers (2002). As a result, trace data can now be searched and filtered with reliability levels accordingly whilst utilizing it for verification of tsunami numerical analysis and estimation of tsunami sources. By analyzing this database, we have quantitatively revealed the fact that the amount of reliable data tends to diminish as it goes older. (author)

Imputation of Baseline LDL Cholesterol Concentration in Patients with Familial Hypercholesterolemia on Statins or Ezetimibe.

Science.gov (United States)

Ruel, Isabelle; Aljenedil, Sumayah; Sadri, Iman; de Varennes, Émilie; Hegele, Robert A; Couture, Patrick; Bergeron, Jean; Wanneh, Eric; Baass, Alexis; Dufour, Robert; Gaudet, Daniel; Brisson, Diane; Brunham, Liam R; Francis, Gordon A; Cermakova, Lubomira; Brophy, James M; Ryomoto, Arnold; Mancini, G B John; Genest, Jacques

2018-02-01

Familial hypercholesterolemia (FH) is the most frequent genetic disorder seen clinically and is characterized by increased LDL cholesterol (LDL-C) (>95th percentile), family history of increased LDL-C, premature atherosclerotic cardiovascular disease (ASCVD) in the patient or in first-degree relatives, presence of tendinous xanthomas or premature corneal arcus, or presence of a pathogenic mutation in the LDLR , PCSK9 , or APOB genes. A diagnosis of FH has important clinical implications with respect to lifelong risk of ASCVD and requirement for intensive pharmacological therapy. The concentration of baseline LDL-C (untreated) is essential for the diagnosis of FH but is often not available because the individual is already on statin therapy. To validate a new algorithm to impute baseline LDL-C, we examined 1297 patients. The baseline LDL-C was compared with the imputed baseline obtained within 18 months of the initiation of therapy. We compared the percent reduction in LDL-C on treatment from baseline with the published percent reductions. After eliminating individuals with missing data, nonstandard doses of statins, or medications other than statins or ezetimibe, we provide data on 951 patients. The mean ± SE baseline LDL-C was 243.0 (2.2) mg/dL [6.28 (0.06) mmol/L], and the mean ± SE imputed baseline LDL-C was 244.2 (2.6) mg/dL [6.31 (0.07) mmol/L] ( P = 0.48). There was no difference in response according to the patient's sex or in percent reduction between observed and expected for individual doses or types of statin or ezetimibe. We provide a validated estimation of baseline LDL-C for patients with FH that may help clinicians in making a diagnosis. © 2017 American Association for Clinical Chemistry.

A Standardized Rubric for Evaluating Webquest Design: Reliability Analysis of ZUNAL Webquest Design Rubric

Science.gov (United States)

Unal, Zafer; Bodur, Yasar; Unal, Aslihan

2012-01-01

Current literature provides many examples of rubrics that are used to evaluate the quality of web-quest designs. However, reliability of these rubrics has not yet been researched. This is the first study to fully characterize and assess the reliability of a webquest evaluation rubric. The ZUNAL rubric was created to utilize the strengths of the…

Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel

DEFF Research Database (Denmark)

Huang, Jie; Howie, Bryan; Mccarthy, Shane

2015-01-01

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low de...

Reliability evaluation of a port oil transportation system in variable operation conditions

International Nuclear Information System (INIS)

Soszynska, Joanna

2006-01-01

The semi-Markov model of the system operation processes is proposed and its selected parameters are determined. The series 'm out of k n ' multi-state system is considered and its reliability and risk characteristics are found. Next, the joint model of the system operation process and the system multi-state reliability and risk is constructed. Moreover, reliability and risk evaluation of the multi-state series 'm out of k n ' system in its operation process is applied to the port oil transportation system

Sensitivity evaluation of human factors for reliability of the containment spray system

International Nuclear Information System (INIS)

Tsujimura, Yasuhiro; Suzuki, Eiji

1988-01-01

Evaluation of the human reliability is one of the most difficult problems that deal with the safety and reliability of large systems, especially of the Engineered Safety Features (ESF) of the nuclear power plant. Influences of human factors on the reliability of the Containment Spray System in the ESF were estimated by using the FTA method in this paper. As a result, the adequacy of the system structure and the effects of human factors on variations of the design of the system structure were explained. (author)

Efficiency evaluation of an electronic equipment: availability,reliability and maintenance

International Nuclear Information System (INIS)

Guyot, C.

1966-01-01

This concept of efficiency often called ''system effectiveness'', is presented and analyzed in terms of reliability and maintenance. It allows to define the availability factor of an electronic equipment. A procedure of evaluation is proposed. (A.L.B.)

The new features of the ExaMe evaluation system and reliability of its fixed tests.

Science.gov (United States)

Martinková, P; Zvára, K; Zvárová, J; Zvára, K

2006-01-01

The ExaMe system for the evaluation of targeted knowledge has been in development since 1998. The new features of the ExaMe system are introduced in this paper. Especially, the new three-layer architecture is described. Besides the system itself, the properties of fixed tests in the ExaMe system are studied. In special detail, the reliability of the fixed tests is discussed. The theory background is explained and some limitations of the reliability are pointed out. Three characteristics used for estimation of reliability of educational tests are discussed: Cronbach's alpha, standardized item alpha and split half coefficient. The relation between these characteristics and reliability and between characteristics themselves is investigated. In more detail, the properties of Cronbach's alpha, the characteristics mostly used for the estimation of reliability, are discussed. A confidence interval is introduced for the characteristics. Since 2000, the serviceability of the ExaMe evaluation system as the supporting evaluation tool has been repeatedly shown at the courses of Ph.D. studies in biomedical informatics at Charles University in Prague. The ExaMe system also opens new possibilities for self-evaluation and distance learning, especially when connected with electronic books on the Internet. The estimation of reliability of tests contains some limitations. Keeping them in mind, we can still get some information about the quality of certain educational tests. Therefore, the estimation of reliability of the fixed tests is implemented in the ExaMe system.

Handling missing data in cluster randomized trials: A demonstration of multiple imputation with PAN through SAS

Directory of Open Access Journals (Sweden)

Jiangxiu Zhou

2014-09-01

Full Text Available The purpose of this study is to demonstrate a way of dealing with missing data in clustered randomized trials by doing multiple imputation (MI with the PAN package in R through SAS. The procedure for doing MI with PAN through SAS is demonstrated in detail in order for researchers to be able to use this procedure with their own data. An illustration of the technique with empirical data was also included. In this illustration thePAN results were compared with pairwise deletion and three types of MI: (1 Normal Model (NM-MI ignoring the cluster structure; (2 NM-MI with dummy-coded cluster variables (fixed cluster structure; and (3 a hybrid NM-MI which imputes half the time ignoring the cluster structure, and the other half including the dummy-coded cluster variables. The empirical analysis showed that using PAN and the other strategies produced comparable parameter estimates. However, the dummy-coded MI overestimated the intraclass correlation, whereas MI ignoring the cluster structure and the hybrid MI underestimated the intraclass correlation. When compared with PAN, the p-value and standard error for the treatment effect were higher with dummy-coded MI, and lower with MI ignoring the clusterstructure, the hybrid MI approach, and pairwise deletion. Previous studies have shown that NM-MI is not appropriate for handling missing data in clustered randomized trials. This approach, in addition to the pairwise deletion approach, leads to a biased intraclass correlation and faultystatistical conclusions. Imputation in clustered randomized trials should be performed with PAN. We have demonstrated an easy way for using PAN through SAS.

Short-Term and Medium-Term Reliability Evaluation for Power Systems With High Penetration of Wind Power

DEFF Research Database (Denmark)

Ding, Yi; Singh, Chanan; Goel, Lalit

2014-01-01

reliability evaluation techniques for power systems are well developed. These techniques are more focused on steady-state (time-independent) reliability evaluation and have been successfully applied in power system planning and expansion. In the operational phase, however, they may be too rough......The expanding share of the fluctuating and less predictable wind power generation can introduce complexities in power system reliability evaluation and management. This entails a need for the system operator to assess the system status more accurately for securing real-time balancing. The existing...... an approximation of the time-varying behavior of power systems with high penetration of wind power. This paper proposes a time-varying reliability assessment technique. Time-varying reliability models for wind farms, conventional generating units, and rapid start-up generating units are developed and represented...

Reliability Evaluation of Primary Cells | Anyaka | Nigerian Journal of ...

African Journals Online (AJOL)

Evaluation of the reliability of a primary cell took place in three stages: 192 cells went through a slow-discharged test. A designed experiment was conducted on 144 cells; there were three factors in the experiment: Storage temperature (three levels), thermal shock (two levels) and date code (two levels). 16 cells ...

Software reliability evaluation of digital plant protection system development process using V and V

International Nuclear Information System (INIS)

Lee, Na Young; Hwang, Il Soon; Seong, Seung Hwan; Oh, Seung Rok

2001-01-01

In the nuclear power industry, digital technology has been introduced recently for the Instrumentation and Control (I and C) of reactor systems. For its application to the safety critical system such as Reactor Protection System(RPS), a reliability assessment is indispensable. Unlike traditional reliability models, software reliability is hard to evaluate, and should be evaluated throughout development lifecycle. In the development process of Digital Plant Protection System(DPPS), the concept of verification and validation (V and V) was introduced to assure the quality of the product. Also, test should be performed to assure the reliability. Verification procedure with model checking is relatively well defined, however, test is labor intensive and not well organized. In this paper, we developed the methodological process of combining the verification with validation test case generation. For this, we used PVS for the table specification and for the theorem proving. As a result, we could not only save time to design test case but also get more effective and complete verification related test case set. Add to this, we could extract some meaningful factors useful for the reliability evaluation both from the V and V and verification combined tests

Field reliability of competence to stand trial opinions: How often do evaluators agree, and what do judges decide when evaluators disagree?

Science.gov (United States)

Gowensmith, W Neil; Murrie, Daniel C; Boccaccini, Marcus T

2012-04-01

Despite many studies that examine the reliability of competence to stand trial (CST) evaluations, few shed light on "field reliability," or agreement among forensic evaluators in routine practice. We reviewed 216 cases from Hawaii, which requires three separate evaluations from independent clinicians for each felony defendant referred for CST evaluation. Results revealed moderate agreement. In 71% of initial CST evaluations, all evaluators agreed about a defendant's competence or incompetence (kappa = .65). Agreement was somewhat lower (61%, kappa = .57) in re-evaluations of defendants who were originally found incompetent and sent for restoration services. We also examined the decisions judges made about a defendant's CST. When evaluators disagreed, judges tended to make decisions consistent with the majority opinion. But when judges disagreed with the majority opinion, they more often did so to find a defendant incompetent than competent, suggesting a generally conservative approach. Overall, results reveal moderate agreement among independent evaluators in routine practice. But we discuss the potential for standardized training and methodology to further improve the field reliability of CST evaluations.

Reading for Reliability: Preservice Teachers Evaluate Web Sources about Climate Change

Science.gov (United States)

Damico, James S.; Panos, Alexandra

2016-01-01

This study examined what happened when 65 undergraduate prospective secondary level teachers across content areas evaluated the reliability of four online sources about climate change: an oil company webpage, a news report, and two climate change organizations with competing views on climate change. The students evaluated the sources at three time…

Quantitative dynamic reliability evaluation of AP1000 passive safety systems by using FMEA and GO-FLOW methodology

International Nuclear Information System (INIS)

Hashim Muhammad; Yoshikawa, Hidekazu; Matsuoka, Takeshi; Yang Ming

2014-01-01

The passive safety systems utilized in advanced pressurized water reactor (PWR) design such as AP1000 should be more reliable than that of active safety systems of conventional PWR by less possible opportunities of hardware failures and human errors (less human intervention). The objectives of present study are to evaluate the dynamic reliability of AP1000 plant in order to check the effectiveness of passive safety systems by comparing the reliability-related issues with that of active safety systems in the event of the big accidents. How should the dynamic reliability of passive safety systems properly evaluated? And then what will be the comparison of reliability results of AP1000 passive safety systems with the active safety systems of conventional PWR. For this purpose, a single loop model of AP1000 passive core cooling system (PXS) and passive containment cooling system (PCCS) are assumed separately for quantitative reliability evaluation. The transient behaviors of these passive safety systems are taken under the large break loss-of-coolant accident in the cold leg. The analysis is made by utilizing the qualitative method failure mode and effect analysis in order to identify the potential failure mode and success-oriented reliability analysis tool called GO-FLOW for quantitative reliability evaluation. The GO-FLOW analysis has been conducted separately for PXS and PCCS systems under the same accident. The analysis results show that reliability of AP1000 passive safety systems (PXS and PCCS) is increased due to redundancies and diversity of passive safety subsystems and components, and four stages automatic depressurization system is the key subsystem for successful actuation of PXS and PCCS system. The reliability results of PCCS system of AP1000 are more reliable than that of the containment spray system of conventional PWR. And also GO-FLOW method can be utilized for reliability evaluation of passive safety systems. (author)

Long-term reliability evaluation of nuclear containments with tendon force degradation

International Nuclear Information System (INIS)

Kim, Sang-Hyo; Choi, Moon-Seock; Joung, Jung-Yeun; Kim, Kun-Soo

2013-01-01

Highlights: • A probabilistic model on long-term degradation of tendon force is developed. • By using the model, we performed reliability evaluation of nuclear containment. • The analysis is also performed for the case with the strict maintenance programme. • We showed how to satisfy the target safety in the containments facing life extension. - Abstract: The long-term reliability of nuclear containment is important for operating nuclear power plants. In particular, long-term reliability should be clarified when the service life of nuclear containment is being extended. This study focuses not only on determining the reliability of nuclear containment but also presenting the reliability improvement by strengthening the containment itself or by running a strict maintenance programme. The degradation characteristics of tendon force are estimated from the data recorded during in-service inspection of containments. A reliability analysis is conducted for a limit state of through-wall cracking, which is conservative, but most crucial limit state. The results of this analysis indicate that reliability is the lowest at 3/4 height of the containment wall. Therefore, this location is the most vulnerable for the specific limit state considered in this analysis. Furthermore, changes in structural reliability owing to an increase in the number of inspecting tendons are analysed for verifying the effect of the maintenance program's intensity on expected containment reliability. In the last part of this study, an example of obtaining target reliability of nuclear containment by strengthening its structural resistance is presented. A case study is conducted for exemplifying the effect of strengthening work on containment reliability, especially during extended service life

A prospective study assessing agreement and reliability of a geriatric evaluation.

Science.gov (United States)

Locatelli, Isabella; Monod, Stéfanie; Cornuz, Jacques; Büla, Christophe J; Senn, Nicolas

2017-07-19

The present study takes place within a geriatric program, aiming at improving the diagnosis and management of geriatric syndromes in primary care. Within this program it was of prime importance to be able to rely on a robust and reproducible geriatric consultation to use as a gold standard for evaluating a primary care brief assessment tool. The specific objective of the present study was thus assessing the agreement and reliability of a comprehensive geriatric consultation. The study was conducted at the outpatient clinic of the Service of Geriatric Medicine, University of Lausanne, Switzerland. All community-dwelling older persons aged 70 years and above were eligible. Patients were excluded if they hadn't a primary care physician, they were unable to speak French, or they were already assessed by a geriatrician within the last 12 months. A set of 9 geriatricians evaluated 20 patients. Each patient was assessed twice within a 2-month delay. Geriatric consultations were based on a structured evaluation process, leading to rating the following geriatric conditions: functional, cognitive, visual, and hearing impairment, mood disorders, risk of fall, osteoporosis, malnutrition, and urinary incontinence. Reliability and agreement estimates on each of these items were obtained using a three-way Intraclass Correlation and a three-way Observed Disagreement index. The latter allowed a decomposition of overall disagreement into disagreements due to each source of error variability (visit, rater and random). Agreement ranged between 0.62 and 0.85. For most domains, geriatrician-related error variability explained an important proportion of disagreement. Reliability ranged between 0 and 0.8. It was poor/moderate for visual impairment, malnutrition and risk of fall, and good/excellent for functional/cognitive/hearing impairment, osteoporosis, incontinence and mood disorders. Six out of nine items of the geriatric consultation described in this study (functional

Reliability evaluation of a port oil transportation system in variable operation conditions

Energy Technology Data Exchange (ETDEWEB)

Soszynska, Joanna [Department of Mathematics, Gdynia Maritime University, ul. Morska 83, 81-225 Gdynia (Poland)]. E-mail: joannas@am.gdynia.pl

2006-04-15

The semi-Markov model of the system operation processes is proposed and its selected parameters are determined. The series 'm out of k {sub n}' multi-state system is considered and its reliability and risk characteristics are found. Next, the joint model of the system operation process and the system multi-state reliability and risk is constructed. Moreover, reliability and risk evaluation of the multi-state series 'm out of k {sub n}' system in its operation process is applied to the port oil transportation system.

[Evaluation of Suicide Risk Levels in Hospitals: Validity and Reliability Tests].

Science.gov (United States)

Macagnino, Sandro; Steinert, Tilman; Uhlmann, Carmen

2018-05-01

Examination of in-hospital suicide risk levels concerning their validity and their reliability. The internal suicide risk levels were evaluated in a cross sectional study of in 163 inpatients. A reliability check was performed via determining interrater-reliability of senior physician, therapist and the responsible nurse. Within the scope of the validity check, we conducted analyses of criterion validity and construct validity. For the total sample an "acceptable" to "good" interrater-reliability (Kendalls W = .77) of suicide risk levels were obtained. Schizophrenic disorders showed the lowest values, for personality disorders we found the highest level of interrater-reliability. When examining the criterion validity, Item-9 of the BDI-II is substantial correlated to our suicide risk levels (ρ m  = .54, p validity check, affective disorders showed the highest correlation (ρ = .77), compatible also with "convergent validity". They differed with schizophrenic disorders which showed the least concordance (ρ = .43). In-hospital suicide risk levels may represent an important contribution to the assessment of suicidal behavior of inpatients experiencing psychiatric treatment due to their overall good validity and reliability. © Georg Thieme Verlag KG Stuttgart · New York.

Bulk electric system reliability evaluation incorporating wind power and demand side management

Science.gov (United States)

Huang, Dange

Electric power systems are experiencing dramatic changes with respect to structure, operation and regulation and are facing increasing pressure due to environmental and societal constraints. Bulk electric system reliability is an important consideration in power system planning, design and operation particularly in the new competitive environment. A wide range of methods have been developed to perform bulk electric system reliability evaluation. Theoretically, sequential Monte Carlo simulation can include all aspects and contingencies in a power system and can be used to produce an informative set of reliability indices. It has become a practical and viable tool for large system reliability assessment technique due to the development of computing power and is used in the studies described in this thesis. The well-being approach used in this research provides the opportunity to integrate an accepted deterministic criterion into a probabilistic framework. This research work includes the investigation of important factors that impact bulk electric system adequacy evaluation and security constrained adequacy assessment using the well-being analysis framework. Load forecast uncertainty is an important consideration in an electrical power system. This research includes load forecast uncertainty considerations in bulk electric system reliability assessment and the effects on system, load point and well-being indices and reliability index probability distributions are examined. There has been increasing worldwide interest in the utilization of wind power as a renewable energy source over the last two decades due to enhanced public awareness of the environment. Increasing penetration of wind power has significant impacts on power system reliability, and security analyses become more uncertain due to the unpredictable nature of wind power. The effects of wind power additions in generating and bulk electric system reliability assessment considering site wind speed

Reliability evaluation of the Savannah River reactor leak detection system

International Nuclear Information System (INIS)

Daugherty, W.L.; Sindelar, R.L.; Wallace, I.T.

1991-01-01

The Savannah River Reactors have been in operation since the mid-1950's. The primary degradation mode for the primary coolant loop piping is intergranular stress corrosion cracking. The leak-before-break (LBB) capability of the primary system piping has been demonstrated as part of an overall structural integrity evaluation. One element of the LBB analyses is a reliability evaluation of the leak detection system. The most sensitive element of the leak detection system is the airborne tritium monitors. The presence of small amounts of tritium in the heavy water coolant provide the basis for a very sensitive system of leak detection. The reliability of the tritium monitors to properly identify a crack leaking at a rate of either 50 or 300 lb/day (0.004 or 0.023 gpm, respectively) has been characterized. These leak rates correspond to action points for which specific operator actions are required. High reliability has been demonstrated using standard fault tree techniques. The probability of not detecting a leak within an assumed mission time of 24 hours is estimated to be approximately 5 x 10 -5 per demand. This result is obtained for both leak rates considered. The methodology and assumptions used to obtain this result are described in this paper. 3 refs., 1 fig., 1 tab

Application-Driven Reliability Measures and Evaluation Tool for Fault-Tolerant Real-Time Systems

National Research Council Canada - National Science Library

Krishna, C

2001-01-01

.... The measure combines graphic-theoretic concepts in evaluating the underlying reliability of the network and other means to evaluate the ability of the network to support interprocessor traffic...

Requirements for an evaluation infrastructure for reliable pervasive healthcare research

DEFF Research Database (Denmark)

Wagner, Stefan Rahr; Toftegaard, Thomas Skjødeberg; Bertelsen, Olav W.

2012-01-01

The need for a non-intrusive evaluation infrastructure platform to support research on reliable pervasive healthcare in the unsupervised setting is analyzed and challenges and possibilities are identified. A list of requirements is presented and a solution is suggested that would allow researchers...

Reliability evaluation of containments including soil-structure interaction

International Nuclear Information System (INIS)

Pires, J.; Hwang, H.; Reich, M.

1985-12-01

Soil-structure interaction effects on the reliability assessment of containment structures are examined. The probability-based method for reliability evaluation of nuclear structures developed at Brookhaven National Laboratory is extended to include soil-structure interaction effects. In this method, reliability of structures is expressed in terms of limit state probabilities. Furthermore, random vibration theory is utilized to calculate limit state probabilities under random seismic loads. Earthquake ground motion is modeled by a segment of a zero-mean, stationary, filtered Gaussian white noise random process, represented by its power spectrum. All possible seismic hazards at a site, represented by a hazard curve, are also included in the analysis. The soil-foundation system is represented by a rigid surface foundation on an elastic halfspace. Random and other uncertainties in the strength properties of the structure, in the stiffness and internal damping of the soil, are also included in the analysis. Finally, a realistic reinforced concrete containment is analyzed to demonstrate the application of the method. For this containment, the soil-structure interaction effects on; (1) limit state probabilities, (2) structural fragility curves, (3) floor response spectra with probabilistic content, and (4) correlation coefficients for total acceleration response at specified structural locations, are examined in detail. 25 refs., 21 figs., 12 tabs

Evaluation of nodal reliability risk in a deregulated power system with photovoltaic power penetration

DEFF Research Database (Denmark)

Zhao, Qian; Wang, Peng; Goel, Lalit

2014-01-01

Owing to the intermittent characteristic of solar radiation, power system reliability may be affected with high photovoltaic (PV) power penetration. To reduce large variation of PV power, additional system balancing reserve would be needed. In deregulated power systems, deployment of reserves...... and customer reliability requirements are correlated with energy and reserve prices. Therefore a new method should be developed to evaluate the impacts of PV power on customer reliability and system reserve deployment in the new environment. In this study, a method based on the pseudo-sequential Monte Carlo...... simulation technique has been proposed to evaluate the reserve deployment and customers' nodal reliability with high PV power penetration. The proposed method can effectively model the chronological aspects and stochastic characteristics of PV power and system operation with high computation efficiency...

Imputing historical statistics, soils information, and other land-use data to crop area

Science.gov (United States)

Perry, C. R., Jr.; Willis, R. W.; Lautenschlager, L.

1982-01-01

In foreign crop condition monitoring, satellite acquired imagery is routinely used. To facilitate interpretation of this imagery, it is advantageous to have estimates of the crop types and their extent for small area units, i.e., grid cells on a map represent, at 60 deg latitude, an area nominally 25 by 25 nautical miles in size. The feasibility of imputing historical crop statistics, soils information, and other ancillary data to crop area for a province in Argentina is studied.

Evaluation of the reliability of a passive system

International Nuclear Information System (INIS)

Bianchi, F.; Burgazzi, L.; D'Auria, F.; Galassi, G.M.; Ricotti, M.E.; Oriani, L.

2001-01-01

A passive system should be theoretically more reliable than an active one. In fact its operation is independent by any external input or energy and is relied only upon natural physical laws (e.g., gravity, natural circulation, etc.) and/or 'intelligent' use of the energy inherently available in the system (e.g., chemical reaction, decay heat, etc.). Nevertheless the passive system may fail its mission as consequences of component failures, deviation of physical phenomena, boundary and/or initial conditions from the expectation. This document describes at first the methodology developed by ENEA, in collaboration of University of Pisa and Polytechnic of Milano, allowing the evaluation of the reliability for a passive system, which operation is based on moving working fluids (type B and C, cf. IAEA). It reports the results of an exercise performed on a system, which operation is based on Natural Circulation.(author)

Reliability assessment of a peer evaluation instrument in a team-based learning course

Directory of Open Access Journals (Sweden)

Wahawisan J

2016-03-01

Full Text Available Objective: To evaluate the reliability of a peer evaluation instrument in a longitudinal team-based learning setting. Methods: Student pharmacists were instructed to evaluate the contributions of their peers. Evaluations were analyzed for the variance of the scores by identifying low, medium, and high scores. Agreement between performance ratings within each group of students was assessed via intra-class correlation coefficient (ICC. Results: We found little variation in the standard deviation (SD based on the score means among the high, medium, and low scores within each group. The lack of variation in SD of results between groups suggests that the peer evaluation instrument produces precise results. The ICC showed strong concordance among raters. Conclusions: Findings suggest that our student peer evaluation instrument provides a reliable method for peer assessment in team-based learning settings.

Statistical Analysis of a Class: Monte Carlo and Multiple Imputation Spreadsheet Methods for Estimation and Extrapolation

Science.gov (United States)

Fish, Laurel J.; Halcoussis, Dennis; Phillips, G. Michael

2017-01-01

The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems. However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are…

Reliability evaluation of emergency AC power systems based on operating experience at U.S. nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Baranowsky, P. W. [U.S. Nuclear Regulatory Commission, Washington, DC (United States)

1986-02-15

The reliability of emergency AC power Systems has been under study at the U.S. Nuclear Regulatory Commission and by its contractors for several years. This paper provides the results of work recently performed to evaluate past U.S. nuclear power plant emergency AC power System reliability performance using system level data. Operating experience involving multiple diesel generator failures, unavailabilities, and simultaneous occurrences of failures and out of service diesel generators were used to evaluate reliability performance at individual nuclear power plants covering a 9 year period from 1976 through 1984. The number and nature of failures and distributions of reliability evaluation results are provided. The results show that plant specific performance varied considerably during the period with a large number achieving high reliability performance and a smaller number accounting for lower levels of reliability performance. (author)

Imputation of single nucleotide polymorhpism genotypes of Hereford cattle: reference panel size, family relationship and population structure

Science.gov (United States)

The objective of this study is to investigate single nucleotide polymorphism (SNP) genotypes imputation of Hereford cattle. Purebred Herefords were from two sources, Line 1 Hereford (N=240) and representatives of Industry Herefords (N=311). Using different reference panels of 62 and 494 males with 1...

Evaluation of Information Requirements of Reliability Methods in Engineering Design

DEFF Research Database (Denmark)

Marini, Vinicius Kaster; Restrepo-Giraldo, John Dairo; Ahmed-Kristensen, Saeema

2010-01-01

This paper aims to characterize the information needed to perform methods for robustness and reliability, and verify their applicability to early design stages. Several methods were evaluated on their support to synthesis in engineering design. Of those methods, FMEA, FTA and HAZOP were selected...

Inter-rater reliability of the evaluation of muscular chains associated with posture alterations in scoliosis

Directory of Open Access Journals (Sweden)

Fortin Carole

2012-05-01

Full Text Available Abstract Background In the Global postural re-education (GPR evaluation, posture alterations are associated with anterior or posterior muscular chain impairments. Our goal was to assess the reliability of the GPR muscular chain evaluation. Methods Design: Inter-rater reliability study. Fifty physical therapists (PTs and two experts trained in GPR assessed the standing posture from photographs of five youths with idiopathic scoliosis using a posture analysis grid with 23 posture indices (PI. The PTs and experts indicated the muscular chain associated with posture alterations. The PTs were also divided into three groups according to their experience in GPR. Experts’ results (after consensus were used to verify agreement between PTs and experts for muscular chain and posture assessments. We used Kappa coefficients (K and the percentage of agreement (%A to assess inter-rater reliability and intra-class coefficients (ICC for determining agreement between PTs and experts. Results For the muscular chain evaluation, reliability was moderate to substantial for 12 PI for the PTs (%A: 56 to 82; K: 0.42 to 0.76 and perfect for 19 PI for the experts. For posture assessment, reliability was moderate to substantial for 12 PI for the PTs (%A > 60%; K: 0.42 to 0.75 and moderate to perfect for 18 PI for the experts (%A: 80 to 100; K: 0.55 to 1.00. The agreement between PTs and experts was good for most muscular chain evaluations (18 PI; ICC: 0.82 to 0.99 and PI (19 PI; ICC: 0.78 to 1.00. Conclusions The GPR muscular chain evaluation has good reliability for most posture indices. GPR evaluation should help guide physical therapists in targeting affected muscles for treatment of abnormal posture patterns.

Evaluation and improvement in nondestructive examination (NDE) reliability for inservice inspection of light water reactors

International Nuclear Information System (INIS)

Doctor, S.R.; Deffenbaugh, J.D.; Good, M.S.; Green, E.R.; Heasler, P.G.; Simonen, F.A.; Spanner, J.C.; Taylor, T.T.

1988-01-01

The Evaluation and Improvement of NDE Reliability for Inservice Inspection of Light Water Reactors (NDE Reliability) program at the Pacific Northwest Laboratory was established by the NRC to determine the reliability of current inservice inspection (ISI) techniques and to develop recommendations that will ensure a suitably high inspection reliability. The objectives of this program include determining the reliability of ISI performed on the primary systems of commercial light-water reactors (LWRs); using probabilistic fracture mechanics analysis to determine the impact of NDE unreliability on system safety; and evaluating reliability improvements that can be achieved with improved and advanced technology. A final objective is to formulate recommended revisions to ASME Code and Regulatory requirements, based on material properties, service conditions and NDE uncertainties. The program scope is limited to ISI of the primary systems including the piping, vessel, and other inspected components. This is a progress report covering the programmatic work from October 1986 through September 1987. (author)

Evaluation and improvement in nondestructive examination (NDE) reliability for inservice inspection of light water reactors

International Nuclear Information System (INIS)

Doctor, S.R.; Deffenbaugh, J.D.; Good, M.S.; Green, E.R.; Heasler, P.G.; Simonen, F.A.; Spanner, J.C.; Taylor, T.T.

1988-01-01

The Evaluation and Improvement of NDE Reliability for Inservice Inspection of Light Water Reactor (NDE Reliability) program at the Pacific Northwest Laboratory was established by the NRC to determine the reliability of current inservice inspection (ISI) techniques and to develop recommendations that will ensure a suitably high inspection reliability. The objectives of this program include determining the reliability of ISI performed on the primary systems of commercial light-water reactors (LWRs); using probabilistic fracture mechanics analysis to determine the impact of NDE unreliability on system safety; and evaluating reliability improvements that can be achieved with improved and advanced technology. A final objective is to formulate recommended revisions to ASME Code and Regulatory requirements, based on material properties, service conditions, and NDE uncertainties. The program scope is limited to ISI of the primary systems including the piping, vessel, and other inspected components. This is a progress report covering the programmatic work from October 1986 through September 1987

Process evaluation of the human reliability data bank

International Nuclear Information System (INIS)

Miller, D.P.; Comer, K.

1985-01-01

The US Nuclear Regulatory Commission and Sandia National Laboratories have been developing a plan for a human reliability data bank since August 1981. This research is in response to the data need of the nuclear power industry's probabilistic risk assessment community. The three phases of the program are to: (a) develop the data bank concept, (b) develop an implementation plan and conduct a process evaluation, and (c) assist a sponsor in implementing the data bank. The program is now in Phase B. This paper describes the methods used and the results of the process evaluation. Decisions to be made in the future regarding full-scale implementation will be based, in part, on the outcome of this study

Process evaluation of the human reliability data bank

International Nuclear Information System (INIS)

Miller, D.P.; Comer, K.

1984-01-01

The US Nuclear Regulatory Commission and Sandia National Laboratories have been developing a plan for a human reliability data bank since August 1981. This research is in response to the data needs of the nuclear power industry's probabilistic risk assessment community. The three phases of the program are to: (A) develop the data bank concept, (B) develop an implementation plan and conduct a process evaluation, and (C) assist a sponsor in implementing the data bank. The program is now in Phase B. This paper describes the methods used and the results of the process evaluation. Decisions to be made in the future regarding full-scale implementation will be based in part on the outcome of this study

How Reliable Are Students' Evaluations of Teaching Quality? A Variance Components Approach

Science.gov (United States)

Feistauer, Daniela; Richter, Tobias

2017-01-01

The inter-rater reliability of university students' evaluations of teaching quality was examined with cross-classified multilevel models. Students (N = 480) evaluated lectures and seminars over three years with a standardised evaluation questionnaire, yielding 4224 data points. The total variance of these student evaluations was separated into the…

Study on seismic reliability for foundation grounds and surrounding slopes of nuclear power plants. Proposal of evaluation methodology and integration of seismic reliability evaluation system

International Nuclear Information System (INIS)

Ohtori, Yasuki; Kanatani, Mamoru

2006-01-01

This paper proposes an evaluation methodology of annual probability of failure for soil structures subjected to earthquakes and integrates the analysis system for seismic reliability of soil structures. The method is based on margin analysis, that evaluates the ground motion level at which structure is damaged. First, ground motion index that is strongly correlated with damage or response of the specific structure, is selected. The ultimate strength in terms of selected ground motion index is then evaluated. Next, variation of soil properties is taken into account for the evaluation of seismic stability of structures. The variation of the safety factor (SF) is evaluated and then the variation is converted into the variation of the specific ground motion index. Finally, the fragility curve is developed and then the annual probability of failure is evaluated combined with seismic hazard curve. The system facilitates the assessment of seismic reliability. A generator of random numbers, dynamic analysis program and stability analysis program are incorporated into one package. Once we define a structural model, distribution of the soil properties, input ground motions and so forth, list of safety factors for each sliding line is obtained. Monte Carlo Simulation (MCS), Latin Hypercube Sampling (LHS), point estimation method (PEM) and first order second moment (FOSM) implemented in this system are also introduced. As numerical examples, a ground foundation and a surrounding slope are assessed using the proposed method and the integrated system. (author)

Evaluating the reliability of multi-body mechanisms: A method considering the uncertainties of dynamic performance

International Nuclear Information System (INIS)

Wu, Jianing; Yan, Shaoze; Zuo, Ming J.

2016-01-01

Mechanism reliability is defined as the ability of a certain mechanism to maintain output accuracy under specified conditions. Mechanism reliability is generally assessed by the classical direct probability method (DPM) derived from the first order second moment (FOSM) method. The DPM relies strongly on the analytical form of the dynamic solution so it is not applicable to multi-body mechanisms that have only numerical solutions. In this paper, an indirect probability model (IPM) is proposed for mechanism reliability evaluation of multi-body mechanisms. IPM combines the dynamic equation, degradation function and Kaplan–Meier estimator to evaluate mechanism reliability comprehensively. Furthermore, to reduce the amount of computation in practical applications, the IPM is simplified into the indirect probability step model (IPSM). A case study of a crank–slider mechanism with clearance is investigated. Results show that relative errors between the theoretical and experimental results of mechanism reliability are less than 5%, demonstrating the effectiveness of the proposed method. - Highlights: • An indirect probability model (IPM) is proposed for mechanism reliability evaluation. • The dynamic equation, degradation function and Kaplan–Meier estimator are used. • Then the simplified form of indirect probability model is proposed. • The experimental results agree well with the predicted results.

Reliability evaluation of smart distribution grids

OpenAIRE

Kazemi, Shahram

2011-01-01

The term "Smart Grid" generally refers to a power grid equipped with the advanced technologies dedicated for purposes such as reliability improvement, ease of control and management, integrating of distributed energy resources and electricity market operations. Improving the reliability of electric power delivered to the end users is one of the main targets of employing smart grid technologies. The smart grid investments targeted for reliability improvement can be directed toward the generati...

Evaluation of MHTGR fuel reliability

International Nuclear Information System (INIS)

Wichner, R.P.; Barthold, W.P.

1992-07-01

Modular High-Temperature Gas-Cooled Reactor (MHTGR) concepts that house the reactor vessel in a tight but unsealed reactor building place heightened importance on the reliability of the fuel particle coatings as fission product barriers. Though accident consequence analyses continue to show favorable results, the increased dependence on one type of barrier, in addition to a number of other factors, has caused the Nuclear Regulatory Commission (NRC) to consider conservative assumptions regarding fuel behavior. For this purpose, the concept termed ''weak fuel'' has been proposed on an interim basis. ''Weak fuel'' is a penalty imposed on consequence analyses whereby the fuel is assumed to respond less favorably to environmental conditions than predicted by behavioral models. The rationale for adopting this penalty, as well as conditions that would permit its reduction or elimination, are examined in this report. The evaluation includes an examination of possible fuel-manufacturing defects, quality-control procedures for defect detection, and the mechanisms by which fuel defects may lead to failure

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans.

Science.gov (United States)

Gottlieb, Assaf; Daneshjou, Roxana; DeGorter, Marianne; Bourgeois, Stephane; Svensson, Peter J; Wadelius, Mia; Deloukas, Panos; Montgomery, Stephen B; Altman, Russ B

2017-11-24

Genome-wide association studies are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into "gene level" effects. Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression-on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort.

31 CFR 19.630 - May the Department of the Treasury impute conduct of one person to another?

Science.gov (United States)

2010-07-01

... 31 Money and Finance: Treasury 1 2010-07-01 2010-07-01 false May the Department of the Treasury impute conduct of one person to another? 19.630 Section 19.630 Money and Finance: Treasury Office of the Secretary of the Treasury GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) General Principles...

The Use of Imputed Sibling Genotypes in Sibship-Based Association Analysis: On Modeling Alternatives, Power and Model Misspecification

NARCIS (Netherlands)

Minica, C.C.; Dolan, C.V.; Willemsen, G.; Vink, J.M.; Boomsma, D.I.

2013-01-01

When phenotypic, but no genotypic data are available for relatives of participants in genetic association studies, previous research has shown that family-based imputed genotypes can boost the statistical power when included in such studies. Here, using simulations, we compared the performance of

Semiautomatic imputation of activity travel diaries : use of global positioning system traces, prompted recall, and context-sensitive learning algorithms

NARCIS (Netherlands)

Moiseeva, A.; Jessurun, A.J.; Timmermans, H.J.P.; Stopher, P.

2016-01-01

Anastasia Moiseeva, Joran Jessurun and Harry Timmermans (2010), ‘Semiautomatic Imputation of Activity Travel Diaries: Use of Global Positioning System Traces, Prompted Recall, and Context-Sensitive Learning Algorithms’, Transportation Research Record: Journal of the Transportation Research Board,

Test-retest reliability of the Progressive Isoinertial Lifting Evaluation (PILE).

Science.gov (United States)

Lygren, Hildegunn; Dragesund, Tove; Joensen, Jón; Ask, Tove; Moe-Nilssen, Rolf

2005-05-01

A repeated measures single group design. To investigate test-retest reliability of Progressive Isoinertial Lifting Evaluation on patients with long lasting musculoskeletal problems related to the lumbar spine. Test-retest reliability has been satisfactory in healthy men. Test-retest reliability for clinical populations has not been reported. A total of 31 patients (17 women and 14 men) with long lasting low back pain participated in the study. The patients were tested twice at an interval of 2 days and at the same time of the day. The heaviest load that the patient could lift 4 times was used as outcome measure. The error of measurement indicates that the true result in 95% of cases will be within +/-4.5 kg from the measured value, while the difference between 2 measurements in 95% of cases will be less than 6.4 kg. Intra-class correlation (1,1) was 0.91. Relative test-retest reliability was high assessed by intra-class correlation, but absolute measurement variability reported as the smallest detectable difference has relevance for the interpretation of clinical test results and should also be considered.

Reliability Of Kraus-Weber Exercise Test As An Evaluation Tool In ...

African Journals Online (AJOL)

Reliability Of Kraus-Weber Exercise Test As An Evaluation Tool In Low Back ... strength and flexibility of the back, abdominal, psoas and hamstring muscles. ... Keywords: Kraus-Weber test, low back pain, muscle flexibility, muscle strength.

Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Science.gov (United States)

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

Reliability and Availability Evaluation of Wireless Sensor Networks for Industrial Applications

Science.gov (United States)

Silva, Ivanovitch; Guedes, Luiz Affonso; Portugal, Paulo; Vasques, Francisco

2012-01-01

Wireless Sensor Networks (WSN) currently represent the best candidate to be adopted as the communication solution for the last mile connection in process control and monitoring applications in industrial environments. Most of these applications have stringent dependability (reliability and availability) requirements, as a system failure may result in economic losses, put people in danger or lead to environmental damages. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communications over long periods of time and consequently disturb, or even disable, control algorithms. The lack of a structured approach enabling the evaluation of permanent faults, prevents system designers to optimize decisions that minimize these occurrences. In this work we propose a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of Wireless Sensor Networks, when permanent faults occur on network devices. The proposal supports any topology, different levels of redundancy, network reconfigurations, criticality of devices and arbitrary failure conditions. The proposed methodology is particularly suitable for the design and validation of Wireless Sensor Networks when trying to optimize its reliability and availability requirements. PMID:22368497

Non-imputability, criminal dangerousness and curative safety measures: myths and realities

Directory of Open Access Journals (Sweden)

Frank Harbottle Quirós

2017-04-01

Full Text Available The curative safety measures are imposed in a criminal proceeding to the non-imputable people provided that through a prognosis it is concluded in an affirmative way about its criminal dangerousness. Although this statement seems very elementary, in judicial practice several myths remain in relation to these legal institutes whose versions may vary, to a greater or lesser extent, between the different countries of the world. In this context, the present article formulates ten myths based on the experience of Costa Rica and provides an explanation that seeks to weaken or knock them down, inviting the reader to reflect on them.

A multi-state reliability evaluation model for P2P networks

International Nuclear Information System (INIS)

Fan Hehong; Sun Xiaohan

2010-01-01

The appearance of new service types and the convergence tendency of the communication networks have endowed the networks more and more P2P (peer to peer) properties. These networks can be more robust and tolerant for a series of non-perfect operational states due to the non-deterministic server-client distributions. Thus a reliability model taking into account of the multi-state and non-deterministic server-client distribution properties is needed for appropriate evaluation of the networks. In this paper, two new performance measures are defined to quantify the overall and local states of the networks. A new time-evolving state-transition Monte Carlo (TEST-MC) simulation model is presented for the reliability analysis of P2P networks in multiple states. The results show that the model is not only valid for estimating the traditional binary-state network reliability parameters, but also adequate for acquiring the parameters in a series of non-perfect operational states, with good efficiencies, especially for highly reliable networks. Furthermore, the model is versatile for the reliability and maintainability analyses in that both the links and the nodes can be failure-prone with arbitrary life distributions, and various maintainability schemes can be applied.

29 CFR 1471.630 - May the Federal Mediation and Conciliation Service impute conduct of one person to another?

Science.gov (United States)

2010-07-01

... 29 Labor 4 2010-07-01 2010-07-01 false May the Federal Mediation and Conciliation Service impute...) FEDERAL MEDIATION AND CONCILIATION SERVICE GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) General Principles Relating to Suspension and Debarment Actions § 1471.630 May the Federal Mediation and...

Reliability Evaluation on Creep Life Prediction of Alloy 617 for a Very High Temperature Reactor

International Nuclear Information System (INIS)

Kim, Woo-Gon; Hong, Sung-Deok; Kim, Yong-Wan; Park, Jae-Young; Kim, Seon-Jin

2012-01-01

This paper evaluates the reliability of creep rupture life under service conditions of Alloy 617, which is considered as one of the candidate materials for use in a very high temperature reactor (VHTR) system. A Z-parameter, which represents the deviation of creep rupture data from the master curve, was used for the reliability analysis of the creep rupture data of Alloy 617. A Service-condition Creep Rupture Interference (SCRI) model, which can consider both the scattering of the creep rupture data and the fluctuations of temperature and stress under any service conditions, was also used for evaluating the reliability of creep rupture life. The statistical analysis showed that the scattering of creep rupture data based on Z-parameter was supported by normal distribution. The values of reliability decreased rapidly with increasing amplitudes of temperature and stress fluctuations. The results established that the reliability decreased with an increasing service time.

A Step by Step Approach for Evaluating the Reliability of the Main Engine Lube Oil System for a Ship's Propulsion System

Directory of Open Access Journals (Sweden)

Mohan Anantharaman

2014-09-01

Full Text Available Effective and efficient maintenance is essential to ensure reliability of a ship's main propulsion system, which in turn is interdependent on the reliability of a number of associated sub- systems. A primary step in evaluating the reliability of the ship's propulsion system will be to evaluate the reliability of each of the sub- system. This paper discusses the methodology adopted to quantify reliability of one of the vital sub-system viz. the lubricating oil system, and development of a model, based on Markov analysis thereof. Having developed the model, means to improve reliability of the system should be considered. The cost of the incremental reliability should be measured to evaluate cost benefits. A maintenance plan can then be devised to achieve the higher level of reliability. Similar approach could be considered to evaluate the reliability of all other sub-systems. This will finally lead to development of a model to evaluate and improve the reliability of the main propulsion system.

Reliability evaluation of oil pipelines operating in aggressive environment

Science.gov (United States)

Magomedov, R. M.; Paizulaev, M. M.; Gebel, E. S.

2017-08-01

In connection with modern increased requirements for ecology and safety, the development of diagnostic services complex is obligatory and necessary enabling to ensure the reliable operation of the gas transportation infrastructure. Estimation of oil pipelines technical condition should be carried out not only to establish the current values of the equipment technological parameters in operation, but also to predict the dynamics of changes in the physical and mechanical characteristics of the material, the appearance of defects, etc. to ensure reliable and safe operation. In the paper, existing Russian and foreign methods for evaluation of the oil pipelines reliability are considered, taking into account one of the main factors leading to the appearance of crevice in the pipeline material, i.e. change the shape of its cross-section, - corrosion. Without compromising the generality of the reasoning, the assumption of uniform corrosion wear for the initial rectangular cross section has been made. As a result a formula for calculation the probability of failure-free operation was formulated. The proposed mathematical model makes it possible to predict emergency situations, as well as to determine optimal operating conditions for oil pipelines.

Combination of individual tree detection and area-based approach in imputation of forest variables using airborne laser data

Science.gov (United States)

Vastaranta, Mikko; Kankare, Ville; Holopainen, Markus; Yu, Xiaowei; Hyyppä, Juha; Hyyppä, Hannu

2012-01-01

The two main approaches to deriving forest variables from laser-scanning data are the statistical area-based approach (ABA) and individual tree detection (ITD). With ITD it is feasible to acquire single tree information, as in field measurements. Here, ITD was used for measuring training data for the ABA. In addition to automatic ITD (ITD auto), we tested a combination of ITD auto and visual interpretation (ITD visual). ITD visual had two stages: in the first, ITD auto was carried out and in the second, the results of the ITD auto were visually corrected by interpreting three-dimensional laser point clouds. The field data comprised 509 circular plots ( r = 10 m) that were divided equally for testing and training. ITD-derived forest variables were used for training the ABA and the accuracies of the k-most similar neighbor ( k-MSN) imputations were evaluated and compared with the ABA trained with traditional measurements. The root-mean-squared error (RMSE) in the mean volume was 24.8%, 25.9%, and 27.2% with the ABA trained with field measurements, ITD auto, and ITD visual, respectively. When ITD methods were applied in acquiring training data, the mean volume, basal area, and basal area-weighted mean diameter were underestimated in the ABA by 2.7-9.2%. This project constituted a pilot study for using ITD measurements as training data for the ABA. Further studies are needed to reduce the bias and to determine the accuracy obtained in imputation of species-specific variables. The method could be applied in areas with sparse road networks or when the costs of fieldwork must be minimized.

The reliability of WorkWell Systems Functional Capacity Evaluation: a systematic review

Science.gov (United States)

2014-01-01

Background Functional capacity evaluation (FCE) determines a person’s ability to perform work-related tasks and is a major component of the rehabilitation process. The WorkWell Systems (WWS) FCE (formerly known as Isernhagen Work Systems FCE) is currently the most commonly used FCE tool in German rehabilitation centres. Our systematic review investigated the inter-rater, intra-rater and test-retest reliability of the WWS FCE. Methods We performed a systematic literature search of studies on the reliability of the WWS FCE and extracted item-specific measures of inter-rater, intra-rater and test-retest reliability from the identified studies. Intraclass correlation coefficients ≥ 0.75, percentages of agreement ≥ 80%, and kappa coefficients ≥ 0.60 were categorised as acceptable, otherwise they were considered non-acceptable. The extracted values were summarised for the five performance categories of the WWS FCE, and the results were classified as either consistent or inconsistent. Results From 11 identified studies, 150 item-specific reliability measures were extracted. 89% of the extracted inter-rater reliability measures, all of the intra-rater reliability measures and 96% of the test-retest reliability measures of the weight handling and strength tests had an acceptable level of reliability, compared to only 67% of the test-retest reliability measures of the posture/mobility tests and 56% of the test-retest reliability measures of the locomotion tests. Both of the extracted test-retest reliability measures of the balance test were acceptable. Conclusions Weight handling and strength tests were found to have consistently acceptable reliability. Further research is needed to explore the reliability of the other tests as inconsistent findings or a lack of data prevented definitive conclusions. PMID:24674029

Student Practice Evaluation Form-Revised Edition online comment bank: development and reliability analysis.

Science.gov (United States)

Rodger, Sylvia; Turpin, Merrill; Copley, Jodie; Coleman, Allison; Chien, Chi-Wen; Caine, Anne-Maree; Brown, Ted

2014-08-01

The reliable evaluation of occupational therapy students completing practice education placements along with provision of appropriate feedback is critical for both students and for universities from a quality assurance perspective. This study describes the development of a comment bank for use with an online version of the Student Practice Evaluation Form-Revised Edition (SPEF-R Online) and investigates its reliability. A preliminary bank of 109 individual comments (based on previous students' placement performance) was developed via five stages. These comments reflected all 11 SPEF-R domains. A purpose-designed online survey was used to examine the reliability of the comment bank. A total of 37 practice educators returned surveys, 31 of which were fully completed. Participants were asked to rate each individual comment using the five-point SPEF-R rating scale. One hundred and two of 109 comments demonstrated satisfactory agreement with their respective default ratings that were determined by the development team. At each domain level, the intra-class correlation coefficients (ranging between 0.86 and 0.96) also demonstrated good to excellent inter-rater reliability. There were only seven items that required rewording prior to inclusion in the final SPEF-R Online comment bank. The development of the SPEF-R Online comment bank offers a source of reliable comments (consistent with the SPEF-R rating scale across different domains) and aims to assist practice educators in providing reliable and timely feedback to students in a user-friendly manner. © 2014 Occupational Therapy Australia.

Multiple Imputation of Groundwater Data to Evaluate Spatial and Temporal Anthropogenic Influences on Subsurface Water Fluxes in Los Angeles, CA

Science.gov (United States)

Manago, K. F.; Hogue, T. S.; Hering, A. S.

2014-12-01

In the City of Los Angeles, groundwater accounts for 11% of the total water supply on average, and 30% during drought years. Due to ongoing drought in California, increased reliance on local water supply highlights the need for better understanding of regional groundwater dynamics and estimating sustainable groundwater supply. However, in an urban setting, such as Los Angeles, understanding or modeling groundwater levels is extremely complicated due to various anthropogenic influences such as groundwater pumping, artificial recharge, landscape irrigation, leaking infrastructure, seawater intrusion, and extensive impervious surfaces. This study analyzes anthropogenic effects on groundwater levels using groundwater monitoring well data from the County of Los Angeles Department of Public Works. The groundwater data is irregularly sampled with large gaps between samples, resulting in a sparsely populated dataset. A multiple imputation method is used to fill the missing data, allowing for multiple ensembles and improved error estimates. The filled data is interpolated to create spatial groundwater maps utilizing information from all wells. The groundwater data is evaluated at a monthly time step over the last several decades to analyze the effect of land cover and identify other influencing factors on groundwater levels spatially and temporally. Preliminary results show irrigated parks have the largest influence on groundwater fluctuations, resulting in large seasonal changes, exceeding changes in spreading grounds. It is assumed that these fluctuations are caused by watering practices required to sustain non-native vegetation. Conversely, high intensity urbanized areas resulted in muted groundwater fluctuations and behavior decoupling from climate patterns. Results provides improved understanding of anthropogenic effects on groundwater levels in addition to providing high quality datasets for validation of regional groundwater models.

[Reliability of HOMA-IR for evaluation of insulin resistance during perioperative period].

Science.gov (United States)

Fujino, Hiroko; Itoda, Shoko; Sako, Saori; Matsuo, Kazuki; Sakamoto, Eiji; Yokoyama, Takeshi

2013-02-01

Hyperglycemia due to increase in insulin resistance (IR) is often observed after surgery in spite of normal insulin secretion. To evaluate the degree of IR, the golden standard method is the normoglycemic hyperinsulinemic clamp technique (glucose clamp: GC). The GC using the artificial pancreas, STG-22 (Nikkiso, Tokyo, Japan), was established as a more reliable method, since it was evaluated during steady-state period under constant insulin infusion. Homeostasis model assessment insulin resistance (HOMA-IR), however, is frequently employed in daily practice because of its convenience. We, therefore, investigated the reliability of HOMA-IR in comparison with the glucose clamp using the STG-22. Eight healthy patients undergoing maxillofacial surgery were employed in this study after obtaining written informed consent. Their insulin resistance was evaluated by HOMA-IR and the GC using the STG-22 before and after surgery. HOMA-IR increased from 0.81 +/- 0.48 to 1.17 +/- 0.50, although there were no significant differences between before and after surgery. On the other hand, M-value by GC significantly decreased after surgery from 8.82 +/- 2.49 mg x kg(-1) x min(-1) to 3.84 +/- 0.79 mg x kg(-1) x min(-1) (P = 0.0003). In addition, no significant correlation was found between the values of HOMA-IR and the M-value by GC. HOMA-IR may not be reliable to evaluate IR for perioperative period.

The evaluation of equipment and Instrumentation Reliability Factors on Power Reactor

International Nuclear Information System (INIS)

Supriatna, Piping; Karlina, Itjeu; Widagdo, Suharyo; Santosa, Kussigit; Darlis; Sudiyono, Bambang; Yuniyanta, Sasongko; Sudarmin

1999-01-01

Equipment and instrumentation reliability on type power reactor control room was determined by its pattern and design. the principle of ergonomy applied on equipment and instrumentation layout in this ABWR type reactor are geometric pattern appropriate with economic body motion, average anthropometry data of operator especially operator hand-reach, range of vision, angle of vision, lighting, color arrangement and harmony as will as operator case in operating the equipment system. Limitation criteria of the parameter mentioned above are based on EPRI NP-3659, NURG 0700, and NUREG/CR-3331 documents. Besides that, the (working) physical environment parameter factor of the control room must be designed in order to fulfil the standard criteria of ergonomic condition based on NUREG-0800. The reliability evaluation of equipment and instrumentation system also occurs observed from man machine interaction side which happen between operator and equipment and instrumentation in the ABWR type power reactor control room. From the MMI analysis can be known the working failure possibility which is caused by the operator. The evaluation result of equipment and instrumentation reliability on ABWR type power reactor control room showed that the design of this ABWR control room is good and fulfils the ergonomy standard criteria have been determined

Missing Value Imputation Based on Gaussian Mixture Model for the Internet of Things

OpenAIRE

Yan, Xiaobo; Xiong, Weiqing; Hu, Liang; Wang, Feng; Zhao, Kuo

2015-01-01

This paper addresses missing value imputation for the Internet of Things (IoT). Nowadays, the IoT has been used widely and commonly by a variety of domains, such as transportation and logistics domain and healthcare domain. However, missing values are very common in the IoT for a variety of reasons, which results in the fact that the experimental data are incomplete. As a result of this, some work, which is related to the data of the IoT, can’t be carried out normally. And it leads to the red...

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

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Assaf Gottlieb

2017-11-01

Full Text Available Abstract Background Genome-wide association studies are useful for discovering genotype–phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into “gene level” effects. Methods Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. Results We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Conclusions Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort

ON CONSTRUCTION OF A RELIABLE GROUND TRUTH FOR EVALUATION OF VISUAL SLAM ALGORITHMS

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Jan Bayer

2016-11-01

Full Text Available In this work we are concerning the problem of localization accuracy evaluation of visual-based Simultaneous Localization and Mapping (SLAM techniques. Quantitative evaluation of the SLAM algorithm performance is usually done using the established metrics of Relative pose error and Absolute trajectory error which require a precise and reliable ground truth. Such a ground truth is usually hard to obtain, while it requires an expensive external localization system. In this work we are proposing to use the SLAM algorithm itself to construct a reliable ground-truth by offline frame-by-frame processing. The generated ground-truth is suitable for evaluation of different SLAM systems, as well as for tuning the parametrization of the on-line SLAM. The presented practical experimental results indicate the feasibility of the proposed approach.

A suggested approach for imputation of missing dietary data for young children in daycare

OpenAIRE

Stevens, June; Ou, Fang-Shu; Truesdale, Kimberly P.; Zeng, Donglin; Vaughn, Amber E.; Pratt, Charlotte; Ward, Dianne S.

2015-01-01

Background: Parent-reported 24-h diet recalls are an accepted method of estimating intake in young children. However, many children eat while at childcare making accurate proxy reports by parents difficult.Objective: The goal of this study was to demonstrate a method to impute missing weekday lunch and daytime snack nutrient data for daycare children and to explore the concurrent predictive and criterion validity of the method.Design: Data were from children aged 2-5 years in the My Parenting...

Application case study of AP1000 automatic depressurization system (ADS) for reliability evaluation by GO-FLOW methodology

Energy Technology Data Exchange (ETDEWEB)

Hashim, Muhammad, E-mail: hashimsajid@yahoo.com; Hidekazu, Yoshikawa, E-mail: yosikawa@kib.biglobe.ne.jp; Takeshi, Matsuoka, E-mail: mats@cc.utsunomiya-u.ac.jp; Ming, Yang, E-mail: myang.heu@gmail.com

2014-10-15

Highlights: • Discussion on reasons why AP1000 equipped with ADS system comparatively to PWR. • Clarification of full and partial depressurization of reactor coolant system by ADS system. • Application case study of four stages ADS system for reliability evaluation in LBLOCA. • GO-FLOW tool is capable to evaluate dynamic reliability of passive safety systems. • Calculated ADS reliability result significantly increased dynamic reliability of PXS. - Abstract: AP1000 nuclear power plant (NPP) utilized passive means for the safety systems to ensure its safety in events of transient or severe accidents. One of the unique safety systems of AP1000 to be compared with conventional PWR is the “four stages Automatic Depressurization System (ADS)”, and ADS system originally works as an active safety system. In the present study, authors first discussed the reasons of why four stages ADS system is added in AP1000 plant to be compared with conventional PWR in the aspect of reliability. And then explained the full and partial depressurization of RCS system by four stages ADS in events of transient and loss of coolant accidents (LOCAs). Lastly, the application case study of four stages ADS system of AP1000 has been conducted in the aspect of reliability evaluation of ADS system under postulated conditions of full RCS depressurization during large break loss of a coolant accident (LBLOCA) in one of the RCS cold legs. In this case study, the reliability evaluation is made by GO-FLOW methodology to determinate the influence of ADS system in dynamic reliability of passive core cooling system (PXS) of AP1000, i.e. what will happen if ADS system fails or successfully actuate. The GO-FLOW is success-oriented reliability analysis tool and is capable to evaluating the systems reliability/unavailability alternatively to Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) tools. Under these specific conditions of LBLOCA, the GO-FLOW calculated reliability results indicated

Education Research: Bias and poor interrater reliability in evaluating the neurology clinical skills examination

Science.gov (United States)

Schuh, L A.; London, Z; Neel, R; Brock, C; Kissela, B M.; Schultz, L; Gelb, D J.

2009-01-01

Objective: The American Board of Psychiatry and Neurology (ABPN) has recently replaced the traditional, centralized oral examination with the locally administered Neurology Clinical Skills Examination (NEX). The ABPN postulated the experience with the NEX would be similar to the Mini-Clinical Evaluation Exercise, a reliable and valid assessment tool. The reliability and validity of the NEX has not been established. Methods: NEX encounters were videotaped at 4 neurology programs. Local faculty and ABPN examiners graded the encounters using 2 different evaluation forms: an ABPN form and one with a contracted rating scale. Some NEX encounters were purposely failed by residents. Cohen’s kappa and intraclass correlation coefficients (ICC) were calculated for local vs ABPN examiners. Results: Ninety-eight videotaped NEX encounters of 32 residents were evaluated by 20 local faculty evaluators and 18 ABPN examiners. The interrater reliability for a determination of pass vs fail for each encounter was poor (kappa 0.32; 95% confidence interval [CI] = 0.11, 0.53). ICC between local faculty and ABPN examiners for each performance rating on the ABPN NEX form was poor to moderate (ICC range 0.14-0.44), and did not improve with the contracted rating form (ICC range 0.09-0.36). ABPN examiners were more likely than local examiners to fail residents. Conclusions: There is poor interrater reliability between local faculty and American Board of Psychiatry and Neurology examiners. A bias was detected for favorable assessment locally, which is concerning for the validity of the examination. Further study is needed to assess whether training can improve interrater reliability and offset bias. GLOSSARY ABIM = American Board of Internal Medicine; ABPN = American Board of Psychiatry and Neurology; CI = confidence interval; HFH = Henry Ford Hospital; ICC = intraclass correlation coefficients; IM = internal medicine; mini-CEX = Mini-Clinical Evaluation Exercise; NEX = Neurology Clinical

GRIMP: A web- and grid-based tool for high-speed analysis of large-scale genome-wide association using imputed data.

NARCIS (Netherlands)

K. Estrada Gil (Karol); A. Abuseiris (Anis); F.G. Grosveld (Frank); A.G. Uitterlinden (André); T.A. Knoch (Tobias); F. Rivadeneira Ramirez (Fernando)

2009-01-01

textabstractThe current fast growth of genome-wide association studies (GWAS) combined with now common computationally expensive imputation requires the online access of large user groups to high-performance computing resources capable of analyzing rapidly and efficiently millions of genetic

Accuracy, reliability, and timing of visual evaluations of decay in fresh-cut lettuce

Science.gov (United States)

Visual assessments are used for evaluating the quality of food products, such as fresh-cut lettuce packaged in bags with modified atmosphere. We have compared the accuracy and the reliability of visual evaluations of decay on fresh-cut lettuce performed with experienced and inexperienced raters. In ...

Using the Superpopulation Model for Imputations and Variance Computation in Survey Sampling

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Petr Novák

2012-03-01

Full Text Available This study is aimed at variance computation techniques for estimates of population characteristics based on survey sampling and imputation. We use the superpopulation regression model, which means that the target variable values for each statistical unit are treated as random realizations of a linear regression model with weighted variance. We focus on regression models with one auxiliary variable and no intercept, which have many applications and straightforward interpretation in business statistics. Furthermore, we deal with caseswhere the estimates are not independent and thus the covariance must be computed. We also consider chained regression models with auxiliary variables as random variables instead of constants.

An In vitro evaluation of the reliability of QR code denture labeling technique.

Science.gov (United States)

Poovannan, Sindhu; Jain, Ashish R; Krishnan, Cakku Jalliah Venkata; Chandran, Chitraa R

2016-01-01

Positive identification of the dead after accidents and disasters through labeled dentures plays a key role in forensic scenario. A number of denture labeling methods are available, and studies evaluating their reliability under drastic conditions are vital. This study was conducted to evaluate the reliability of QR (Quick Response) Code labeled at various depths in heat-cured acrylic blocks after acid treatment, heat treatment (burns), and fracture in forensics. It was an in vitro study. This study included 160 specimens of heat-cured acrylic blocks (1.8 cm × 1.8 cm) and these were divided into 4 groups (40 samples per group). QR Codes were incorporated in the samples using clear acrylic sheet and they were assessed for reliability under various depths, acid, heat, and fracture. Data were analyzed using Chi-square test, test of proportion. The QR Code inclusion technique was reliable under various depths of acrylic sheet, acid (sulfuric acid 99%, hydrochloric acid 40%) and heat (up to 370°C). Results were variable with fracture of QR Code labeled acrylic blocks. Within the limitations of the study, by analyzing the results, it was clearly indicated that the QR Code technique was reliable under various depths of acrylic sheet, acid, and heat (370°C). Effectiveness varied in fracture and depended on the level of distortion. This study thus suggests that QR Code is an effective and simpler denture labeling method.

Systematic evaluation of the teaching qualities of Obstetrics and Gynecology faculty: reliability and validity of the SETQ tools.

Directory of Open Access Journals (Sweden)

Renée van der Leeuw

Full Text Available BACKGROUND: The importance of effective clinical teaching for the quality of future patient care is globally understood. Due to recent changes in graduate medical education, new tools are needed to provide faculty with reliable and individualized feedback on their teaching qualities. This study validates two instruments underlying the System for Evaluation of Teaching Qualities (SETQ aimed at measuring and improving the teaching qualities of obstetrics and gynecology faculty. METHODS AND FINDINGS: This cross-sectional multi-center questionnaire study was set in seven general teaching hospitals and two academic medical centers in the Netherlands. Seventy-seven residents and 114 faculty were invited to complete the SETQ instruments in the duration of one month from September 2008 to September 2009. To assess reliability and validity of the instruments, we used exploratory factor analysis, inter-item correlation, reliability coefficient alpha and inter-scale correlations. We also compared composite scales from factor analysis to global ratings. Finally, the number of residents' evaluations needed per faculty for reliable assessments was calculated. A total of 613 evaluations were completed by 66 residents (85.7% response rate. 99 faculty (86.8% response rate participated in self-evaluation. Factor analysis yielded five scales with high reliability (Cronbach's alpha for residents' and faculty: learning climate (0.86 and 0.75, professional attitude (0.89 and 0.81, communication of learning goals (0.89 and 0.82, evaluation of residents (0.87 and 0.79 and feedback (0.87 and 0.86. Item-total, inter-scale and scale-global rating correlation coefficients were significant (P<0.01. Four to six residents' evaluations are needed per faculty (reliability coefficient 0.60-0.80. CONCLUSIONS: Both SETQ instruments were found reliable and valid for evaluating teaching qualities of obstetrics and gynecology faculty. Future research should examine improvement of

Evaluation of the reliability of maize reference assays for GMO quantification.

Science.gov (United States)

Papazova, Nina; Zhang, David; Gruden, Kristina; Vojvoda, Jana; Yang, Litao; Buh Gasparic, Meti; Blejec, Andrej; Fouilloux, Stephane; De Loose, Marc; Taverniers, Isabel

2010-03-01

A reliable PCR reference assay for relative genetically modified organism (GMO) quantification must be specific for the target taxon and amplify uniformly along the commercialised varieties within the considered taxon. Different reference assays for maize (Zea mays L.) are used in official methods for GMO quantification. In this study, we evaluated the reliability of eight existing maize reference assays, four of which are used in combination with an event-specific polymerase chain reaction (PCR) assay validated and published by the Community Reference Laboratory (CRL). We analysed the nucleotide sequence variation in the target genomic regions in a broad range of transgenic and conventional varieties and lines: MON 810 varieties cultivated in Spain and conventional varieties from various geographical origins and breeding history. In addition, the reliability of the assays was evaluated based on their PCR amplification performance. A single base pair substitution, corresponding to a single nucleotide polymorphism (SNP) reported in an earlier study, was observed in the forward primer of one of the studied alcohol dehydrogenase 1 (Adh1) (70) assays in a large number of varieties. The SNP presence is consistent with a poor PCR performance observed for this assay along the tested varieties. The obtained data show that the Adh1 (70) assay used in the official CRL NK603 assay is unreliable. Based on our results from both the nucleotide stability study and the PCR performance test, we can conclude that the Adh1 (136) reference assay (T25 and Bt11 assays) as well as the tested high mobility group protein gene assay, which also form parts of CRL methods for quantification, are highly reliable. Despite the observed uniformity in the nucleotide sequence of the invertase gene assay, the PCR performance test reveals that this target sequence might occur in more than one copy. Finally, although currently not forming a part of official quantification methods, zein and SSIIb

Intra- and interobserver reliability of gray scale/dynamic range evaluation of ultrasonography using a standardized phantom

International Nuclear Information System (INIS)

Lee, Song; Choi, Joon Il; Park, Michael Yong; Yeo, Dong Myung; Byun, Jae Young; Jung, Seung Eun; Rha, Sung Eun; Oh, Soon Nam; Lee, Young Joon

2014-01-01

To evaluate intra- and interobserver reliability of the gray scale/dynamic range of the phantom image evaluation of ultrasonography using a standardized phantom, and to assess the effect of interactive education on the reliability. Three radiologists (a resident, and two board-certified radiologists with 2 and 7 years of experience in evaluating ultrasound phantom images) performed the gray scale/dynamic range test for an ultrasound machine using a standardized phantom. They scored the number of visible cylindrical structures of varying degrees of brightness and made a pass or fail decision. First, they scored 49 phantom images twice from a 2010 survey with limited knowledge of phantom images. After this, the radiologists underwent two hours of interactive education for the phantom images and scored another 91 phantom images from a 2011 survey twice. Intra- and interobserver reliability before and after the interactive education session were analyzed using K analyses. Before education, the K-value for intraobserver reliability for the radiologist with 7 years of experience, 2 years of experience, and the resident was 0.386, 0.469, and 0.465, respectively. After education, the K-values were improved (0.823, 0.611, and 0.711, respectively). For interobserver reliability, the K-value was also better after the education for the 3 participants (0.067, 0.002, and 0.547 before education; 0.635, 0.667, and 0.616 after education, respectively). The intra- and interobserver reliability of the gray scale/dynamic range was fair to substantial. Interactive education can improve reliability. For more reliable results, double- checking of phantom images by multiple reviewers is recommended.

Evaluation of reliability of EC inspection of VVER SG tubes

International Nuclear Information System (INIS)

Stanic, D.

2001-01-01

Evaluation of eddy current data collected during inspection of VVER steam generators is very complex task because of numerous parameters which have affect on eddy current signals. That was the reason that recently ago INETEC has started related scientific project in order to evaluate the reliability of eddy current (EC) inspection of VVER steam generator (SG) tubing. In the scope of project the following objectives will be investigated: 1. Determination of POD (Probability of detection) of various types degradation cracks, where their basic parameters are variables (basic parameters are depth, length, width, orientation, number) on three different sets of tubes (clean ideal tubes, tubes with pilgering, tubes electroplated with copper) 2. Sizing quality (accuracy, repeatability) (same data sets as defined in 1.) 3. Effect of fill factor on POD and sizing quality. 4. Effect of tube bends on POD and sizing quality. 5. Effect of other tube geometry variations on POD and sizing quality (tube ovality, transition zone region, expanded (rolled) part of tube, dents, dings). Investigation will start with bobbin probe technique which is the most used technique for general purpose VVER tube examination. Since INETEC is the only world company which successfully developed and applied rotating probe technique for VVER SG tubes, scope of the project will be extended on rotating probe technique utilizing 'pancake' and 'point' coil. Method reliability will be investigated first on the huge set of EDM notches representing various defect morphologies and simulating different factors, and the second part will be investigated on sets of degradation defects obtained by artificial corrosion. In the scope of the project the measures for enhancing the method reliability have to be determined. This considers the proper definition of parameters of examination system, as well as establishment of the suitable analysis procedures. This article presents the temporary results of the first part of

Standards and reliability in evaluation: when rules of thumb don't apply.

Science.gov (United States)

Norcini, J J

1999-10-01

The purpose of this paper is to identify situations in which two rules of thumb in evaluation do not apply. The first rule is that all standards should be absolute. When selection decisions are being made or when classroom tests are given, however, relative standards may be better. The second rule of thumb is that every test should have a reliability of .80 or better. Depending on the circumstances, though, the standard error of measurement, the consistency of pass/fail classifications, and the domain-referenced reliability coefficients may be better indicators of reproducibility.

Evaluation of the reliability of transport networks based on the stochastic flow of moving objects

International Nuclear Information System (INIS)

Wu Weiwei; Ning, Angelika; Ning Xuanxi

2008-01-01

In transport networks, human beings are moving objects whose moving direction is stochastic in emergency situations. Based on this idea, a new model-stochastic moving network (SMN) is proposed. It is different from binary-state networks and stochastic-flow networks. The flow of SMNs has multiple-saturated states, that correspond to different flow values in each arc. In this paper, we try to evaluate the system reliability, defined as the probability that the saturated flow of the network is not less than a given demand d. Based on this new model, we obtain the flow probability distribution of every arc by simulation. An algorithm based on the blocking cutset of the SMN is proposed to evaluate the network reliability. An example is used to show how to calculate the corresponding reliabilities for different given demands of the SMN. Simulation experiments of different size were made and the system reliability precision was calculated. The precision of simulation results also discussed

Evaluation of the reliability of Levine method of wound swab for ...

African Journals Online (AJOL)

The aim of this paper is to evaluate the reliability of Levine swab in accurate identification of microorganisms present in a wound and identify the necessity for further studies in this regard. Methods: A semi structured questionnaire was administered and physical examination was performed on patients with chronic wounds ...

Balance Assessment in Sports-Related Concussion: Evaluating Test-Retest Reliability of the Equilibrate System.

Science.gov (United States)

Odom, Mitchell J; Lee, Young M; Zuckerman, Scott L; Apple, Rachel P; Germanos, Theodore; Solomon, Gary S; Sills, Allen K

2016-01-01

This study evaluated the test-retest reliability of a novel computer-based, portable balance assessment tool, the Equilibrate System (ES), used to diagnose sports-related concussion. Twenty-seven students participated in ES testing consisting of three sessions over 4 weeks. The modified Balance Error Scoring System was performed. For each participant, test-retest reliability was established using the intraclass correlation coefficient (ICC). The ES test-retest reliability from baseline to week 2 produced an ICC value of 0.495 (95% CI, 0.123-0.745). Week 2 testing produced ICC values of 0.602 (95% CI, 0.279-0.803) and 0.610 (95% CI, 0.299-0.804), respectively. All other single measures test-retest reliability values produced poor ICC values. Same-day ES testing showed fair to good test-retest reliability while interweek measures displayed poor to fair test-retest reliability. Testing conditions should be controlled when using computerized balance assessment methods. ES testing should only be used as a part of a comprehensive assessment.

Creation of reliable relevance judgments in information retrieval systems evaluation experimentation through crowdsourcing: a review.

Science.gov (United States)

Samimi, Parnia; Ravana, Sri Devi

2014-01-01

Test collection is used to evaluate the information retrieval systems in laboratory-based evaluation experimentation. In a classic setting, generating relevance judgments involves human assessors and is a costly and time consuming task. Researchers and practitioners are still being challenged in performing reliable and low-cost evaluation of retrieval systems. Crowdsourcing as a novel method of data acquisition is broadly used in many research fields. It has been proven that crowdsourcing is an inexpensive and quick solution as well as a reliable alternative for creating relevance judgments. One of the crowdsourcing applications in IR is to judge relevancy of query document pair. In order to have a successful crowdsourcing experiment, the relevance judgment tasks should be designed precisely to emphasize quality control. This paper is intended to explore different factors that have an influence on the accuracy of relevance judgments accomplished by workers and how to intensify the reliability of judgments in crowdsourcing experiment.

Reliability evaluation for hinges of folder devices using ESPI

International Nuclear Information System (INIS)

Lee, Tae Hun; Chang, Seok Weon; Jhang, Kyung Young

2004-01-01

Folder type electronic devices have hinge to support the rotational motion of folder. This hinge is stressed by the rotational inertia moment of folder at the maximum open limit position of folder. This stress is repeated whenever the folder is open, and it is a cause of hinge fracture. In this paper, the reliability evaluation for the hinge fracture in the folder type cellular phone is discussed. For this, the durability testing machine using crack-rocker mechanism is developed to evaluate the life cycle of the hinge, and the degradation after repetitions of opening and shutting is evaluated from the deformation around the hinge, where the deformation is measured by ESPI (electronic speckle pattern interferometer). Experimental results showed that ESPI was able to measure the deformation of hinge precisely, so we could monitor the change of deformation around the hinge as the repetition number of folder open is increased.

Quality Evaluation Scores are no more Reliable than Gestalt in Evaluating the Quality of Emergency Medicine Blogs: A METRIQ Study.

Science.gov (United States)

Thoma, Brent; Sebok-Syer, Stefanie S; Colmers-Gray, Isabelle; Sherbino, Jonathan; Ankel, Felix; Trueger, N Seth; Grock, Andrew; Siemens, Marshall; Paddock, Michael; Purdy, Eve; Kenneth Milne, William; Chan, Teresa M

2018-01-30

Construct: We investigated the quality of emergency medicine (EM) blogs as educational resources. Online medical education resources such as blogs are increasingly used by EM trainees and clinicians. However, quality evaluations of these resources using gestalt are unreliable. We investigated the reliability of two previously derived quality evaluation instruments for blogs. Sixty English-language EM websites that published clinically oriented blog posts between January 1 and February 24, 2016, were identified. A random number generator selected 10 websites, and the 2 most recent clinically oriented blog posts from each site were evaluated using gestalt, the Academic Life in Emergency Medicine (ALiEM) Approved Instructional Resources (AIR) score, and the Medical Education Translational Resources: Impact and Quality (METRIQ-8) score, by a sample of medical students, EM residents, and EM attendings. Each rater evaluated all 20 blog posts with gestalt and 15 of the 20 blog posts with the ALiEM AIR and METRIQ-8 scores. Pearson's correlations were calculated between the average scores for each metric. Single-measure intraclass correlation coefficients (ICCs) evaluated the reliability of each instrument. Our study included 121 medical students, 88 EM residents, and 100 EM attendings who completed ratings. The average gestalt rating of each blog post correlated strongly with the average scores for ALiEM AIR (r = .94) and METRIQ-8 (r = .91). Single-measure ICCs were fair for gestalt (0.37, IQR 0.25-0.56), ALiEM AIR (0.41, IQR 0.29-0.60) and METRIQ-8 (0.40, IQR 0.28-0.59). The average scores of each blog post correlated strongly with gestalt ratings. However, neither ALiEM AIR nor METRIQ-8 showed higher reliability than gestalt. Improved reliability may be possible through rater training and instrument refinement.

Development of Probabilistic Reliability Models of Photovoltaic System Topologies for System Adequacy Evaluation

Directory of Open Access Journals (Sweden)

Ahmad Alferidi

2017-02-01

Full Text Available The contribution of solar power in electric power systems has been increasing rapidly due to its environmentally friendly nature. Photovoltaic (PV systems contain solar cell panels, power electronic converters, high power switching and often transformers. These components collectively play an important role in shaping the reliability of PV systems. Moreover, the power output of PV systems is variable, so it cannot be controlled as easily as conventional generation due to the unpredictable nature of weather conditions. Therefore, solar power has a different influence on generating system reliability compared to conventional power sources. Recently, different PV system designs have been constructed to maximize the output power of PV systems. These different designs are commonly adopted based on the scale of a PV system. Large-scale grid-connected PV systems are generally connected in a centralized or a string structure. Central and string PV schemes are different in terms of connecting the inverter to PV arrays. Micro-inverter systems are recognized as a third PV system topology. It is therefore important to evaluate the reliability contribution of PV systems under these topologies. This work utilizes a probabilistic technique to develop a power output model for a PV generation system. A reliability model is then developed for a PV integrated power system in order to assess the reliability and energy contribution of the solar system to meet overall system demand. The developed model is applied to a small isolated power unit to evaluate system adequacy and capacity level of a PV system considering the three topologies.

Stroke Impact Scale 3.0: Reliability and Validity Evaluation of the Korean Version.

Science.gov (United States)

Choi, Seong Uk; Lee, Hye Sun; Shin, Joon Ho; Ho, Seung Hee; Koo, Mi Jung; Park, Kyoung Hae; Yoon, Jeong Ah; Kim, Dong Min; Oh, Jung Eun; Yu, Se Hwa; Kim, Dong A

2017-06-01

To establish the reliability and validity the Korean version of the Stroke Impact Scale (K-SIS) 3.0. A total of 70 post-stroke patients were enrolled. All subjects were evaluated for general characteristics, Mini-Mental State Examination (MMSE), the National Institutes of Health Stroke Scale (NIHSS), Modified Barthel Index, Hospital Anxiety and Depression Scale (HADS). The SF-36 and K-SIS 3.0 assessed their health-related quality of life. Statistical analysis after evaluation, determined the reliability and validity of the K-SIS 3.0. A total of 70 patients (mean age, 54.97 years) participated in this study. Internal consistency of the SIS 3.0 (Cronbach's alpha) was obtained, and all domains had good co-efficiency, with threshold above 0.70. Test-retest reliability of SIS 3.0 required correlation (Spearman's rho) of the same domain scores obtained on the first and second assessments. Results were above 0.5, with the exception of social participation and mobility. Concurrent validity of K-SIS 3.0 was assessed using the SF-36, and other scales with the same or similar domains. Each domain of K-SIS 3.0 had a positive correlation with corresponding similar domain of SF-36 and other scales (HADS, MMSE, and NIHSS). The newly developed K-SIS 3.0 showed high inter-intra reliability and test-retest reliabilities, together with high concurrent validity with the original and various other scales, for patients with stroke. K-SIS 3.0 can therefore be used for stroke patients, to assess their health-related quality of life and treatment efficacy.

Sensitivity analysis in multiple imputation in effectiveness studies of psychotherapy.

Science.gov (United States)

Crameri, Aureliano; von Wyl, Agnes; Koemeda, Margit; Schulthess, Peter; Tschuschke, Volker

2015-01-01

The importance of preventing and treating incomplete data in effectiveness studies is nowadays emphasized. However, most of the publications focus on randomized clinical trials (RCT). One flexible technique for statistical inference with missing data is multiple imputation (MI). Since methods such as MI rely on the assumption of missing data being at random (MAR), a sensitivity analysis for testing the robustness against departures from this assumption is required. In this paper we present a sensitivity analysis technique based on posterior predictive checking, which takes into consideration the concept of clinical significance used in the evaluation of intra-individual changes. We demonstrate the possibilities this technique can offer with the example of irregular longitudinal data collected with the Outcome Questionnaire-45 (OQ-45) and the Helping Alliance Questionnaire (HAQ) in a sample of 260 outpatients. The sensitivity analysis can be used to (1) quantify the degree of bias introduced by missing not at random data (MNAR) in a worst reasonable case scenario, (2) compare the performance of different analysis methods for dealing with missing data, or (3) detect the influence of possible violations to the model assumptions (e.g., lack of normality). Moreover, our analysis showed that ratings from the patient's and therapist's version of the HAQ could significantly improve the predictive value of the routine outcome monitoring based on the OQ-45. Since analysis dropouts always occur, repeated measurements with the OQ-45 and the HAQ analyzed with MI are useful to improve the accuracy of outcome estimates in quality assurance assessments and non-randomized effectiveness studies in the field of outpatient psychotherapy.

Evaluating and categorizing the reliability of distribution coefficient values in the sorption database

International Nuclear Information System (INIS)

Ochs, Michael; Saito, Yoshihiko; Kitamura, Akira; Shibata, Masahiro; Sasamoto, Hiroshi; Yui, Mikazu

2007-03-01

Japan Atomic Energy Agency (JAEA) has developed the sorption database (JNC-SDB) for bentonite and rocks in order to assess the retardation property of important radioactive elements in natural and engineered barriers in the H12 report. The database includes distribution coefficient (K d ) of important radionuclides. The K d values in the SDB are about 20,000 data. The SDB includes a great variety of K d and additional key information from many different literatures. Accordingly, the classification guideline and classification system were developed in order to evaluate the reliability of each K d value (Th, Pa, U, Np, Pu, Am, Cm, Cs, Ra, Se, Tc on bentonite). The reliability of 3740 K d values are evaluated and categorized. (author)

Validity and reliability of the Mastication Observation and Evaluation (MOE) instrument.

Science.gov (United States)

Remijn, Lianne; Speyer, Renée; Groen, Brenda E; van Limbeek, Jacques; Nijhuis-van der Sanden, Maria W G

2014-07-01

The Mastication Observation and Evaluation (MOE) instrument was developed to allow objective assessment of a child's mastication process. It contains 14 items and was developed over three Delphi rounds. The present study concerns the further development of the MOE using the COSMIN (Consensus based Standard for the Selection of Measurement Instruments) and investigated the instrument's internal consistency, inter-observer reliability, construct validity and floor and ceiling effects. Consumption of three bites of bread and biscuit was evaluated using the MOE. Data of 59 healthy children (6-48 mths) and 38 children (bread) and 37 children (biscuit) with cerebral palsy (24-72 mths) were used. Four items were excluded before analysis due to zero variance. Principal Components Analysis showed one factor with 8 items. Internal consistency was >0.70 (Chronbach's alpha) for both food consistencies and for both groups of children. Inter-observer reliability varied from 0.51 to 0.98 (weighted Gwet's agreement coefficient). The total MOE scores for both groups showed normal distribution for the population. There were no floor or ceiling effects. The revised MOE now contains 8 items that (a) have a consistent concept for mastication and can be scored on a 4-point scale with sufficient reliability and (b) are sensitive to stages of chewing development in young children. The removed items are retained as part of a criterion referenced list within the MOE. Copyright © 2014 Elsevier Ltd. All rights reserved.

Verification of practicability of quantitative reliability evaluation method (De-BDA) in nuclear power plants

International Nuclear Information System (INIS)

Takahashi, Kinshiro; Yukimachi, Takeo.

1988-01-01

A variety of methods have been applied to study of reliability analysis in which human factors are included in order to enhance the safety and availability of nuclear power plants. De-BDA (Detailed Block Diagram Analysis) is one of such mehtods developed with the objective of creating a more comprehensive and understandable tool for quantitative analysis of reliability associated with plant operations. The practicability of this method has been verified by applying it to reliability analysis of various phases of plant operation as well as evaluation of enhanced man-machine interface in the central control room. (author)

Evaluation and improvement in nondestructive examination (NDE) reliability for inservice inspection of light water reactors

International Nuclear Information System (INIS)

Doctor, S.R.; Andersen, E.S.; Bowey, R.E.; Diaz, A.A.; Good, M.S.; Heasler, P.G.; Hockey, R.L.; Simonen, F.A.; Spanner, J.C.; Taylor, T.T.; Vo, T.V.

1991-01-01

This program is intended to establish the effectiveness, reliability and adequacy of inservice inspection of reactor pressure vessels and primary piping systems and the impact of ISI reliability on system integrity. The objectives of the program include: (a) determine the effectiveness and reliability of ultrasonic inservice inspection (ISI) performed on commercial, light water reactor pressure vessels and piping; (b) recommend Code changes to the inspection procedures to improve the reliability of ISI; (c) using fracture mechanics analysis, determine the impact of NDE unreliability on system safety and determine the level of inspection reliability required to assure a suitably low failure probability; (d) evaluate the degree of reliability improvement which could be achieved using improved NDE techniques; and (e) based on importance of component to safety, material properties, service conditions, and NDE uncertainties, formulate improved inservice inspection criteria (including sampling plan, frequency, and reliability of inspection) for revisions to ASME Section XI and regulatory requirements needed to assure suitably low failure probabilities

Validity and reliability of a self-administered foot evaluation questionnaire (SAFE-Q).

Science.gov (United States)

Niki, Hisateru; Tatsunami, Shinobu; Haraguchi, Naoki; Aoki, Takafumi; Okuda, Ryuzo; Suda, Yasunori; Takao, Masato; Tanaka, Yasuhito

2013-03-01

The Japanese Society for Surgery of the Foot (JSSF) is developing a QOL questionnaire instrument for use in pathological conditions related to the foot and ankle. The main body of the outcome instrument (the Self-Administered Foot Evaluation Questionnaire, SAFE-Q version 2) consists of 34 questionnaire items, which provide five subscale scores (1: Pain and Pain-Related; 2: Physical Functioning and Daily Living; 3: Social Functioning; 4: Shoe-Related; and 5: General Health and Well-Being). In addition, the instrument has nine optional questionnaire items that provide a Sports Activity subscale score. The purpose of this study was to evaluate the test-retest reliability of the SAFE-Q. Version 2 of the SAFE-Q was administered to 876 patients and 491 non-patients, and the test-retest reliability was evaluated for 131 patients. In addition, the SF-36 questionnaire and the JSSF Scale scoring form were administered to all of the participants. Subscale scores were scaled such that the final sum of scores ranged between zero (least healthy) to 100 (healthiest). The intraclass correlation coefficients were larger than 0.7 for all of the scores. The means of the five subscale scores were between 60 and 75. The five subscales easily separated patients from non-patients. The coefficients for the correlations of the subscale scores with the scores on the JSSF Scale and the SF-36 subscales were all highly statistically significantly greater than zero (p valid and reliable. In the future, it will be beneficial to test the responsiveness of the SAFE-Q.

Analyzing the reliability of shuffle-exchange networks using reliability block diagrams

International Nuclear Information System (INIS)

Bistouni, Fathollah; Jahanshahi, Mohsen

2014-01-01

Supercomputers and multi-processor systems are comprised of thousands of processors that need to communicate in an efficient way. One reasonable solution would be the utilization of multistage interconnection networks (MINs), where the challenge is to analyze the reliability of such networks. One of the methods to increase the reliability and fault-tolerance of the MINs is use of various switching stages. Therefore, recently, the reliability of one of the most common MINs namely shuffle-exchange network (SEN) has been evaluated through the investigation on the impact of increasing the number of switching stage. Also, it is concluded that the reliability of SEN with one additional stage (SEN+) is better than SEN or SEN with two additional stages (SEN+2), even so, the reliability of SEN is better compared to SEN with two additional stages (SEN+2). Here we re-evaluate the reliability of these networks where the results of the terminal, broadcast, and network reliability analysis demonstrate that SEN+ and SEN+2 continuously outperform SEN and are very alike in terms of reliability. - Highlights: • The impact of increasing the number of stages on reliability of MINs is investigated. • The RBD method as an accurate method is used for the reliability analysis of MINs. • Complex series–parallel RBDs are used to determine the reliability of the MINs. • All measures of the reliability (i.e. terminal, broadcast, and network reliability) are analyzed. • All reliability equations will be calculated for different size N×N

The Maastricht Clinical Teaching Questionnaire (MCTQ) as a valid and reliable instrument for the evaluation of clinical teachers.

Science.gov (United States)

Stalmeijer, Renée E; Dolmans, Diana H J M; Wolfhagen, Ineke H A P; Muijtjens, Arno M M; Scherpbier, Albert J J A

2010-11-01

Clinical teaching's importance in the medical curriculum has led to increased interest in its evaluation. Instruments for evaluating clinical teaching must be theory based, reliable, and valid. The Maastricht Clinical Teaching Questionnaire (MCTQ), based on the theoretical constructs of cognitive apprenticeship, elicits evaluations of individual clinical teachers' performance at the workplace. The authors investigated its construct validity and reliability, and they used the underlying factors to test a causal model representing effective clinical teaching. Between March 2007 and December 2008, the authors asked students who had completed clerkship rotations in different departments of two teaching hospitals to use the MCTQ to evaluate their clinical teachers. To establish construct validity, the authors performed a confirmatory factor analysis of the evaluation data, and they estimated reliability by calculating the generalizability coefficient and standard error measurement. Finally, to test a model of the factors, they fitted a structural linear model to the data. Confirmatory factor analysis yielded a five-factor model which fit the data well. Generalizability studies indicated that 7 to 10 student ratings can produce reliable ratings of individual teachers. The hypothesized structural linear model underlined the central roles played by modeling and coaching (mediated by articulation). The MCTQ is a valid and reliable evaluation instrument, thereby demonstrating the usefulness of the cognitive apprenticeship concept for clinical teaching during clerkships. Furthermore, a valuable model of clinical teaching emerged, highlighting modeling, coaching, and stimulating students' articulation and exploration as crucial to effective teaching at the clinical workplace.

Distribution system reliability evaluation using credibility theory | Xu ...

African Journals Online (AJOL)

In this paper, a hybrid algorithm based on fuzzy simulation and Failure Mode and Effect Analysis (FMEA) is applied to determine fuzzy reliability indices of distribution system. This approach can obtain fuzzy expected values and their variances of reliability indices, and the credibilities of reliability indices meeting specified ...

Rainfall Reliability Evaluation for Stability of Municipal Solid Waste Landfills on Slope

Directory of Open Access Journals (Sweden)

Fu-Kuo Huang

2013-01-01

Full Text Available A method to assess the reliability for the stability of municipal solid waste (MSW landfills on slope due to rainfall infiltration is proposed. Parameter studies are first done to explore the influence of factors on the stability of MSW. These factors include rainfall intensity, duration, pattern, and the engineering properties of MSW. Then 100 different combinations of parameters are generated and associated stability analyses of MSW on slope are performed assuming that each parameter is uniform distributed around its reason ranges. In the following, the performance of the stability of MSW is interpreted by the artificial neural network (ANN trained and verified based on the aforementioned 100 analysis results. The reliability for the stability of MSW landfills on slope is then evaluated and explored for different rainfall parameters by the ANN model with first-order reliability method (FORM and Monte Carlo simulation (MCS.

Research on Control Method Based on Real-Time Operational Reliability Evaluation for Space Manipulator

Directory of Open Access Journals (Sweden)

Yifan Wang

2014-05-01

Full Text Available A control method based on real-time operational reliability evaluation for space manipulator is presented for improving the success rate of a manipulator during the execution of a task. In this paper, a method for quantitative analysis of operational reliability is given when manipulator is executing a specified task; then a control model which could control the quantitative operational reliability is built. First, the control process is described by using a state space equation. Second, process parameters are estimated in real time using Bayesian method. Third, the expression of the system's real-time operational reliability is deduced based on the state space equation and process parameters which are estimated using Bayesian method. Finally, a control variable regulation strategy which considers the cost of control is given based on the Theory of Statistical Process Control. It is shown via simulations that this method effectively improves the operational reliability of space manipulator control system.

Comparison of Imputation Methods for Handling Missing Categorical Data with Univariate Pattern|| Una comparación de métodos de imputación de variables categóricas con patrón univariado

Directory of Open Access Journals (Sweden)

Torres Munguía, Juan Armando

2014-06-01

Full Text Available This paper examines the sample proportions estimates in the presence of univariate missing categorical data. A database about smoking habits (2011 National Addiction Survey of Mexico was used to create simulated yet realistic datasets at rates 5% and 15% of missingness, each for MCAR, MAR and MNAR mechanisms. Then the performance of six methods for addressing missingness is evaluated: listwise, mode imputation, random imputation, hot-deck, imputation by polytomous regression and random forests. Results showed that the most effective methods for dealing with missing categorical data in most of the scenarios assessed in this paper were hot-deck and polytomous regression approaches. || El presente estudio examina la estimación de proporciones muestrales en la presencia de valores faltantes en una variable categórica. Se utiliza una encuesta de consumo de tabaco (Encuesta Nacional de Adicciones de México 2011 para crear bases de datos simuladas pero reales con 5% y 15% de valores perdidos para cada mecanismo de no respuesta MCAR, MAR y MNAR. Se evalúa el desempeño de seis métodos para tratar la falta de respuesta: listwise, imputación de moda, imputación aleatoria, hot-deck, imputación por regresión politómica y árboles de clasificación. Los resultados de las simulaciones indican que los métodos más efectivos para el tratamiento de la no respuesta en variables categóricas, bajo los escenarios simulados, son hot-deck y la regresión politómica.

Evaluation of structural reliability using simulation methods

Directory of Open Access Journals (Sweden)

Baballëku Markel

2015-01-01

Full Text Available Eurocode describes the 'index of reliability' as a measure of structural reliability, related to the 'probability of failure'. This paper is focused on the assessment of this index for a reinforced concrete bridge pier. It is rare to explicitly use reliability concepts for design of structures, but the problems of structural engineering are better known through them. Some of the main methods for the estimation of the probability of failure are the exact analytical integration, numerical integration, approximate analytical methods and simulation methods. Monte Carlo Simulation is used in this paper, because it offers a very good tool for the estimation of probability in multivariate functions. Complicated probability and statistics problems are solved through computer aided simulations of a large number of tests. The procedures of structural reliability assessment for the bridge pier and the comparison with the partial factor method of the Eurocodes have been demonstrated in this paper.

Low field magnetic resonance imaging of the lumbar spine: Reliability of qualitative evaluation of disc and muscle parameters

DEFF Research Database (Denmark)

Sørensen, Joan Solgaard; Kjaer, Per; Jensen, Tue Secher

2006-01-01

PURPOSE: To determine the intra- and interobserver reliability in grading disc and muscle parameters using low-field magnetic resonance imaging (MRI). MATERIAL AND METHODS: MRI scans of 100 subjects representative of the general population were evaluated blindly by two radiologists. Criteria......: Convincing reliability was found in the evaluation of disc- and muscle-related MRI variables....

On Matrix Sampling and Imputation of Context Questionnaires with Implications for the Generation of Plausible Values in Large-Scale Assessments

Science.gov (United States)

Kaplan, David; Su, Dan

2016-01-01

This article presents findings on the consequences of matrix sampling of context questionnaires for the generation of plausible values in large-scale assessments. Three studies are conducted. Study 1 uses data from PISA 2012 to examine several different forms of missing data imputation within the chained equations framework: predictive mean…

21 CFR 1404.630 - May the Office of National Drug Control Policy impute conduct of one person to another?

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 9 2010-04-01 2010-04-01 false May the Office of National Drug Control Policy impute conduct of one person to another? 1404.630 Section 1404.630 Food and Drugs OFFICE OF NATIONAL DRUG CONTROL POLICY GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) General Principles Relating to Suspension and Debarment Actions § 1404.630...

Evaluation of the reliability of the protection system of 1300 MWE PWR'S

International Nuclear Information System (INIS)

Blin, A.

1990-01-01

An assesment of the reliability of the Digital Integrated Protection System (SPIN) of the 1300 MWe type french reactors has been carried out by treating an example: the emergency shutdown, which can be called upon by several initiating events. The whole chain, from sensors to breakers and control rods, is taken into account. The reliability parameters used for the quantification are evaluated essentially from the experience feedback of french reactors. The not wellknown parameters being the common cause failure rates of electronic components and the efficiency rate of the self-tests, the results of the study are then presented in a parametric form, according to these two factors

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

NARCIS (Netherlands)

Y.J. Kim (Young Jin); J. Lee (Juyoung); B.-J. Kim (Bong-Jo); T. Park (Taesung); G.R. Abecasis (Gonçalo); M.A.A. De Almeida (Marcio); D. Altshuler (David); J.L. Asimit (Jennifer L.); G. Atzmon (Gil); M. Barber (Mathew); A. Barzilai (Ari); N.L. Beer (Nicola L.); G.I. Bell (Graeme I.); J. Below (Jennifer); T. Blackwell (Tom); J. Blangero (John); M. Boehnke (Michael); D.W. Bowden (Donald W.); N.P. Burtt (Noël); J.C. Chambers (John); H. Chen (Han); P. Chen (Ping); P.S. Chines (Peter); S. Choi (Sungkyoung); C. Churchhouse (Claire); P. Cingolani (Pablo); B.K. Cornes (Belinda); N.J. Cox (Nancy); A.G. Day-Williams (Aaron); A. Duggirala (Aparna); J. Dupuis (Josée); T. Dyer (Thomas); S. Feng (Shuang); J. Fernandez-Tajes (Juan); T. Ferreira (Teresa); T.E. Fingerlin (Tasha E.); J. Flannick (Jason); J.C. Florez (Jose); P. Fontanillas (Pierre); T.M. Frayling (Timothy); C. Fuchsberger (Christian); E. Gamazon (Eric); K. Gaulton (Kyle); S. Ghosh (Saurabh); B. Glaser (Benjamin); A.L. Gloyn (Anna); R.L. Grossman (Robert L.); J. Grundstad (Jason); C. Hanis (Craig); A. Heath (Allison); H. Highland (Heather); M. Horikoshi (Momoko); I.-S. Huh (Ik-Soo); J.R. Huyghe (Jeroen R.); M.K. Ikram (Kamran); K.A. Jablonski (Kathleen); Y. Jun (Yang); N. Kato (Norihiro); J. Kim (Jayoun); Y.J. Kim (Young Jin); B.-J. Kim (Bong-Jo); J. Lee (Juyoung); C.R. King (C. Ryan); J.S. Kooner (Jaspal S.); M.-S. Kwon (Min-Seok); H.K. Im (Hae Kyung); M. Laakso (Markku); K.K.-Y. Lam (Kevin Koi-Yau); J. Lee (Jaehoon); S. Lee (Selyeong); S. Lee (Sungyoung); D.M. Lehman (Donna M.); H. Li (Heng); C.M. Lindgren (Cecilia); X. Liu (Xuanyao); O.E. Livne (Oren E.); A.E. Locke (Adam E.); A. Mahajan (Anubha); J.B. Maller (Julian B.); A.K. Manning (Alisa K.); T.J. Maxwell (Taylor J.); A. Mazoure (Alexander); M.I. McCarthy (Mark); J.B. Meigs (James B.); B. Min (Byungju); K.L. Mohlke (Karen); A.P. Morris (Andrew); S. Musani (Solomon); Y. Nagai (Yoshihiko); M.C.Y. Ng (Maggie C.Y.); D. Nicolae (Dan); S. Oh (Sohee); N.D. Palmer (Nicholette); T. Park (Taesung); T.I. Pollin (Toni I.); I. Prokopenko (Inga); D. Reich (David); M.A. Rivas (Manuel); L.J. Scott (Laura); M. Seielstad (Mark); Y.S. Cho (Yoon Shin); X. Sim (Xueling); R. Sladek (Rob); P. Smith (Philip); I. Tachmazidou (Ioanna); E.S. Tai (Shyong); Y.Y. Teo (Yik Ying); T.M. Teslovich (Tanya M.); J. Torres (Jason); V. Trubetskoy (Vasily); S.M. Willems (Sara); A.L. Williams (Amy L.); J.G. Wilson (James); S. Wiltshire (Steven); S. Won (Sungho); A.R. Wood (Andrew); W. Xu (Wang); J. Yoon (Joon); M. Zawistowski (Matthew); E. Zeggini (Eleftheria); W. Zhang (Weihua); S. Zöllner (Sebastian)

2015-01-01

textabstractBackground: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the

Development of slim-maud: a multi-attribute utility approach to human reliability evaluation

International Nuclear Information System (INIS)

Embrey, D.E.

1984-01-01

This paper describes further work on the Success Likelihood Index Methodology (SLIM), a procedure for quantitatively evaluating human reliability in nuclear power plants and other systems. SLIM was originally developed by Human Reliability Associates during an earlier contract with Brookhaven National Laboratory (BNL). A further development of SLIM, SLIM-MAUD (Multi-Attribute Utility Decomposition) is also described. This is an extension of the original approach using an interactive, computer-based system. All of the work described in this report was supported by the Human Factors and Safeguards Branch of the US Nuclear Regulatory Commission

Reliability and risk evaluation of a port oil pipeline transportation system in variable operation conditions

Energy Technology Data Exchange (ETDEWEB)

Soszynska, Joanna, E-mail: joannas@am.gdynia.p [Department of Mathematics, Gdynia Maritime University, ul. Morska 83, 81-225 Gdynia (Poland)

2010-02-15

The semi-Markov model of the system operation processes is proposed and its selected characteristics are determined. A system composed on multi-state components is considered and its reliability and risk characteristics are found. Next, the joint model of the system operation process and the system multi-state reliability is applied to the reliability and risk evaluation of the port oil pipeline transportation system. The pipeline system is described and its operation process unknown parameters are identified on the basis of real statistical data. The mean values of the pipeline system operation process unconditional sojourn times in particular operation states are found and applied to determining this process transient probabilities in these states. The piping different reliability structures in various its operation states are fixed and their conditional reliability functions on the basis of data coming from experts are approximately determined. Finally, after applying earlier estimated transient probabilities and system conditional reliability functions in particular operation states the unconditional reliability function, the mean values and standard deviations of the pipeline lifetimes in particular reliability states, risk function and the moment when the risk exceeds a critical value are found.

Reliability and risk evaluation of a port oil pipeline transportation system in variable operation conditions

International Nuclear Information System (INIS)

Soszynska, Joanna

2010-01-01

The semi-Markov model of the system operation processes is proposed and its selected characteristics are determined. A system composed on multi-state components is considered and its reliability and risk characteristics are found. Next, the joint model of the system operation process and the system multi-state reliability is applied to the reliability and risk evaluation of the port oil pipeline transportation system. The pipeline system is described and its operation process unknown parameters are identified on the basis of real statistical data. The mean values of the pipeline system operation process unconditional sojourn times in particular operation states are found and applied to determining this process transient probabilities in these states. The piping different reliability structures in various its operation states are fixed and their conditional reliability functions on the basis of data coming from experts are approximately determined. Finally, after applying earlier estimated transient probabilities and system conditional reliability functions in particular operation states the unconditional reliability function, the mean values and standard deviations of the pipeline lifetimes in particular reliability states, risk function and the moment when the risk exceeds a critical value are found.

A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information

International Nuclear Information System (INIS)

Wang, Lizhi; Pan, Rong; Li, Xiaoyang; Jiang, Tongmin

2013-01-01

Accelerated degradation testing (ADT) is a common approach in reliability prediction, especially for products with high reliability. However, oftentimes the laboratory condition of ADT is different from the field condition; thus, to predict field failure, one need to calibrate the prediction made by using ADT data. In this paper a Bayesian evaluation method is proposed to integrate the ADT data from laboratory with the failure data from field. Calibration factors are introduced to calibrate the difference between the lab and the field conditions so as to predict a product's actual field reliability more accurately. The information fusion and statistical inference procedure are carried out through a Bayesian approach and Markov chain Monte Carlo methods. The proposed method is demonstrated by two examples and the sensitivity analysis to prior distribution assumption

Different methods for analysing and imputation missing values in wind speed series; La problematica de la calidad de la informacion en series de velocidad del viento-metodologias de analisis y imputacion de datos faltantes

Energy Technology Data Exchange (ETDEWEB)

Ferreira, A. M.

2004-07-01

This study concerns about different methods for analysing and imputation missing values in wind speed series. The algorithm EM and a methodology derivated from the sequential hot deck have been utilized. Series with missing values imputed are compared with original and complete series, using several criteria, such the wind potential; and appears to exist a significant goodness of fit between the estimates and real values. (Author)

Human Reliability Assessment and Human Performance Evaluation: Research and Analysis Activities at the U.S. NRC

International Nuclear Information System (INIS)

Ramey-Smith, A.M.

1998-01-01

The author indicates the themes of the six programs identified by the US NRC mission on human performance and human reliability activities. They aim at developing the technical basis to support human performance, at developing and updating a model of human performance and human reliability, at fostering national and international dialogue and cooperation efforts on human performance evaluation, at conducting operating events analysis and database development, and at providing support to human performance and human reliability inspection

Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk

DEFF Research Database (Denmark)

Goode, Ellen L; Fridley, Brooke L; Vierkant, Robert A

2009-01-01

Polymorphisms in genes critical to cell cycle control are outstanding candidates for association with ovarian cancer risk; numerous genes have been interrogated by multiple research groups using differing tagging single-nucleotide polymorphism (SNP) sets. To maximize information gleaned from......, and rs3212891; CDK2 rs2069391, rs2069414, and rs17528736; and CCNE1 rs3218036. These results exemplify the utility of imputation in candidate gene studies and lend evidence to a role of cell cycle genes in ovarian cancer etiology, suggest a reduced set of SNPs to target in additional cases and controls....

Decision Diagram Based Symbolic Algorithm for Evaluating the Reliability of a Multistate Flow Network

Directory of Open Access Journals (Sweden)

Rongsheng Dong

2016-01-01

Full Text Available Evaluating the reliability of Multistate Flow Network (MFN is an NP-hard problem. Ordered binary decision diagram (OBDD or variants thereof, such as multivalued decision diagram (MDD, are compact and efficient data structures suitable for dealing with large-scale problems. Two symbolic algorithms for evaluating the reliability of MFN, MFN_OBDD and MFN_MDD, are proposed in this paper. In the algorithms, several operating functions are defined to prune the generated decision diagrams. Thereby the state space of capacity combinations is further compressed and the operational complexity of the decision diagrams is further reduced. Meanwhile, the related theoretical proofs and complexity analysis are carried out. Experimental results show the following: (1 compared to the existing decomposition algorithm, the proposed algorithms take less memory space and fewer loops. (2 The number of nodes and the number of variables of MDD generated in MFN_MDD algorithm are much smaller than those of OBDD built in the MFN_OBDD algorithm. (3 In two cases with the same number of arcs, the proposed algorithms are more suitable for calculating the reliability of sparse networks.

Statistical estimation Monte Carlo for unreliability evaluation of highly reliable system

International Nuclear Information System (INIS)

Xiao Gang; Su Guanghui; Jia Dounan; Li Tianduo

2000-01-01

Based on analog Monte Carlo simulation, statistical Monte Carlo methods for unreliable evaluation of highly reliable system are constructed, including direct statistical estimation Monte Carlo method and weighted statistical estimation Monte Carlo method. The basal element is given, and the statistical estimation Monte Carlo estimators are derived. Direct Monte Carlo simulation method, bounding-sampling method, forced transitions Monte Carlo method, direct statistical estimation Monte Carlo and weighted statistical estimation Monte Carlo are used to evaluate unreliability of a same system. By comparing, weighted statistical estimation Monte Carlo estimator has smallest variance, and has highest calculating efficiency

Chinese-adapted youth attitude to noise scale: Evaluation of validity and reliability

Directory of Open Access Journals (Sweden)

Xiaofang Zhu

2014-01-01

Full Text Available Noise exposure is central to hearing impairment, especially for adolescents. Chinese youth frequently and consciously expose themselves to loud noise, often for many hours. Hence, a Chinese-adapted evaluative scale to measure youth′s attitude toward noise could rigorously evaluate data validity and reliability. After authenticating the youth attitude to noise scale (YANS originally developed by Olsen and Erlandsson, we purposively sampled and surveyed 642 freshmen at Capital Medical University in Beijing, China. To establish validity, we conducted confirmatory factor analysis according to Olsen′s classification. To establish reliability, we calculated Cronbach′s alpha coefficient and split-half coefficient. We used Bland-Altman analysis to calculate the agreement limits between test and retest. Among 642 students, 550 (85.67% participated in statistical analysis (399 females [72.55%] vs. 151 males [27.45%]. Confirmatory factorial analysis sorted 19 items into four main subcategories (F1-F4 in terms of factor load, yielding a correlation coefficient between factors <0.40. The Cronbach′s alpha coefficient (0.70 was within the desirable range, confirming the reliability of Chinese-adapted YANS. The split-half coefficient was 0.53. Furthermore, the paired t-test reported a mean difference of 0.002 (P = 0.9601. Notably, the mean overall YANS score (3.46 was similar to YANS testing in Belgium (3.10, but higher than Sweden (2.10 and Brazil (2.80. The Chinese version of the YANS questionnaire is valid, reliable, and adaptable to Chinese adolescents. Analysis of the adapted YANS showed that a significant number of Chinese youth display a poor attitude and behavior toward noise. Therefore, Chinese YANS can play a pivotal role in programs that focus on increasing youth awareness of noise and hearing health.

Evaluate the system reliability for a manufacturing network with reworking actions

International Nuclear Information System (INIS)

Lin, Yi-Kuei; Chang, Ping-Chen

2012-01-01

To measure the system reliability of a manufacturing system with reworking actions is a crucial issue in industry, in which the system reliability could be one of the essential performance indicators to evaluate whether the manufacturing system is capable or not. In a manufacturing system, the input flow (raw materials/WIP) processed by each machine might be defective and thus the output flow (WIP/products) would be less than the input amount. Moreover, defective WIP/products are usually incentive to be reworked for reducing wasting and increasing output. Therefore, reworking actions are necessary to be considered in the manufacturing system. Based on the path concept, we revise such a manufacturing system as a stochastic-flow network in which the capacity of each machine is stochastic (i.e., multistate) due to the failure, partial failure, and maintenance. We decompose the network into one general processing path and several reworking paths. Subsequently, three algorithms for different network models are proposed to generate the lower boundary vector which affords to produce enough products satisfying the demand d. In terms of such a vector, the system reliability can be derived afterwards.

Simulated patient training: Using inter-rater reliability to evaluate simulated patient consistency in nursing education.

Science.gov (United States)

MacLean, Sharon; Geddes, Fiona; Kelly, Michelle; Della, Phillip

2018-03-01

Simulated patients (SPs) are frequently used for training nursing students in communication skills. An acknowledged benefit of using SPs is the opportunity to provide a standardized approach by which participants can demonstrate and develop communication skills. However, relatively little evidence is available on how to best facilitate and evaluate the reliability and accuracy of SPs' performances. The aim of this study is to investigate the effectiveness of an evidenced based SP training framework to ensure standardization of SPs. The training framework was employed to improve inter-rater reliability of SPs. A quasi-experimental study was employed to assess SP post-training understanding of simulation scenario parameters using inter-rater reliability agreement indices. Two phases of data collection took place. Initially a trial phase including audio-visual (AV) recordings of two undergraduate nursing students completing a simulation scenario is rated by eight SPs using the Interpersonal Communication Assessments Scale (ICAS) and Quality of Discharge Teaching Scale (QDTS). In phase 2, eight SP raters and four nursing faculty raters independently evaluated students' (N=42) communication practices using the QDTS. Intraclass correlation coefficients (ICC) were >0.80 for both stages of the study in clinical communication skills. The results support the premise that if trained appropriately, SPs have a high degree of reliability and validity to both facilitate and evaluate student performance in nurse education. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Evaluating and categorizing the reliability of distribution coefficient values in the sorption database (4)

International Nuclear Information System (INIS)

Suyama, Tadahiro; Tachi, Yukio; Ganter, Charlotte; Kunze, Susanne; Ochs, Michael

2011-02-01

Sorption of radionuclides in bentonites and rocks is one of the key processes in the safe geological disposal of radioactive waste. Japan Atomic Energy Agency (JAEA) has developed sorption database (JAEA-SDB) which includes extensive compilation of sorption K d data by batch experiments, extracted from published literatures. JAEA published the first SDB as an important basis for the H12 performance assessment (PA), and has been continuing to improve and update the SDB in view of potential future data needs, focusing on assuring the desired quality level and practical applications to K d -setting for the geological environment. The JAEA-SDB includes more than 24,000 K d data which are related with various conditions and methods, and different reliabilities. Accordingly, the quality assuring (QA) and classifying guideline/criteria has been developed in order to evaluate the reliability of each K d value. The reliability of K d values of key radionuclides for bentonite, mudstone, granite and Fe-oxide/hydroxide, Al-oxide/hydroxide has been already evaluated. These QA information has been made available to access through the web-based JAEA-SDB since March, 2009. In this report, the QA/classification of selected entries in the JAEA-SDB, focusing on key radionuclides (Th, Np, Am, Se and Cs) sorption on tuff existing widely in geological environment, was done following the approach/guideline defined in our previous report. As a result, the reliability of 560 K d values was evaluated and classified. This classification scheme is expected to make it possible to obtain quick overview of the available data from the SDB, and to have suitable access to the respective data for K d -setting in PA. (author)

Multi-state time-varying reliability evaluation of smart grid with flexible demand resources utilizing Lz transform

Science.gov (United States)

Jia, Heping; Jin, Wende; Ding, Yi; Song, Yonghua; Yu, Dezhao

2017-01-01

With the expanding proportion of renewable energy generation and development of smart grid technologies, flexible demand resources (FDRs) have been utilized as an approach to accommodating renewable energies. However, multiple uncertainties of FDRs may influence reliable and secure operation of smart grid. Multi-state reliability models for a single FDR and aggregating FDRs have been proposed in this paper with regard to responsive abilities for FDRs and random failures for both FDR devices and information system. The proposed reliability evaluation technique is based on Lz transform method which can formulate time-varying reliability indices. A modified IEEE-RTS has been utilized as an illustration of the proposed technique.

Reliability assessment and correlation analysis of evaluating orthodontic treatment outcome in Chinese patients

OpenAIRE

Song, Guang-Ying; Zhao, Zhi-He; Ding, Yin; Bai, Yu-Xing; Wang, Lin; He, Hong; Shen, Gang; Li, Wei-Ran; Baumrind, Sheldon; Geng, Zhi; Xu, Tian-Min

2013-01-01

This study aimed to assess the reliability of experienced Chinese orthodontists in evaluating treatment outcome and to determine the correlations between three diagnostic information sources. Sixty-nine experienced Chinese orthodontic specialists each evaluated the outcome of orthodontic treatment of 108 Chinese patients. Three different information sources: study casts (SC), lateral cephalometric X-ray images (LX) and facial photographs (PH) were generated at the end of treatment for 108 pat...

Evaluation of Smart Grid Technologies Employed for System Reliability Improvement: Pacific Northwest Smart Grid Demonstration Experience

Energy Technology Data Exchange (ETDEWEB)

Agalgaonkar, Yashodhan P.; Hammerstrom, Donald J.

2017-06-01

The Pacific Northwest Smart Grid Demonstration (PNWSGD) was a smart grid technology performance evaluation project that included multiple U.S. states and cooperation from multiple electric utilities in the northwest region. One of the local objectives for the project was to achieve improved distribution system reliability. Toward this end, some PNWSGD utilities automated their distribution systems, including the application of fault detection, isolation, and restoration and advanced metering infrastructure. In light of this investment, a major challenge was to establish a correlation between implementation of these smart grid technologies and actual improvements of distribution system reliability. This paper proposes using Welch’s t-test to objectively determine and quantify whether distribution system reliability is improving over time. The proposed methodology is generic, and it can be implemented by any utility after calculation of the standard reliability indices. The effectiveness of the proposed hypothesis testing approach is demonstrated through comprehensive practical results. It is believed that wider adoption of the proposed approach can help utilities to evaluate a realistic long-term performance of smart grid technologies.

Ceramics Analysis and Reliability Evaluation of Structures (CARES). Users and programmers manual

Science.gov (United States)

Nemeth, Noel N.; Manderscheid, Jane M.; Gyekenyesi, John P.

1990-01-01

This manual describes how to use the Ceramics Analysis and Reliability Evaluation of Structures (CARES) computer program. The primary function of the code is to calculate the fast fracture reliability or failure probability of macroscopically isotropic ceramic components. These components may be subjected to complex thermomechanical loadings, such as those found in heat engine applications. The program uses results from MSC/NASTRAN or ANSYS finite element analysis programs to evaluate component reliability due to inherent surface and/or volume type flaws. CARES utilizes the Batdorf model and the two-parameter Weibull cumulative distribution function to describe the effect of multiaxial stress states on material strength. The principle of independent action (PIA) and the Weibull normal stress averaging models are also included. Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities are estimated from four-point bend bar or unifrom uniaxial tensile specimen fracture strength data. Parameter estimation can be performed for single or multiple failure modes by using the least-square analysis or the maximum likelihood method. Kolmogorov-Smirnov and Anderson-Darling goodness-of-fit tests, ninety percent confidence intervals on the Weibull parameters, and Kanofsky-Srinivasan ninety percent confidence band values are also provided. The probabilistic fast-fracture theories used in CARES, along with the input and output for CARES, are described. Example problems to demonstrate various feature of the program are also included. This manual describes the MSC/NASTRAN version of the CARES program.

Blinded evaluation of interrater reliability of an operative competency assessment tool for direct laryngoscopy and rigid bronchoscopy.

Science.gov (United States)

Ishman, Stacey L; Benke, James R; Johnson, Kaalan Erik; Zur, Karen B; Jacobs, Ian N; Thorne, Marc C; Brown, David J; Lin, Sandra Y; Bhatti, Nasir; Deutsch, Ellen S

2012-10-01

OBJECTIVES To confirm interrater reliability using blinded evaluation of a skills-assessment instrument to assess the surgical performance of resident and fellow trainees performing pediatric direct laryngoscopy and rigid bronchoscopy in simulated models. DESIGN Prospective, paired, blinded observational validation study. SUBJECTS Paired observers from multiple institutions simultaneously evaluated residents and fellows who were performing surgery in an animal laboratory or using high-fidelity manikins. The evaluators had no previous affiliation with the residents and fellows and did not know their year of training. INTERVENTIONS One- and 2-page versions of an objective structured assessment of technical skills (OSATS) assessment instrument composed of global and a task-specific surgical items were used to evaluate surgical performance. RESULTS Fifty-two evaluations were completed by 17 attending evaluators. The instrument agreement for the 2-page assessment was 71.4% when measured as a binary variable (ie, competent vs not competent) (κ = 0.38; P = .08). Evaluation as a continuous variable revealed a 42.9% percentage agreement (κ = 0.18; P = .14). The intraclass correlation was 0.53, considered substantial/good interrater reliability (69% reliable). For the 1-page instrument, agreement was 77.4% when measured as a binary variable (κ = 0.53, P = .0015). Agreement when evaluated as a continuous measure was 71.0% (κ = 0.54, P formative feedback on operational competency.

Reliability Calculations

DEFF Research Database (Denmark)

Petersen, Kurt Erling

1986-01-01

Risk and reliability analysis is increasingly being used in evaluations of plant safety and plant reliability. The analysis can be performed either during the design process or during the operation time, with the purpose to improve the safety or the reliability. Due to plant complexity and safety...... and availability requirements, sophisticated tools, which are flexible and efficient, are needed. Such tools have been developed in the last 20 years and they have to be continuously refined to meet the growing requirements. Two different areas of application were analysed. In structural reliability probabilistic...... approaches have been introduced in some cases for the calculation of the reliability of structures or components. A new computer program has been developed based upon numerical integration in several variables. In systems reliability Monte Carlo simulation programs are used especially in analysis of very...

Comparação de métodos de imputação única e múltipla usando como exemplo um modelo de risco para mortalidade cirúrgica Comparison of simple and multiple imputation methods using a risk model for surgical mortality as example

Directory of Open Access Journals (Sweden)

Luciana Neves Nunes

2010-12-01

Full Text Available INTRODUÇÃO: A perda de informações é um problema frequente em estudos realizados na área da Saúde. Na literatura essa perda é chamada de missing data ou dados faltantes. Através da imputação dos dados faltantes são criados conjuntos de dados artificialmente completos que podem ser analisados por técnicas estatísticas tradicionais. O objetivo desse artigo foi comparar, em um exemplo baseado em dados reais, a utilização de três técnicas de imputações diferentes. MÉTODO: Os dados utilizados referem-se a um estudo de desenvolvimento de modelo de risco cirúrgico, sendo que o tamanho da amostra foi de 450 pacientes. Os métodos de imputação empregados foram duas imputações únicas e uma imputação múltipla (IM, e a suposição sobre o mecanismo de não-resposta foi MAR (Missing at Random. RESULTADOS: A variável com dados faltantes foi a albumina sérica, com 27,1% de perda. Os modelos obtidos pelas imputações únicas foram semelhantes entre si, mas diferentes dos obtidos com os dados imputados pela IM quanto à inclusão de variáveis nos modelos. CONCLUSÕES: Os resultados indicam que faz diferença levar em conta a relação da albumina com outras variáveis observadas, pois foram obtidos modelos diferentes nas imputações única e múltipla. A imputação única subestima a variabilidade, gerando intervalos de confiança mais estreitos. É importante se considerar o uso de métodos de imputação quando há dados faltantes, especialmente a IM que leva em conta a variabilidade entre imputações para as estimativas do modelo.INTRODUCTION: It is common for studies in health to face problems with missing data. Through imputation, complete data sets are built artificially and can be analyzed by traditional statistical analysis. The objective of this paper is to compare three types of imputation based on real data. METHODS: The data used came from a study on the development of risk models for surgical mortality. The

Structural Reliability Methods

DEFF Research Database (Denmark)

Ditlevsen, Ove Dalager; Madsen, H. O.

The structural reliability methods quantitatively treat the uncertainty of predicting the behaviour and properties of a structure given the uncertain properties of its geometry, materials, and the actions it is supposed to withstand. This book addresses the probabilistic methods for evaluation...... of structural reliability, including the theoretical basis for these methods. Partial safety factor codes under current practice are briefly introduced and discussed. A probabilistic code format for obtaining a formal reliability evaluation system that catches the most essential features of the nature...... of the uncertainties and their interplay is the developed, step-by-step. The concepts presented are illustrated by numerous examples throughout the text....

Evaluating abdominal core muscle fatigue: Assessment of the validity and reliability of the prone bridging test.

Science.gov (United States)

De Blaiser, C; De Ridder, R; Willems, T; Danneels, L; Vanden Bossche, L; Palmans, T; Roosen, P

2018-02-01

The aims of this study were to research the amplitude and median frequency characteristics of selected abdominal, back, and hip muscles of healthy subjects during a prone bridging endurance test, based on surface electromyography (sEMG), (a) to determine if the prone bridging test is a valid field test to measure abdominal muscle fatigue, and (b) to evaluate if the current method of administrating the prone bridging test is reliable. Thirty healthy subjects participated in this experiment. The sEMG activity of seven abdominal, back, and hip muscles was bilaterally measured. Normalized median frequencies were computed from the EMG power spectra. The prone bridging tests were repeated on separate days to evaluate inter and intratester reliability. Significant differences in normalized median frequency slope (NMF slope ) values between several abdominal, back, and hip muscles could be demonstrated. Moderate-to-high correlation coefficients were shown between NMF slope values and endurance time. Multiple backward linear regression revealed that the test endurance time could only be significantly predicted by the NMF slope of the rectus abdominis. Statistical analysis showed excellent reliability (ICC=0.87-0.89). The findings of this study support the validity and reliability of the prone bridging test for evaluating abdominal muscle fatigue. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Non-destructive Reliability Evaluation of Electronic Device by ESPI

International Nuclear Information System (INIS)

Yoon, Sung Un; Kim, Koung Suk; Kang, Ki Soo; Jo, Seon Hyung

2001-01-01

This paper propose electronic speckle pattern interferometry(ESPI) for reliability evaluation of electronic device. Especially, vibration problem in a fan of air conditioner, motor of washing machine and etc. is important factor to design the devices. But, it is difficult to apply previous method, accelerometer to the devices with complex geometry. ESPI, non-contact measurement technique applies a commercial fan of air conditioner to vibration analysis. Vibration mode shapes, natural frequency and the range of the frequency are decided and compared with that of FEM analysis. In mechanical deign of new product, ESPI adds weak point of previous method to supply effective design information

Evaluating and categorizing the reliability of distribution coefficient values in the sorption database (3)

International Nuclear Information System (INIS)

Ochs, Michael; Kunze, Susanne; Suyama, Tadahiro; Tachi, Yukio; Yui, Mikazu

2010-02-01

Sorption of radionuclides in bentonites and rocks is one of the key processes in the safe geological disposal of radioactive waste. Japan Atomic Energy Agency (JAEA) has developed sorption database (JAEA-SDB) which includes extensive compilation of sorption K d data by batch experiments, extracted from published literatures. JAEA published the first SDB as an important basis for the H12 performance assessment (PA), and has been continuing to improve and update the SDB in view of potential future data needs, focusing on assuring the desired quality level and practical applications to K d -setting for the geological environment. The JAEA-SDB includes more than 24,000 K d data which are related with various conditions and methods, and different reliabilities. Accordingly, the quality assuring (QA) and classifying guideline/criteria has been developed in order to evaluate the reliability of each K d value. The reliability of K d values of key radionuclides for bentonite and mudstone system has been already evaluated. To use these QA information, the new web-based JAEA-SDB was published in March, 2009. In this report, the QA/classification of selected entries for key radionuclides (Th, Np, Am, Se and Cs) in the JAEA-SDB was done following the approach/guideline defined in our previous report focusing granite rocks which are related to reference systems in H12 PA and possible applications in the context of URL activities, and Fe-oxide/hydroxide, Al-oxide/hydroxide existing widely in geological environment. As a result, the reliability of 1,373 K d values was evaluated and classified. This classification scheme is expected to make it possible to obtain quick overview of the available data from the SDB, and to have suitable access to the respective data for K d -setting in PA. (author)

[Development and reliability evaluation of an instrument to measure health-related quality of life in independent elderly].

Science.gov (United States)

Lima, Maria José Barbosa de; Portela, Margareth Crisóstomo

2010-08-01

This study presents an instrument, the health-related quality of life (HRQOL) profile for independent elderly, to measure the health-related quality of life of the functionally independent elderly assisted in the outpatient setting, based on the adaptation of four validated scales: Short-Form Health Survey (SF-36), Duke-UNC Health Profile (DUHP), Sickness Impact Profile (SIP), and Nottingham Health Profile (NHP). The study also evaluates the instrument's reliability based on its use by two different observers with a 15-day interval. The instrument includes five dimensions (health perception, symptoms, physical function, psychological function, and social function) and 45 items. Reliability evaluation of the QUASI instrument was based on interviews with 142 elderly outpatients in the city of Rio de Janeiro, Brazil. Prevalence-adjusted kappa statistic was used to assess all 45 items. Correlation was also calculated between overall scores and scores on individual dimensions. In the reliability evaluation, 39 of the 45 items showed prevalence-adjusted kappa greater than 0.60.

Building and integrating reliability models in a Reliability-Centered-Maintenance approach

International Nuclear Information System (INIS)

Verite, B.; Villain, B.; Venturini, V.; Hugonnard, S.; Bryla, P.

1998-03-01

Electricite de France (EDF) has recently developed its OMF-Structures method, designed to optimize preventive maintenance of passive structures such as pipes and support, based on risk. In particular, reliability performances of components need to be determined; it is a two-step process, consisting of a qualitative sort followed by a quantitative evaluation, involving two types of models. Initially, degradation models are widely used to exclude some components from the field of preventive maintenance. The reliability of the remaining components is then evaluated by means of quantitative reliability models. The results are then included in a risk indicator that is used to directly optimize preventive maintenance tasks. (author)

Systematic evaluation of the teaching qualities of Obstetrics and Gynecology faculty: reliability and validity of the SETQ tools.

Science.gov (United States)

van der Leeuw, Renée; Lombarts, Kiki; Heineman, Maas Jan; Arah, Onyebuchi

2011-05-03

The importance of effective clinical teaching for the quality of future patient care is globally understood. Due to recent changes in graduate medical education, new tools are needed to provide faculty with reliable and individualized feedback on their teaching qualities. This study validates two instruments underlying the System for Evaluation of Teaching Qualities (SETQ) aimed at measuring and improving the teaching qualities of obstetrics and gynecology faculty. This cross-sectional multi-center questionnaire study was set in seven general teaching hospitals and two academic medical centers in the Netherlands. Seventy-seven residents and 114 faculty were invited to complete the SETQ instruments in the duration of one month from September 2008 to September 2009. To assess reliability and validity of the instruments, we used exploratory factor analysis, inter-item correlation, reliability coefficient alpha and inter-scale correlations. We also compared composite scales from factor analysis to global ratings. Finally, the number of residents' evaluations needed per faculty for reliable assessments was calculated. A total of 613 evaluations were completed by 66 residents (85.7% response rate). 99 faculty (86.8% response rate) participated in self-evaluation. Factor analysis yielded five scales with high reliability (Cronbach's alpha for residents' and faculty): learning climate (0.86 and 0.75), professional attitude (0.89 and 0.81), communication of learning goals (0.89 and 0.82), evaluation of residents (0.87 and 0.79) and feedback (0.87 and 0.86). Item-total, inter-scale and scale-global rating correlation coefficients were significant (Pteaching qualities of obstetrics and gynecology faculty. Future research should examine improvement of teaching qualities when using SETQ.

Study of evaluation techniques of software configuration management and reliability

Energy Technology Data Exchange (ETDEWEB)

Youn, Cheong; Baek, Y. W.; Kim, H. C.; Han, H. C.; Choi, C. R. [Chungnam National Univ., Taejon (Korea, Republic of)

2001-03-15

The Study of activities to solve software safety and quality must be executed in base of establishing software development process for digitalized nuclear plant. Especially study of software testing and Verification and Validation must executed. For this purpose methodologies and tools which can improve software qualities are evaluated and software Testing, V and V and Configuration Management which can be applied to software life cycle are investigated. This study establish a guideline that can be used to assure software safety and reliability requirements in digitalized nuclear plant systems.

Methods for reliability evaluation of trust and reputation systems

Science.gov (United States)

Janiszewski, Marek B.

2016-09-01

Trust and reputation systems are a systematic approach to build security on the basis of observations of node's behaviour. Exchange of node's opinions about other nodes is very useful to indicate nodes which act selfishly or maliciously. The idea behind trust and reputation systems gets significance because of the fact that conventional security measures (based on cryptography) are often not sufficient. Trust and reputation systems can be used in various types of networks such as WSN, MANET, P2P and also in e-commerce applications. Trust and reputation systems give not only benefits but also could be a thread itself. Many attacks aim at trust and reputation systems exist, but such attacks still have not gain enough attention of research teams. Moreover, joint effects of many of known attacks have been determined as a very interesting field of research. Lack of an acknowledged methodology of evaluation of trust and reputation systems is a serious problem. This paper aims at presenting various approaches of evaluation such systems. This work also contains a description of generalization of many trust and reputation systems which can be used to evaluate reliability of such systems in the context of preventing various attacks.

Estimating past hepatitis C infection risk from reported risk factor histories: implications for imputing age of infection and modeling fibrosis progression

Directory of Open Access Journals (Sweden)

Busch Michael P

2007-12-01

Full Text Available Abstract Background Chronic hepatitis C virus infection is prevalent and often causes hepatic fibrosis, which can progress to cirrhosis and cause liver cancer or liver failure. Study of fibrosis progression often relies on imputing the time of infection, often as the reported age of first injection drug use. We sought to examine the accuracy of such imputation and implications for modeling factors that influence progression rates. Methods We analyzed cross-sectional data on hepatitis C antibody status and reported risk factor histories from two large studies, the Women's Interagency HIV Study and the Urban Health Study, using modern survival analysis methods for current status data to model past infection risk year by year. We compared fitted distributions of past infection risk to reported age of first injection drug use. Results Although injection drug use appeared to be a very strong risk factor, models for both studies showed that many subjects had considerable probability of having been infected substantially before or after their reported age of first injection drug use. Persons reporting younger age of first injection drug use were more likely to have been infected after, and persons reporting older age of first injection drug use were more likely to have been infected before. Conclusion In cross-sectional studies of fibrosis progression where date of HCV infection is estimated from risk factor histories, modern methods such as multiple imputation should be used to account for the substantial uncertainty about when infection occurred. The models presented here can provide the inputs needed by such methods. Using reported age of first injection drug use as the time of infection in studies of fibrosis progression is likely to produce a spuriously strong association of younger age of infection with slower rate of progression.

Reliability of the Matson Evaluation of Social Skills with Youngsters (MESSY) for Children with Autism Spectrum Disorders

Science.gov (United States)

Matson, Johnny L.; Horovitz, Max; Mahan, Sara; Fodstad, Jill

2013-01-01

The purpose of this paper was to update the psychometrics of the "Matson Evaluation of Social Skills for Youngsters" ("MESSY") with children with Autism Spectrum Disorders (ASD), specifically with respect to internal consistency, split-half reliability, and inter-rater reliability. In Study 1, 114 children with ASD (Autistic Disorder, Asperger's…

Reliability Engineering

CERN Document Server

Lazzaroni, Massimo

2012-01-01

This book gives a practical guide for designers and users in Information and Communication Technology context. In particular, in the first Section, the definition of the fundamental terms according to the international standards are given. Then, some theoretical concepts and reliability models are presented in Chapters 2 and 3: the aim is to evaluate performance for components and systems and reliability growth. Chapter 4, by introducing the laboratory tests, puts in evidence the reliability concept from the experimental point of view. In ICT context, the failure rate for a given system can be

Reliability and mechanical design

International Nuclear Information System (INIS)

Lemaire, Maurice

1997-01-01

A lot of results in mechanical design are obtained from a modelisation of physical reality and from a numerical solution which would lead to the evaluation of needs and resources. The goal of the reliability analysis is to evaluate the confidence which it is possible to grant to the chosen design through the calculation of a probability of failure linked to the retained scenario. Two types of analysis are proposed: the sensitivity analysis and the reliability analysis. Approximate methods are applicable to problems related to reliability, availability, maintainability and safety (RAMS)

Development and Reliability Evaluation of the Movement Rating Instrument for Virtual Reality Video Game Play.

Science.gov (United States)

Levac, Danielle; Nawrotek, Joanna; Deschenes, Emilie; Giguere, Tia; Serafin, Julie; Bilodeau, Martin; Sveistrup, Heidi

2016-06-01

Virtual reality active video games are increasingly popular physical therapy interventions for children with cerebral palsy. However, physical therapists require educational resources to support decision making about game selection to match individual patient goals. Quantifying the movements elicited during virtual reality active video game play can inform individualized game selection in pediatric rehabilitation. The objectives of this study were to develop and evaluate the feasibility and reliability of the Movement Rating Instrument for Virtual Reality Game Play (MRI-VRGP). Item generation occurred through an iterative process of literature review and sample videotape viewing. The MRI-VRGP includes 25 items quantifying upper extremity, lower extremity, and total body movements. A total of 176 videotaped 90-second game play sessions involving 7 typically developing children and 4 children with cerebral palsy were rated by 3 raters trained in MRI-VRGP use. Children played 8 games on 2 virtual reality and active video game systems. Intraclass correlation coefficients (ICCs) determined intra-rater and interrater reliability. Excellent intrarater reliability was evidenced by ICCs of >0.75 for 17 of the 25 items across the 3 raters. Interrater reliability estimates were less precise. Excellent interrater reliability was achieved for far reach upper extremity movements (ICC=0.92 [for right and ICC=0.90 for left) and for squat (ICC=0.80) and jump items (ICC=0.99), with 9 items achieving ICCs of >0.70, 12 items achieving ICCs of between 0.40 and 0.70, and 4 items achieving poor reliability (close-reach upper extremity-ICC=0.14 for right and ICC=0.07 for left) and single-leg stance (ICC=0.55 for right and ICC=0.27 for left). Poor video quality, differing item interpretations between raters, and difficulty quantifying the high-speed movements involved in game play affected reliability. With item definition clarification and further psychometric property evaluation, the MRI

Validity and Reliability of the Korean Version of the Utrecht Scale for Evaluation of Rehabilitation-Participation

Directory of Open Access Journals (Sweden)

Joo-Hyun Lee

2017-01-01

Full Text Available This study investigated the reliability and validity of the Korean version of the Utrecht Scale for Evaluation of Rehabilitation-Participation (K-USER-P in patients with stroke. Stroke patients participated in this study. The Utrecht Scale for Evaluation of Rehabilitation-Participation was translated from English into Korean. A total of 120 questionnaires involving the K-USER-P were distributed to rehabilitation hospitals and centers by mail. Of those, 100 questionnaires were returned and 67 were included in the final analysis after exclusion of questionnaires with insufficient responses. We analyzed the questionnaires for internal consistency, test-retest reliability, and construct validity. The results indicated that internal consistency coefficients of the frequency, restriction, and satisfaction domains were 0.69, 0.66, and 0.67, respectively. Test-retest reliability was 0.63, 0.45, and 0.71 for the three domains, respectively. Intercorrelations between the SF-12 and the London Handicap Scale were generally moderate to good. The Korean version of the Utrecht Scale for Evaluation of Rehabilitation-Participation can be used as a measure of the participation level of stroke patients in clinical practice and the local community.

Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes

KAUST Repository

Chatterjee, Nilanjan; Chen, Yi-Hau; Luo, Sheng; Carroll, Raymond J.

2009-01-01

Although prospective logistic regression is the standard method of analysis for case-control data, it has been recently noted that in genetic epidemiologic studies one can use the "retrospective" likelihood to gain major power by incorporating various population genetics model assumptions such as Hardy-Weinberg-Equilibrium (HWE), gene-gene and gene-environment independence. In this article we review these modern methods and contrast them with the more classical approaches through two types of applications (i) association tests for typed and untyped single nucleotide polymorphisms (SNPs) and (ii) estimation of haplotype effects and haplotype-environment interactions in the presence of haplotype-phase ambiguity. We provide novel insights to existing methods by construction of various score-tests and pseudo-likelihoods. In addition, we describe a novel two-stage method for analysis of untyped SNPs that can use any flexible external algorithm for genotype imputation followed by a powerful association test based on the retrospective likelihood. We illustrate applications of the methods using simulated and real data. © Institute of Mathematical Statistics, 2009.

Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes

KAUST Repository

Chatterjee, Nilanjan

2009-11-01

Although prospective logistic regression is the standard method of analysis for case-control data, it has been recently noted that in genetic epidemiologic studies one can use the "retrospective" likelihood to gain major power by incorporating various population genetics model assumptions such as Hardy-Weinberg-Equilibrium (HWE), gene-gene and gene-environment independence. In this article we review these modern methods and contrast them with the more classical approaches through two types of applications (i) association tests for typed and untyped single nucleotide polymorphisms (SNPs) and (ii) estimation of haplotype effects and haplotype-environment interactions in the presence of haplotype-phase ambiguity. We provide novel insights to existing methods by construction of various score-tests and pseudo-likelihoods. In addition, we describe a novel two-stage method for analysis of untyped SNPs that can use any flexible external algorithm for genotype imputation followed by a powerful association test based on the retrospective likelihood. We illustrate applications of the methods using simulated and real data. © Institute of Mathematical Statistics, 2009.

A prospective study assessing agreement and reliability of a geriatric evaluation

OpenAIRE

Locatelli, Isabella; Monod, St?fanie; Cornuz, Jacques; B?la, Christophe J.; Senn, Nicolas

2017-01-01

Background The present study takes place within a geriatric program, aiming at improving the diagnosis and management of geriatric syndromes in primary care. Within this program it was of prime importance to be able to rely on a robust and reproducible geriatric consultation to use as a gold standard for evaluating a primary care brief assessment tool. The specific objective of the present study was thus assessing the agreement and reliability of a comprehensive geriatric consultation. Method...

Power distribution system reliability evaluation using dagger-sampling Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Hu, Y.; Zhao, S.; Ma, Y. [North China Electric Power Univ., Hebei (China). Dept. of Electrical Engineering

2009-03-11

A dagger-sampling Monte Carlo simulation method was used to evaluate power distribution system reliability. The dagger-sampling technique was used to record the failure of a component as an incident and to determine its occurrence probability by generating incident samples using random numbers. The dagger sampling technique was combined with the direct sequential Monte Carlo method to calculate average values of load point indices and system indices. Results of the 2 methods with simulation times of up to 100,000 years were then compared. The comparative evaluation showed that less computing time was required using the dagger-sampling technique due to its higher convergence speed. When simulation times were 1000 years, the dagger-sampling method required 0.05 seconds to accomplish an evaluation, while the direct method required 0.27 seconds. 12 refs., 3 tabs., 4 figs.

Evaluating seismic reliability of Reinforced Concrete Bridge in view of their rehabilitation

Directory of Open Access Journals (Sweden)

Boubel Hasnae

2018-01-01

Full Text Available Considering in this work, a simplified methodology was proposed in order to evaluate seismic vulnerability of Reinforced Concrete Bridge. Reliability assessment of stress limits state and the applied loading which are assumed to be random variables. It is assumed that only their means and standard deviations are known while no information is available about their densities of probabilities. First Order Reliability Method is applied to a response surface representation of the stress limit state obtained through quadratic polynomial regression of finite element results. Then a parametric study is performed regarding the influence of the distributions of probabilities chosen to model the problem uncertainties for Reinforced Concrete Bridge. It is shown that the probability of failure depends largely on the chosen densities of probabilities, mainly in the useful domain of small failure probabilities.

Once is not enough : Establishing reliability criteria for teacher evaluation based on classroom observations

NARCIS (Netherlands)

van der Lans, Rikkert; van de Grift, Wim; van Veen, Klaas

2016-01-01

Classroom observation is the most implemented method to evaluate teaching. To ensure reliability, researchers often train observers extensively. However, schools have limited resources to train observers and often lesson observation is performed by limitedly trained or untrained colleagues. In this

Reliability of a functional test battery evaluating functionality, proprioception, and strength in recreational athletes with functional ankle instability.

Science.gov (United States)

Sekir, U; Yildiz, Y; Hazneci, B; Ors, F; Saka, T; Aydin, T

2008-12-01

In contrast to the single evaluation methods used in the past, the combination of multiple tests allows one to obtain a global assessment of the ankle joint. The aim of this study was to determine the reliability of the different tests in a functional test battery. Twenty-four male recreational athletes with unilateral functional ankle instability (FAI) were recruited for this study. One component of the test battery included five different functional ability tests. These tests included a single limb hopping course, single-legged and triple-legged hop for distance, and six and cross six meter hop for time. The ankle joint position sense and one leg standing test were used for evaluation of proprioception and sensorimotor control. The isokinetic strengths of the ankle invertor and evertor muscles were evaluated at a velocity of 120 degrees /s. The reliability of the test battery was assessed by calculating the intraclass correlation coefficient (ICC). Each subject was tested two times, with an interval of 3-5 days between the test sessions. The ICCs for ankle functional and proprioceptive ability showed high reliability (ICCs ranging from 0.94 to 0.98). Additionally, isokinetic ankle joint inversion and eversion strength measurements represented good to high reliability (ICCs between 0.82 and 0.98). The functional test battery investigated in this study proved to be a reliable tool for the assessment of athletes with functional ankle instability. Therefore, clinicians may obtain reliable information from the functional test battery during the assessment of ankle joint performance in patients with functional ankle instability.

Validity and Reliability of the Clinical Competency Evaluation Instrument for Use among Physiotherapy Students: Pilot study.

Science.gov (United States)

Muhamad, Zailani; Ramli, Ayiesah; Amat, Salleh

2015-05-01

The aim of this study was to determine the content validity, internal consistency, test-retest reliability and inter-rater reliability of the Clinical Competency Evaluation Instrument (CCEVI) in assessing the clinical performance of physiotherapy students. This study was carried out between June and September 2013 at University Kebangsaan Malaysia (UKM), Kuala Lumpur, Malaysia. A panel of 10 experts were identified to establish content validity by evaluating and rating each of the items used in the CCEVI with regards to their relevance in measuring students' clinical competency. A total of 50 UKM undergraduate physiotherapy students were assessed throughout their clinical placement to determine the construct validity of these items. The instrument's reliability was determined through a cross-sectional study involving a clinical performance assessment of 14 final-year undergraduate physiotherapy students. The content validity index of the entire CCEVI was 0.91, while the proportion of agreement on the content validity indices ranged from 0.83-1.00. The CCEVI construct validity was established with factor loading of ≥0.6, while internal consistency (Cronbach's alpha) overall was 0.97. Test-retest reliability of the CCEVI was confirmed with a Pearson's correlation range of 0.91-0.97 and an intraclass coefficient correlation range of 0.95-0.98. Inter-rater reliability of the CCEVI domains ranged from 0.59 to 0.97 on initial and subsequent assessments. This pilot study confirmed the content validity of the CCEVI. It showed high internal consistency, thereby providing evidence that the CCEVI has moderate to excellent inter-rater reliability. However, additional refinement in the wording of the CCEVI items, particularly in the domains of safety and documentation, is recommended to further improve the validity and reliability of the instrument.

A Reliability and Validity of an Instrument to Evaluate the School-Based Assessment System: A Pilot Study

Science.gov (United States)

Ghazali, Nor Hasnida Md

2016-01-01

A valid, reliable and practical instrument is needed to evaluate the implementation of the school-based assessment (SBA) system. The aim of this study is to develop and assess the validity and reliability of an instrument to measure the perception of teachers towards the SBA implementation in schools. The instrument is developed based on a…

A questionnaire to evaluate the impact of chronic diseases: validated translation and Illness Effects Questionnaire (IEQ reliability study

Directory of Open Access Journals (Sweden)

Patrícia Pinto Fonseca

2012-01-01

Full Text Available INTRODUCTION: Patients' perception about their health condition, mainly involving chronic diseases, has been investigated in many studies and it has been associated to depression, compliance with the treatment, quality of life and prognosis. The Illness Effects Questionnaire (IEQ is a tool which makes the standardized evaluation of patients' perception about their illness possible, so that it is brief and accessible to the different clinical settings. This work aims to begin the transcultural adaptation of the IEQ to Brazil through the validated translation and the reliability study. METHODS: The back-translation method and the test-retest reliability study were used in a sample of 30 adult patients under chronic hemodialysis. The reliability indexes were estimated using the Pearson, Spearman, Weighted Kappa and Cronbach's alpha coefficients. RESULTS: The semantic equivalence was reached through the validated translation. In this study, the reliability indexes obtained were respectively: 0.85 and 0.75 (p < 0.001; 0.68 and 0.92 (p < 0.0001. DISCUSSION: The reliability indexes obtained attest to the stability of responses in both evaluations. Additional procedures are necessary for the transcultural adaptation of the IEQ to be complete. CONCLUSION: The results indicate the translation validity and the reliability of the Brazilian version of the IEQ for the sample studied.

Reliability and cost evaluation of small isolated power systems containing photovoltaic and wind energy

Science.gov (United States)

Karki, Rajesh

Renewable energy application in electric power systems is growing rapidly worldwide due to enhanced public concerns for adverse environmental impacts and escalation in energy costs associated with the use of conventional energy sources. Photovoltaics and wind energy sources are being increasingly recognized as cost effective generation sources. A comprehensive evaluation of reliability and cost is required to analyze the actual benefits of utilizing these energy sources. The reliability aspects of utilizing renewable energy sources have largely been ignored in the past due the relatively insignificant contribution of these sources in major power systems, and consequently due to the lack of appropriate techniques. Renewable energy sources have the potential to play a significant role in the electrical energy requirements of small isolated power systems which are primarily supplied by costly diesel fuel. A relatively high renewable energy penetration can significantly reduce the system fuel costs but can also have considerable impact on the system reliability. Small isolated systems routinely plan their generating facilities using deterministic adequacy methods that cannot incorporate the highly erratic behavior of renewable energy sources. The utilization of a single probabilistic risk index has not been generally accepted in small isolated system evaluation despite its utilization in most large power utilities. Deterministic and probabilistic techniques are combined in this thesis using a system well-being approach to provide useful adequacy indices for small isolated systems that include renewable energy. This thesis presents an evaluation model for small isolated systems containing renewable energy sources by integrating simulation models that generate appropriate atmospheric data, evaluate chronological renewable power outputs and combine total available energy and load to provide useful system indices. A software tool SIPSREL+ has been developed which generates

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Science.gov (United States)

Horikoshi, Momoko; Mӓgi, Reedik; van de Bunt, Martijn; Surakka, Ida; Sarin, Antti-Pekka; Mahajan, Anubha; Marullo, Letizia; Thorleifsson, Gudmar; Hӓgg, Sara; Hottenga, Jouke-Jan; Ladenvall, Claes; Ried, Janina S; Winkler, Thomas W; Willems, Sara M; Pervjakova, Natalia; Esko, Tõnu; Beekman, Marian; Nelson, Christopher P; Willenborg, Christina; Wiltshire, Steven; Ferreira, Teresa; Fernandez, Juan; Gaulton, Kyle J; Steinthorsdottir, Valgerdur; Hamsten, Anders; Magnusson, Patrik K E; Willemsen, Gonneke; Milaneschi, Yuri; Robertson, Neil R; Groves, Christopher J; Bennett, Amanda J; Lehtimӓki, Terho; Viikari, Jorma S; Rung, Johan; Lyssenko, Valeriya; Perola, Markus; Heid, Iris M; Herder, Christian; Grallert, Harald; Müller-Nurasyid, Martina; Roden, Michael; Hypponen, Elina; Isaacs, Aaron; van Leeuwen, Elisabeth M; Karssen, Lennart C; Mihailov, Evelin; Houwing-Duistermaat, Jeanine J; de Craen, Anton J M; Deelen, Joris; Havulinna, Aki S; Blades, Matthew; Hengstenberg, Christian; Erdmann, Jeanette; Schunkert, Heribert; Kaprio, Jaakko; Tobin, Martin D; Samani, Nilesh J; Lind, Lars; Salomaa, Veikko; Lindgren, Cecilia M; Slagboom, P Eline; Metspalu, Andres; van Duijn, Cornelia M; Eriksson, Johan G; Peters, Annette; Gieger, Christian; Jula, Antti; Groop, Leif; Raitakari, Olli T; Power, Chris; Penninx, Brenda W J H; de Geus, Eco; Smit, Johannes H; Boomsma, Dorret I; Pedersen, Nancy L; Ingelsson, Erik; Thorsteinsdottir, Unnur; Stefansson, Kari; Ripatti, Samuli; Prokopenko, Inga; McCarthy, Mark I; Morris, Andrew P

2015-07-01

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

A fuzzy-based reliability approach to evaluate basic events of fault tree analysis for nuclear power plant probabilistic safety assessment

International Nuclear Information System (INIS)

Purba, Julwan Hendry

2014-01-01

Highlights: • We propose a fuzzy-based reliability approach to evaluate basic event reliabilities. • It implements the concepts of failure possibilities and fuzzy sets. • Experts evaluate basic event failure possibilities using qualitative words. • Triangular fuzzy numbers mathematically represent qualitative failure possibilities. • It is a very good alternative for conventional reliability approach. - Abstract: Fault tree analysis has been widely utilized as a tool for nuclear power plant probabilistic safety assessment. This analysis can be completed only if all basic events of the system fault tree have their quantitative failure rates or failure probabilities. However, it is difficult to obtain those failure data due to insufficient data, environment changing or new components. This study proposes a fuzzy-based reliability approach to evaluate basic events of system fault trees whose failure precise probability distributions of their lifetime to failures are not available. It applies the concept of failure possibilities to qualitatively evaluate basic events and the concept of fuzzy sets to quantitatively represent the corresponding failure possibilities. To demonstrate the feasibility and the effectiveness of the proposed approach, the actual basic event failure probabilities collected from the operational experiences of the David–Besse design of the Babcock and Wilcox reactor protection system fault tree are used to benchmark the failure probabilities generated by the proposed approach. The results confirm that the proposed fuzzy-based reliability approach arises as a suitable alternative for the conventional probabilistic reliability approach when basic events do not have the corresponding quantitative historical failure data for determining their reliability characteristics. Hence, it overcomes the limitation of the conventional fault tree analysis for nuclear power plant probabilistic safety assessment

Evaluating the reliability of predictions made using environmental transfer models

International Nuclear Information System (INIS)

1989-01-01

The development and application of mathematical models for predicting the consequences of releases of radionuclides into the environment from normal operations in the nuclear fuel cycle and in hypothetical accident conditions has increased dramatically in the last two decades. This Safety Practice publication has been prepared to provide guidance on the available methods for evaluating the reliability of environmental transfer model predictions. It provides a practical introduction of the subject and a particular emphasis has been given to worked examples in the text. It is intended to supplement existing IAEA publications on environmental assessment methodology. 60 refs, 17 figs, 12 tabs

Digital System Reliability Test for the Evaluation of safety Critical Software of Digital Reactor Protection System

Directory of Open Access Journals (Sweden)

Hyun-Kook Shin

2006-08-01

Full Text Available A new Digital Reactor Protection System (DRPS based on VME bus Single Board Computer has been developed by KOPEC to prevent software Common Mode Failure(CMF inside digital system. The new DRPS has been proved to be an effective digital safety system to prevent CMF by Defense-in-Depth and Diversity (DID&D analysis. However, for practical use in Nuclear Power Plants, the performance test and the reliability test are essential for the digital system qualification. In this study, a single channel of DRPS prototype has been manufactured for the evaluation of DRPS capabilities. The integrated functional tests are performed and the system reliability is analyzed and tested. The results of reliability test show that the application software of DRPS has a very high reliability compared with the analog reactor protection systems.

Improving Reliability of a Residency Interview Process

Science.gov (United States)

Serres, Michelle L.; Gundrum, Todd E.

2013-01-01

Objective. To improve the reliability and discrimination of a pharmacy resident interview evaluation form, and thereby improve the reliability of the interview process. Methods. In phase 1 of the study, authors used a Many-Facet Rasch Measurement model to optimize an existing evaluation form for reliability and discrimination. In phase 2, interviewer pairs used the modified evaluation form within 4 separate interview stations. In phase 3, 8 interviewers individually-evaluated each candidate in one-on-one interviews. Results. In phase 1, the evaluation form had a reliability of 0.98 with person separation of 6.56; reproducibly, the form separated applicants into 6 distinct groups. Using that form in phase 2 and 3, our largest variation source was candidates, while content specificity was the next largest variation source. The phase 2 g-coefficient was 0.787, while confirmatory phase 3 was 0.922. Process reliability improved with more stations despite fewer interviewers per station—impact of content specificity was greatly reduced with more interview stations. Conclusion. A more reliable, discriminating evaluation form was developed to evaluate candidates during resident interviews, and a process was designed that reduced the impact from content specificity. PMID:24159209

Improving reliability of a residency interview process.

Science.gov (United States)

Peeters, Michael J; Serres, Michelle L; Gundrum, Todd E

2013-10-14

To improve the reliability and discrimination of a pharmacy resident interview evaluation form, and thereby improve the reliability of the interview process. In phase 1 of the study, authors used a Many-Facet Rasch Measurement model to optimize an existing evaluation form for reliability and discrimination. In phase 2, interviewer pairs used the modified evaluation form within 4 separate interview stations. In phase 3, 8 interviewers individually-evaluated each candidate in one-on-one interviews. In phase 1, the evaluation form had a reliability of 0.98 with person separation of 6.56; reproducibly, the form separated applicants into 6 distinct groups. Using that form in phase 2 and 3, our largest variation source was candidates, while content specificity was the next largest variation source. The phase 2 g-coefficient was 0.787, while confirmatory phase 3 was 0.922. Process reliability improved with more stations despite fewer interviewers per station-impact of content specificity was greatly reduced with more interview stations. A more reliable, discriminating evaluation form was developed to evaluate candidates during resident interviews, and a process was designed that reduced the impact from content specificity.

A study on the quantitative evaluation of the reliability for safety critical software using Bayesian belief nets

International Nuclear Information System (INIS)

Eom, H. S.; Jang, S. C.; Ha, J. J.

2003-01-01

Despite the efforts to avoid undesirable risks, or at least to bring them under control in the world, new risks that are highly difficult to manage continue to emerge from the use of new technologies, such as the use of digital instrumentation and control (I and C) components in nuclear power plant. Whenever new risk issues came out by now, we have endeavored to find the most effective ways to reduce risks, or to allocate limited resources to do this. One of the major challenges is the reliability analysis of safety-critical software associated with digital safety systems. Though many activities such as testing, verification and validation (V and V) techniques have been carried out in the design stage of software, however, the process of quantitatively evaluating the reliability of safety-critical software has not yet been developed because of the irrelevance of the conventional software reliability techniques to apply for the digital safety systems. This paper focuses on the applicability of Bayesian Belief Net (BBN) techniques to quantitatively estimate the reliability of safety-critical software adopted in digital safety system. In this paper, a typical BBN model was constructed using the dedication process of the Commercial-Off-The-Shelf (COTS) installed by KAERI. In conclusion, the adoption of BBN technique can facilitate the process of evaluating the safety-critical software reliability in nuclear power plant, as well as provide very useful information (e.g., 'what if' analysis) associated with software reliability in the viewpoint of practicality

The water balance questionnaire: design, reliability and validity of a questionnaire to evaluate water balance in the general population.

Science.gov (United States)

Malisova, Olga; Bountziouka, Vassiliki; Panagiotakos, Demosthenes B; Zampelas, Antonis; Kapsokefalou, Maria

2012-03-01

There is a need to develop a questionnaire as a research tool for the evaluation of water balance in the general population. The water balance questionnaire (WBQ) was designed to evaluate water intake from fluid and solid foods and drinking water, and water loss from urine, faeces and sweat at sedentary conditions and physical activity. For validation purposes, the WBQ was administrated in 40 apparently healthy participants aged 22-57 years (37.5% males). Hydration indices in urine (24 h volume, osmolality, specific gravity, pH, colour) were measured through established procedures. Furthermore, the questionnaire was administered twice to 175 subjects to evaluate its reliability. Kendall's τ-b and the Bland and Altman method were used to assess the questionnaire's validity and reliability. The proposed WBQ to assess water balance in healthy individuals was found to be valid and reliable, and it could thus be a useful tool in future projects that aim to evaluate water balance.

A Novel OBDD-Based Reliability Evaluation Algorithm for Wireless Sensor Networks on the Multicast Model

Directory of Open Access Journals (Sweden)

Zongshuai Yan

2015-01-01

Full Text Available The two-terminal reliability calculation for wireless sensor networks (WSNs is a #P-hard problem. The reliability calculation of WSNs on the multicast model provides an even worse combinatorial explosion of node states with respect to the calculation of WSNs on the unicast model; many real WSNs require the multicast model to deliver information. This research first provides a formal definition for the WSN on the multicast model. Next, a symbolic OBDD_Multicast algorithm is proposed to evaluate the reliability of WSNs on the multicast model. Furthermore, our research on OBDD_Multicast construction avoids the problem of invalid expansion, which reduces the number of subnetworks by identifying the redundant paths of two adjacent nodes and s-t unconnected paths. Experiments show that the OBDD_Multicast both reduces the complexity of the WSN reliability analysis and has a lower running time than Xing’s OBDD- (ordered binary decision diagram- based algorithm.

[The external evaluation of study quality: the role in maintaining the reliability of laboratory information].

Science.gov (United States)

Men'shikov, V V

2013-08-01

The external evaluation of quality of clinical laboratory examinations was gradually introduced in USSR medical laboratories since 1970s. In Russia, in the middle of 1990 a unified all-national system of external evaluation quality was organized known as the Federal center of external evaluation of quality at the basis of laboratory of the state research center of preventive medicine. The main positions of policy in this area were neatly formulated in the guidance documents of ministry of Health. Nowadays, the center of external evaluation of quality proposes 100 and more types of control studies and permanently extends their specter starting from interests of different disciplines of clinical medicine. The consistent participation of laboratories in the cycles of external evaluation of quality intrinsically promotes improvement of indicators of properness and precision of analysis results and increases reliability of laboratory information. However, a significant percentage of laboratories does not participate at all in external evaluation of quality or takes part in control process irregularly and in limited number of tests. The managers of a number of medical organizations disregard the application of the proposed possibilities to increase reliability of laboratory information and limit financing of studies in the field of quality control. The article proposes to adopt the national standard on the basis of ISO 17043 "Evaluation of compliance. The common requirements of professional competence testing".

Reliability calculations

International Nuclear Information System (INIS)

Petersen, K.E.

1986-03-01

Risk and reliability analysis is increasingly being used in evaluations of plant safety and plant reliability. The analysis can be performed either during the design process or during the operation time, with the purpose to improve the safety or the reliability. Due to plant complexity and safety and availability requirements, sophisticated tools, which are flexible and efficient, are needed. Such tools have been developed in the last 20 years and they have to be continuously refined to meet the growing requirements. Two different areas of application were analysed. In structural reliability probabilistic approaches have been introduced in some cases for the calculation of the reliability of structures or components. A new computer program has been developed based upon numerical integration in several variables. In systems reliability Monte Carlo simulation programs are used especially in analysis of very complex systems. In order to increase the applicability of the programs variance reduction techniques can be applied to speed up the calculation process. Variance reduction techniques have been studied and procedures for implementation of importance sampling are suggested. (author)

Reliability evaluation of thermophysical properties from first-principles calculations.

Science.gov (United States)

Palumbo, Mauro; Fries, Suzana G; Dal Corso, Andrea; Kürmann, Fritz; Hickel, Tilmann; Neugebauer, Jürg

2014-08-20

Thermophysical properties, such as heat capacity, bulk modulus and thermal expansion, are of great importance for many technological applications and are traditionally determined experimentally. With the rapid development of computational methods, however, first-principles computed temperature-dependent data are nowadays accessible. We evaluate various computational realizations of such data in comparison to the experimental scatter. The work is focussed on the impact of different first-principles codes (QUANTUM ESPRESSO and VASP), pseudopotentials (ultrasoft and projector augmented wave) as well as phonon determination methods (linear response and direct force constant method) on these properties. Based on the analysis of data for two pure elements, Cr and Ni, consequences for the reliability of temperature-dependent first-principles data in computational thermodynamics are discussed.

Test-retest reliability of the isernhagen work systems functional capacity evaluation in healthy adults

NARCIS (Netherlands)

Reneman, MF; Brouwer, S; Meinema, A; Dijkstra, PU; Geertzen, JHB; Groothoff, JW

2004-01-01

Aim of this study was to investigate test-retest reliability of the Isernhagen Work System Functional Capacity Evaluation (IWS FCE) in healthy subjects. The IWS FCE consists of 28 tests that reflect work-related activities such as lifting, carrying, bending, etc. A convenience sample of 26 healthy

Reliable tool life measurements in turning - an application to cutting fluid efficiency evaluation

DEFF Research Database (Denmark)

Axinte, Dragos A.; Belluco, Walter; De Chiffre, Leonardo

2001-01-01

The paper proposes a method to obtain reliable measurements of tool life in turning, discussing some aspects related to experimental procedure and measurement accuracy. The method (i) allows and experimental determination of the extended Taylor's equation, with a limited set of experiments and (ii......) provides efficiency evaluation. Six cutting oils, five of which formulated from vegetable basestock, were evaluated in turning. Experiments were run in a range of cutting parameters. according to a 2, 3-1 factorial design, machining AISI 316L stainless steel with coated carbide tools. Tool life...

Study of evaluation techniques of software safety and reliability in nuclear power plants