bivariate measurement error: Topics by WorldWideScience.org

Sample records for bivariate measurement error

A bivariate measurement error model for semicontinuous and continuous variables: Application to nutritional epidemiology.

Science.gov (United States)

Kipnis, Victor; Freedman, Laurence S; Carroll, Raymond J; Midthune, Douglas

2016-03-01

Semicontinuous data in the form of a mixture of a large portion of zero values and continuously distributed positive values frequently arise in many areas of biostatistics. This article is motivated by the analysis of relationships between disease outcomes and intakes of episodically consumed dietary components. An important aspect of studies in nutritional epidemiology is that true diet is unobservable and commonly evaluated by food frequency questionnaires with substantial measurement error. Following the regression calibration approach for measurement error correction, unknown individual intakes in the risk model are replaced by their conditional expectations given mismeasured intakes and other model covariates. Those regression calibration predictors are estimated using short-term unbiased reference measurements in a calibration substudy. Since dietary intakes are often "energy-adjusted," e.g., by using ratios of the intake of interest to total energy intake, the correct estimation of the regression calibration predictor for each energy-adjusted episodically consumed dietary component requires modeling short-term reference measurements of the component (a semicontinuous variable), and energy (a continuous variable) simultaneously in a bivariate model. In this article, we develop such a bivariate model, together with its application to regression calibration. We illustrate the new methodology using data from the NIH-AARP Diet and Health Study (Schatzkin et al., 2001, American Journal of Epidemiology 154, 1119-1125), and also evaluate its performance in a simulation study. © 2015, The International Biometric Society.
Robust bivariate error detection in skewed data with application to historical radiosonde winds

KAUST Repository

Sun, Ying

2017-01-18

The global historical radiosonde archives date back to the 1920s and contain the only directly observed measurements of temperature, wind, and moisture in the upper atmosphere, but they contain many random errors. Most of the focus on cleaning these large datasets has been on temperatures, but winds are important inputs to climate models and in studies of wind climatology. The bivariate distribution of the wind vector does not have elliptical contours but is skewed and heavy-tailed, so we develop two methods for outlier detection based on the bivariate skew-t (BST) distribution, using either distance-based or contour-based approaches to flag observations as potential outliers. We develop a framework to robustly estimate the parameters of the BST and then show how the tuning parameter to get these estimates is chosen. In simulation, we compare our methods with one based on a bivariate normal distribution and a nonparametric approach based on the bagplot. We then apply all four methods to the winds observed for over 35,000 radiosonde launches at a single station and demonstrate differences in the number of observations flagged across eight pressure levels and through time. In this pilot study, the method based on the BST contours performs very well.
Robust bivariate error detection in skewed data with application to historical radiosonde winds

KAUST Repository

Sun, Ying; Hering, Amanda S.; Browning, Joshua M.

2017-01-01

The global historical radiosonde archives date back to the 1920s and contain the only directly observed measurements of temperature, wind, and moisture in the upper atmosphere, but they contain many random errors. Most of the focus on cleaning these large datasets has been on temperatures, but winds are important inputs to climate models and in studies of wind climatology. The bivariate distribution of the wind vector does not have elliptical contours but is skewed and heavy-tailed, so we develop two methods for outlier detection based on the bivariate skew-t (BST) distribution, using either distance-based or contour-based approaches to flag observations as potential outliers. We develop a framework to robustly estimate the parameters of the BST and then show how the tuning parameter to get these estimates is chosen. In simulation, we compare our methods with one based on a bivariate normal distribution and a nonparametric approach based on the bagplot. We then apply all four methods to the winds observed for over 35,000 radiosonde launches at a single station and demonstrate differences in the number of observations flagged across eight pressure levels and through time. In this pilot study, the method based on the BST contours performs very well.
A New Measure Of Bivariate Asymmetry And Its Evaluation

International Nuclear Information System (INIS)

Ferreira, Flavio Henn; Kolev, Nikolai Valtchev

2008-01-01

In this paper we propose a new measure of bivariate asymmetry, based on conditional correlation coefficients. A decomposition of the Pearson correlation coefficient in terms of its conditional versions is studied and an example of application of the proposed measure is given.
On bivariate geometric distribution

Directory of Open Access Journals (Sweden)

K. Jayakumar

2013-05-01

Full Text Available Characterizations of bivariate geometric distribution using univariate and bivariate geometric compounding are obtained. Autoregressive models with marginals as bivariate geometric distribution are developed. Various bivariate geometric distributions analogous to important bivariate exponential distributions like, Marshall-Olkin’s bivariate exponential, Downton’s bivariate exponential and Hawkes’ bivariate exponential are presented.
Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

KAUST Repository

Zhang, Saijuan; Krebs-Smith, Susan M.; Midthune, Douglas; Perez, Adriana; Buckman, Dennis W.; Kipnis, Victor; Freedman, Laurence S.; Dodd, Kevin W.; Carroll, Raymond J

2011-01-01

There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole
Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

KAUST Repository

Zhang, Saijuan

2011-01-06

There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole
Smoothing of the bivariate LOD score for non-normal quantitative traits.

Science.gov (United States)

Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

2005-12-30

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.
Approximation of bivariate copulas by patched bivariate Fréchet copulas

KAUST Repository

Zheng, Yanting; Yang, Jingping; Huang, Jianhua Z.

2011-01-01

Bivariate Fréchet (BF) copulas characterize dependence as a mixture of three simple structures: comonotonicity, independence and countermonotonicity. They are easily interpretable but have limitations when used as approximations to general dependence structures. To improve the approximation property of the BF copulas and keep the advantage of easy interpretation, we develop a new copula approximation scheme by using BF copulas locally and patching the local pieces together. Error bounds and a probabilistic interpretation of this approximation scheme are developed. The new approximation scheme is compared with several existing copula approximations, including shuffle of min, checkmin, checkerboard and Bernstein approximations and exhibits better performance, especially in characterizing the local dependence. The utility of the new approximation scheme in insurance and finance is illustrated in the computation of the rainbow option prices and stop-loss premiums. © 2010 Elsevier B.V.
Approximation of bivariate copulas by patched bivariate Fréchet copulas

KAUST Repository

Zheng, Yanting

2011-03-01

Bivariate Fréchet (BF) copulas characterize dependence as a mixture of three simple structures: comonotonicity, independence and countermonotonicity. They are easily interpretable but have limitations when used as approximations to general dependence structures. To improve the approximation property of the BF copulas and keep the advantage of easy interpretation, we develop a new copula approximation scheme by using BF copulas locally and patching the local pieces together. Error bounds and a probabilistic interpretation of this approximation scheme are developed. The new approximation scheme is compared with several existing copula approximations, including shuffle of min, checkmin, checkerboard and Bernstein approximations and exhibits better performance, especially in characterizing the local dependence. The utility of the new approximation scheme in insurance and finance is illustrated in the computation of the rainbow option prices and stop-loss premiums. © 2010 Elsevier B.V.
Two new bivariate zero-inflated generalized Poisson distributions with a flexible correlation structure

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Chi Zhang

2015-05-01

Full Text Available To model correlated bivariate count data with extra zero observations, this paper proposes two new bivariate zero-inflated generalized Poisson (ZIGP distributions by incorporating a multiplicative factor (or dependency parameter λ, named as Type I and Type II bivariate ZIGP distributions, respectively. The proposed distributions possess a flexible correlation structure and can be used to fit either positively or negatively correlated and either over- or under-dispersed count data, comparing to the existing models that can only fit positively correlated count data with over-dispersion. The two marginal distributions of Type I bivariate ZIGP share a common parameter of zero inflation while the two marginal distributions of Type II bivariate ZIGP have their own parameters of zero inflation, resulting in a much wider range of applications. The important distributional properties are explored and some useful statistical inference methods including maximum likelihood estimations of parameters, standard errors estimation, bootstrap confidence intervals and related testing hypotheses are developed for the two distributions. A real data are thoroughly analyzed by using the proposed distributions and statistical methods. Several simulation studies are conducted to evaluate the performance of the proposed methods.
Quantifying and handling errors in instrumental measurements using the measurement error theory

DEFF Research Database (Denmark)

Andersen, Charlotte Møller; Bro, R.; Brockhoff, P.B.

2003-01-01

. This is a new way of using the measurement error theory. Reliability ratios illustrate that the models for the two fish species are influenced differently by the error. However, the error seems to influence the predictions of the two reference measures in the same way. The effect of using replicated x...... measurements. A new general formula is given for how to correct the least squares regression coefficient when a different number of replicated x-measurements is used for prediction than for calibration. It is shown that the correction should be applied when the number of replicates in prediction is less than...
Correcting AUC for Measurement Error.

Science.gov (United States)

Rosner, Bernard; Tworoger, Shelley; Qiu, Weiliang

2015-12-01

Diagnostic biomarkers are used frequently in epidemiologic and clinical work. The ability of a diagnostic biomarker to discriminate between subjects who develop disease (cases) and subjects who do not (controls) is often measured by the area under the receiver operating characteristic curve (AUC). The diagnostic biomarkers are usually measured with error. Ignoring measurement error can cause biased estimation of AUC, which results in misleading interpretation of the efficacy of a diagnostic biomarker. Several methods have been proposed to correct AUC for measurement error, most of which required the normality assumption for the distributions of diagnostic biomarkers. In this article, we propose a new method to correct AUC for measurement error and derive approximate confidence limits for the corrected AUC. The proposed method does not require the normality assumption. Both real data analyses and simulation studies show good performance of the proposed measurement error correction method.
Bivariate value-at-risk

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Giuseppe Arbia

2007-10-01

Full Text Available In this paper we extend the concept of Value-at-risk (VaR to bivariate return distributions in order to obtain measures of the market risk of an asset taking into account additional features linked to downside risk exposure. We first present a general definition of risk as the probability of an adverse event over a random distribution and we then introduce a measure of market risk (b-VaR that admits the traditional b of an asset in portfolio management as a special case when asset returns are normally distributed. Empirical evidences are provided by using Italian stock market data.
[Analysis of intrusion errors in free recall].

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Diesfeldt, H F A

2017-06-01

Extra-list intrusion errors during five trials of the eight-word list-learning task of the Amsterdam Dementia Screening Test (ADST) were investigated in 823 consecutive psychogeriatric patients (87.1% suffering from major neurocognitive disorder). Almost half of the participants (45.9%) produced one or more intrusion errors on the verbal recall test. Correct responses were lower when subjects made intrusion errors, but learning slopes did not differ between subjects who committed intrusion errors and those who did not so. Bivariate regression analyses revealed that participants who committed intrusion errors were more deficient on measures of eight-word recognition memory, delayed visual recognition and tests of executive control (the Behavioral Dyscontrol Scale and the ADST-Graphical Sequences as measures of response inhibition). Using hierarchical multiple regression, only free recall and delayed visual recognition retained an independent effect in the association with intrusion errors, such that deficient scores on tests of episodic memory were sufficient to explain the occurrence of intrusion errors. Measures of inhibitory control did not add significantly to the explanation of intrusion errors in free recall, which makes insufficient strength of memory traces rather than a primary deficit in inhibition the preferred account for intrusion errors in free recall.
Stress-strength reliability for general bivariate distributions

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Alaa H. Abdel-Hamid

2016-10-01

Full Text Available An expression for the stress-strength reliability R=P(X1bivariate distribution. Such distribution includes bivariate compound Weibull, bivariate compound Gompertz, bivariate compound Pareto, among others. In the parametric case, the maximum likelihood estimates of the parameters and reliability function R are obtained. In the non-parametric case, point and interval estimates of R are developed using Govindarajulu's asymptotic distribution-free method when X1 and X2 are dependent. An example is given when the population distribution is bivariate compound Weibull. Simulation is performed, based on different sample sizes to study the performance of estimates.
Compact disk error measurements

Science.gov (United States)

Howe, D.; Harriman, K.; Tehranchi, B.

1993-01-01

The objectives of this project are as follows: provide hardware and software that will perform simple, real-time, high resolution (single-byte) measurement of the error burst and good data gap statistics seen by a photoCD player read channel when recorded CD write-once discs of variable quality (i.e., condition) are being read; extend the above system to enable measurement of the hard decision (i.e., 1-bit error flags) and soft decision (i.e., 2-bit error flags) decoding information that is produced/used by the Cross Interleaved - Reed - Solomon - Code (CIRC) block decoder employed in the photoCD player read channel; construct a model that uses data obtained via the systems described above to produce meaningful estimates of output error rates (due to both uncorrected ECC words and misdecoded ECC words) when a CD disc having specific (measured) error statistics is read (completion date to be determined); and check the hypothesis that current adaptive CIRC block decoders are optimized for pressed (DAD/ROM) CD discs. If warranted, do a conceptual design of an adaptive CIRC decoder that is optimized for write-once CD discs.
Quantile Regression With Measurement Error

KAUST Repository

Wei, Ying

2009-08-27

Regression quantiles can be substantially biased when the covariates are measured with error. In this paper we propose a new method that produces consistent linear quantile estimation in the presence of covariate measurement error. The method corrects the measurement error induced bias by constructing joint estimating equations that simultaneously hold for all the quantile levels. An iterative EM-type estimation algorithm to obtain the solutions to such joint estimation equations is provided. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a longitudinal study with an unusual measurement error structure. © 2009 American Statistical Association.
Parameter estimation and statistical test of geographically weighted bivariate Poisson inverse Gaussian regression models

Science.gov (United States)

Amalia, Junita; Purhadi, Otok, Bambang Widjanarko

2017-11-01

Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.
Bivariate discrete beta Kernel graduation of mortality data.

Science.gov (United States)

Mazza, Angelo; Punzo, Antonio

2015-07-01

Various parametric/nonparametric techniques have been proposed in literature to graduate mortality data as a function of age. Nonparametric approaches, as for example kernel smoothing regression, are often preferred because they do not assume any particular mortality law. Among the existing kernel smoothing approaches, the recently proposed (univariate) discrete beta kernel smoother has been shown to provide some benefits. Bivariate graduation, over age and calendar years or durations, is common practice in demography and actuarial sciences. In this paper, we generalize the discrete beta kernel smoother to the bivariate case, and we introduce an adaptive bandwidth variant that may provide additional benefits when data on exposures to the risk of death are available; furthermore, we outline a cross-validation procedure for bandwidths selection. Using simulations studies, we compare the bivariate approach proposed here with its corresponding univariate formulation and with two popular nonparametric bivariate graduation techniques, based on Epanechnikov kernels and on P-splines. To make simulations realistic, a bivariate dataset, based on probabilities of dying recorded for the US males, is used. Simulations have confirmed the gain in performance of the new bivariate approach with respect to both the univariate and the bivariate competitors.

Redundant measurements for controlling errors

International Nuclear Information System (INIS)

Ehinger, M.H.; Crawford, J.M.; Madeen, M.L.

1979-07-01

Current federal regulations for nuclear materials control require consideration of operating data as part of the quality control program and limits of error propagation. Recent work at the BNFP has revealed that operating data are subject to a number of measurement problems which are very difficult to detect and even more difficult to correct in a timely manner. Thus error estimates based on operational data reflect those problems. During the FY 1978 and FY 1979 R and D demonstration runs at the BNFP, redundant measurement techniques were shown to be effective in detecting these problems to allow corrective action. The net effect is a reduction in measurement errors and a significant increase in measurement sensitivity. Results show that normal operation process control measurements, in conjunction with routine accountability measurements, are sensitive problem indicators when incorporated in a redundant measurement program
Measurement error in a single regressor

NARCIS (Netherlands)

Meijer, H.J.; Wansbeek, T.J.

2000-01-01

For the setting of multiple regression with measurement error in a single regressor, we present some very simple formulas to assess the result that one may expect when correcting for measurement error. It is shown where the corrected estimated regression coefficients and the error variance may lie,
Impact of Measurement Error on Synchrophasor Applications

Energy Technology Data Exchange (ETDEWEB)

Liu, Yilu [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gracia, Jose R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ewing, Paul D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Zhao, Jiecheng [Univ. of Tennessee, Knoxville, TN (United States); Tan, Jin [Univ. of Tennessee, Knoxville, TN (United States); Wu, Ling [Univ. of Tennessee, Knoxville, TN (United States); Zhan, Lingwei [Univ. of Tennessee, Knoxville, TN (United States)

2015-07-01

Phasor measurement units (PMUs), a type of synchrophasor, are powerful diagnostic tools that can help avert catastrophic failures in the power grid. Because of this, PMU measurement errors are particularly worrisome. This report examines the internal and external factors contributing to PMU phase angle and frequency measurement errors and gives a reasonable explanation for them. It also analyzes the impact of those measurement errors on several synchrophasor applications: event location detection, oscillation detection, islanding detection, and dynamic line rating. The primary finding is that dynamic line rating is more likely to be influenced by measurement error. Other findings include the possibility of reporting nonoscillatory activity as an oscillation as the result of error, failing to detect oscillations submerged by error, and the unlikely impact of error on event location and islanding detection.
An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

Science.gov (United States)

Campbell, C. W.

1983-01-01

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.
Errors in practical measurement in surveying, engineering, and technology

International Nuclear Information System (INIS)

Barry, B.A.; Morris, M.D.

1991-01-01

This book discusses statistical measurement, error theory, and statistical error analysis. The topics of the book include an introduction to measurement, measurement errors, the reliability of measurements, probability theory of errors, measures of reliability, reliability of repeated measurements, propagation of errors in computing, errors and weights, practical application of the theory of errors in measurement, two-dimensional errors and includes a bibliography. Appendices are included which address significant figures in measurement, basic concepts of probability and the normal probability curve, writing a sample specification for a procedure, classification, standards of accuracy, and general specifications of geodetic control surveys, the geoid, the frequency distribution curve and the computer and calculator solution of problems
Modeling the probability distribution of positional errors incurred by residential address geocoding

Directory of Open Access Journals (Sweden)

Mazumdar Soumya

2007-01-01

Full Text Available Abstract Background The assignment of a point-level geocode to subjects' residences is an important data assimilation component of many geographic public health studies. Often, these assignments are made by a method known as automated geocoding, which attempts to match each subject's address to an address-ranged street segment georeferenced within a streetline database and then interpolate the position of the address along that segment. Unfortunately, this process results in positional errors. Our study sought to model the probability distribution of positional errors associated with automated geocoding and E911 geocoding. Results Positional errors were determined for 1423 rural addresses in Carroll County, Iowa as the vector difference between each 100%-matched automated geocode and its true location as determined by orthophoto and parcel information. Errors were also determined for 1449 60%-matched geocodes and 2354 E911 geocodes. Huge (> 15 km outliers occurred among the 60%-matched geocoding errors; outliers occurred for the other two types of geocoding errors also but were much smaller. E911 geocoding was more accurate (median error length = 44 m than 100%-matched automated geocoding (median error length = 168 m. The empirical distributions of positional errors associated with 100%-matched automated geocoding and E911 geocoding exhibited a distinctive Greek-cross shape and had many other interesting features that were not capable of being fitted adequately by a single bivariate normal or t distribution. However, mixtures of t distributions with two or three components fit the errors very well. Conclusion Mixtures of bivariate t distributions with few components appear to be flexible enough to fit many positional error datasets associated with geocoding, yet parsimonious enough to be feasible for nascent applications of measurement-error methodology to spatial epidemiology.
Measurement system and model for simultaneously measuring 6DOF geometric errors.

Science.gov (United States)

Zhao, Yuqiong; Zhang, Bin; Feng, Qibo

2017-09-04

A measurement system to simultaneously measure six degree-of-freedom (6DOF) geometric errors is proposed. The measurement method is based on a combination of mono-frequency laser interferometry and laser fiber collimation. A simpler and more integrated optical configuration is designed. To compensate for the measurement errors introduced by error crosstalk, element fabrication error, laser beam drift, and nonparallelism of two measurement beam, a unified measurement model, which can improve the measurement accuracy, is deduced and established using the ray-tracing method. A numerical simulation using the optical design software Zemax is conducted, and the results verify the correctness of the model. Several experiments are performed to demonstrate the feasibility and effectiveness of the proposed system and measurement model.
Evolution of association between renal and liver functions while awaiting heart transplant: An application using a bivariate multiphase nonlinear mixed effects model.

Science.gov (United States)

Rajeswaran, Jeevanantham; Blackstone, Eugene H; Barnard, John

2018-07-01

In many longitudinal follow-up studies, we observe more than one longitudinal outcome. Impaired renal and liver functions are indicators of poor clinical outcomes for patients who are on mechanical circulatory support and awaiting heart transplant. Hence, monitoring organ functions while waiting for heart transplant is an integral part of patient management. Longitudinal measurements of bilirubin can be used as a marker for liver function and glomerular filtration rate for renal function. We derive an approximation to evolution of association between these two organ functions using a bivariate nonlinear mixed effects model for continuous longitudinal measurements, where the two submodels are linked by a common distribution of time-dependent latent variables and a common distribution of measurement errors.
KMRR thermal power measurement error estimation

International Nuclear Information System (INIS)

Rhee, B.W.; Sim, B.S.; Lim, I.C.; Oh, S.K.

1990-01-01

The thermal power measurement error of the Korea Multi-purpose Research Reactor has been estimated by a statistical Monte Carlo method, and compared with those obtained by the other methods including deterministic and statistical approaches. The results show that the specified thermal power measurement error of 5% cannot be achieved if the commercial RTDs are used to measure the coolant temperatures of the secondary cooling system and the error can be reduced below the requirement if the commercial RTDs are replaced by the precision RTDs. The possible range of the thermal power control operation has been identified to be from 100% to 20% of full power
The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R.

Science.gov (United States)

Vogelgesang, Felicitas; Schlattmann, Peter; Dewey, Marc

2018-05-01

Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity - the two outcomes of interest in meta-analyses of diagnostic accuracy studies - utilizing random effects. Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach. Schattauer GmbH.
Bivariate Kumaraswamy Models via Modified FGM Copulas: Properties and Applications

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Indranil Ghosh

2017-11-01

Full Text Available A copula is a useful tool for constructing bivariate and/or multivariate distributions. In this article, we consider a new modified class of FGM (Farlie–Gumbel–Morgenstern bivariate copula for constructing several different bivariate Kumaraswamy type copulas and discuss their structural properties, including dependence structures. It is established that construction of bivariate distributions by this method allows for greater flexibility in the values of Spearman’s correlation coefficient, ρ and Kendall’s τ .
An Affine Invariant Bivariate Version of the Sign Test.

Science.gov (United States)

1987-06-01

words: affine invariance, bivariate quantile, bivariate symmetry, model,. generalized median, influence function , permutation test, normal efficiency...calculate a bivariate version of the influence function , and the resulting form is bounded, as is the case for the univartate sign test, and shows the...terms of a blvariate analogue of IHmpel’s (1974) influence function . The latter, though usually defined as a von-Mises derivative of certain
The error model and experiment of measuring angular position error based on laser collimation

Science.gov (United States)

Cai, Yangyang; Yang, Jing; Li, Jiakun; Feng, Qibo

2018-01-01

Rotary axis is the reference component of rotation motion. Angular position error is the most critical factor which impair the machining precision among the six degree-of-freedom (DOF) geometric errors of rotary axis. In this paper, the measuring method of angular position error of rotary axis based on laser collimation is thoroughly researched, the error model is established and 360 ° full range measurement is realized by using the high precision servo turntable. The change of space attitude of each moving part is described accurately by the 3×3 transformation matrices and the influences of various factors on the measurement results is analyzed in detail. Experiments results show that the measurement method can achieve high measurement accuracy and large measurement range.
Comparing Measurement Error between Two Different Methods of Measurement of Various Magnitudes

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Zavorsky, Gerald S.

2010-01-01

Measurement error is a common problem in several fields of research such as medicine, physiology, and exercise science. The standard deviation of repeated measurements on the same person is the measurement error. One way of presenting measurement error is called the repeatability, which is 2.77 multiplied by the within subject standard deviation.…
Fusing metabolomics data sets with heterogeneous measurement errors

Science.gov (United States)

Waaijenborg, Sandra; Korobko, Oksana; Willems van Dijk, Ko; Lips, Mirjam; Hankemeier, Thomas; Wilderjans, Tom F.; Smilde, Age K.

2018-01-01

Combining different metabolomics platforms can contribute significantly to the discovery of complementary processes expressed under different conditions. However, analysing the fused data might be hampered by the difference in their quality. In metabolomics data, one often observes that measurement errors increase with increasing measurement level and that different platforms have different measurement error variance. In this paper we compare three different approaches to correct for the measurement error heterogeneity, by transformation of the raw data, by weighted filtering before modelling and by a modelling approach using a weighted sum of residuals. For an illustration of these different approaches we analyse data from healthy obese and diabetic obese individuals, obtained from two metabolomics platforms. Concluding, the filtering and modelling approaches that both estimate a model of the measurement error did not outperform the data transformation approaches for this application. This is probably due to the limited difference in measurement error and the fact that estimation of measurement error models is unstable due to the small number of repeats available. A transformation of the data improves the classification of the two groups. PMID:29698490
STUDI PERBANDINGAN ANTARA ALGORITMA BIVARIATE MARGINAL DISTRIBUTION DENGAN ALGORITMA GENETIKA

Directory of Open Access Journals (Sweden)

Chastine Fatichah

2006-01-01

Full Text Available Bivariate Marginal Distribution Algorithm is extended from Estimation of Distribution Algorithm. This heuristic algorithm proposes the new approach for recombination of generate new individual that without crossover and mutation process such as genetic algorithm. Bivariate Marginal Distribution Algorithm uses connectivity variable the pair gene for recombination of generate new individual. Connectivity between variable is doing along optimization process. In this research, genetic algorithm performance with one point crossover is compared with Bivariate Marginal Distribution Algorithm performance in case Onemax, De Jong F2 function, and Traveling Salesman Problem. In this research, experimental results have shown performance the both algorithm is dependence of parameter respectively and also population size that used. For Onemax case with size small problem, Genetic Algorithm perform better with small number of iteration and more fast for get optimum result. However, Bivariate Marginal Distribution Algorithm perform better of result optimization for case Onemax with huge size problem. For De Jong F2 function, Genetic Algorithm perform better from Bivariate Marginal Distribution Algorithm of a number of iteration and time. For case Traveling Salesman Problem, Bivariate Marginal Distribution Algorithm have shown perform better from Genetic Algorithm of optimization result. Abstract in Bahasa Indonesia : Bivariate Marginal Distribution Algorithm merupakan perkembangan lebih lanjut dari Estimation of Distribution Algorithm. Algoritma heuristik ini mengenalkan pendekatan baru dalam melakukan rekombinasi untuk membentuk individu baru, yaitu tidak menggunakan proses crossover dan mutasi seperti pada Genetic Algorithm. Bivariate Marginal Distribution Algorithm menggunakan keterkaitan pasangan variabel dalam melakukan rekombinasi untuk membentuk individu baru. Keterkaitan antar variabel tersebut ditemukan selama proses optimasi berlangsung. Aplikasi yang
Comparison of Model Reliabilities from Single-Step and Bivariate Blending Methods

DEFF Research Database (Denmark)

Taskinen, Matti; Mäntysaari, Esa; Lidauer, Martin

2013-01-01

Model based reliabilities in genetic evaluation are compared between three methods: animal model BLUP, single-step BLUP, and bivariate blending after genomic BLUP. The original bivariate blending is revised in this work to better account animal models. The study data is extracted from...... be calculated. Model reliabilities by the single-step and the bivariate blending methods were higher than by animal model due to genomic information. Compared to the single-step method, the bivariate blending method reliability estimates were, in general, lower. Computationally bivariate blending method was......, on the other hand, lighter than the single-step method....
Measurement Errors and Uncertainties Theory and Practice

CERN Document Server

Rabinovich, Semyon G

2006-01-01

Measurement Errors and Uncertainties addresses the most important problems that physicists and engineers encounter when estimating errors and uncertainty. Building from the fundamentals of measurement theory, the author develops the theory of accuracy of measurements and offers a wealth of practical recommendations and examples of applications. This new edition covers a wide range of subjects, including: - Basic concepts of metrology - Measuring instruments characterization, standardization and calibration -Estimation of errors and uncertainty of single and multiple measurements - Modern probability-based methods of estimating measurement uncertainty With this new edition, the author completes the development of the new theory of indirect measurements. This theory provides more accurate and efficient methods for processing indirect measurement data. It eliminates the need to calculate the correlation coefficient - a stumbling block in measurement data processing - and offers for the first time a way to obtain...
Error calculations statistics in radioactive measurements

International Nuclear Information System (INIS)

Verdera, Silvia

1994-01-01

Basic approach and procedures frequently used in the practice of radioactive measurements.Statistical principles applied are part of Good radiopharmaceutical Practices and quality assurance.Concept of error, classification as systematic and random errors.Statistic fundamentals,probability theories, populations distributions, Bernoulli, Poisson,Gauss, t-test distribution,Ξ2 test, error propagation based on analysis of variance.Bibliography.z table,t-test table, Poisson index ,Ξ2 test
Radiation risk estimation based on measurement error models

CERN Document Server

Masiuk, Sergii; Shklyar, Sergiy; Chepurny, Mykola; Likhtarov, Illya

2017-01-01

This monograph discusses statistics and risk estimates applied to radiation damage under the presence of measurement errors. The first part covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk estimation in models with measurement errors is considered. Efficiency of the methods presented is verified using data from radio-epidemiological studies.

Measuring worst-case errors in a robot workcell

International Nuclear Information System (INIS)

Simon, R.W.; Brost, R.C.; Kholwadwala, D.K.

1997-10-01

Errors in model parameters, sensing, and control are inevitably present in real robot systems. These errors must be considered in order to automatically plan robust solutions to many manipulation tasks. Lozano-Perez, Mason, and Taylor proposed a formal method for synthesizing robust actions in the presence of uncertainty; this method has been extended by several subsequent researchers. All of these results presume the existence of worst-case error bounds that describe the maximum possible deviation between the robot's model of the world and reality. This paper examines the problem of measuring these error bounds for a real robot workcell. These measurements are difficult, because of the desire to completely contain all possible deviations while avoiding bounds that are overly conservative. The authors present a detailed description of a series of experiments that characterize and quantify the possible errors in visual sensing and motion control for a robot workcell equipped with standard industrial robot hardware. In addition to providing a means for measuring these specific errors, these experiments shed light on the general problem of measuring worst-case errors
Errors of Inference Due to Errors of Measurement.

Science.gov (United States)

Linn, Robert L.; Werts, Charles E.

Failure to consider errors of measurement when using partial correlation or analysis of covariance techniques can result in erroneous conclusions. Certain aspects of this problem are discussed and particular attention is given to issues raised in a recent article by Brewar, Campbell, and Crano. (Author)
Measurement Error in Education and Growth Regressions

NARCIS (Netherlands)

Portela, M.; Teulings, C.N.; Alessie, R.

The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations
Measurement error in education and growth regressions

NARCIS (Netherlands)

Portela, Miguel; Teulings, Coen; Alessie, R.

2004-01-01

The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations
Fixturing error measurement and analysis using CMMs

International Nuclear Information System (INIS)

Wang, Y; Chen, X; Gindy, N

2005-01-01

Influence of fixture on the errors of a machined surface can be very significant. The machined surface errors generated during machining can be measured by using a coordinate measurement machine (CMM) through the displacements of three coordinate systems on a fixture-workpiece pair in relation to the deviation of the machined surface. The surface errors consist of the component movement, component twist, deviation between actual machined surface and defined tool path. A turbine blade fixture for grinding operation is used for case study
Radon measurements-discussion of error estimates for selected methods

International Nuclear Information System (INIS)

Zhukovsky, Michael; Onischenko, Alexandra; Bastrikov, Vladislav

2010-01-01

The main sources of uncertainties for grab sampling, short-term (charcoal canisters) and long term (track detectors) measurements are: systematic bias of reference equipment; random Poisson and non-Poisson errors during calibration; random Poisson and non-Poisson errors during measurements. The origins of non-Poisson random errors during calibration are different for different kinds of instrumental measurements. The main sources of uncertainties for retrospective measurements conducted by surface traps techniques can be divided in two groups: errors of surface 210 Pb ( 210 Po) activity measurements and uncertainties of transfer from 210 Pb surface activity in glass objects to average radon concentration during this object exposure. It's shown that total measurement error of surface trap retrospective technique can be decreased to 35%.
Covariate analysis of bivariate survival data

Energy Technology Data Exchange (ETDEWEB)

Bennett, L.E.

1992-01-01

The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.
Incorporating measurement error in n=1 psychological autoregressive modeling

NARCIS (Netherlands)

Schuurman, Noemi K.; Houtveen, Jan H.; Hamaker, Ellen L.

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive
Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies.

Science.gov (United States)

Goldman, Gretchen T; Mulholland, James A; Russell, Armistead G; Strickland, Matthew J; Klein, Mitchel; Waller, Lance A; Tolbert, Paige E

2011-06-22

Two distinctly different types of measurement error are Berkson and classical. Impacts of measurement error in epidemiologic studies of ambient air pollution are expected to depend on error type. We characterize measurement error due to instrument imprecision and spatial variability as multiplicative (i.e. additive on the log scale) and model it over a range of error types to assess impacts on risk ratio estimates both on a per measurement unit basis and on a per interquartile range (IQR) basis in a time-series study in Atlanta. Daily measures of twelve ambient air pollutants were analyzed: NO2, NOx, O3, SO2, CO, PM10 mass, PM2.5 mass, and PM2.5 components sulfate, nitrate, ammonium, elemental carbon and organic carbon. Semivariogram analysis was applied to assess spatial variability. Error due to this spatial variability was added to a reference pollutant time-series on the log scale using Monte Carlo simulations. Each of these time-series was exponentiated and introduced to a Poisson generalized linear model of cardiovascular disease emergency department visits. Measurement error resulted in reduced statistical significance for the risk ratio estimates for all amounts (corresponding to different pollutants) and types of error. When modelled as classical-type error, risk ratios were attenuated, particularly for primary air pollutants, with average attenuation in risk ratios on a per unit of measurement basis ranging from 18% to 92% and on an IQR basis ranging from 18% to 86%. When modelled as Berkson-type error, risk ratios per unit of measurement were biased away from the null hypothesis by 2% to 31%, whereas risk ratios per IQR were attenuated (i.e. biased toward the null) by 5% to 34%. For CO modelled error amount, a range of error types were simulated and effects on risk ratio bias and significance were observed. For multiplicative error, both the amount and type of measurement error impact health effect estimates in air pollution epidemiology. By modelling
Reliability for some bivariate beta distributions

Directory of Open Access Journals (Sweden)

Nadarajah Saralees

2005-01-01

Full Text Available In the area of stress-strength models there has been a large amount of work as regards estimation of the reliability R=Pr( Xbivariate distribution with dependence between X and Y . In particular, we derive explicit expressions for R when the joint distribution is bivariate beta. The calculations involve the use of special functions.
Reliability for some bivariate gamma distributions

Directory of Open Access Journals (Sweden)

Nadarajah Saralees

2005-01-01

Full Text Available In the area of stress-strength models, there has been a large amount of work as regards estimation of the reliability R=Pr( Xbivariate distribution with dependence between X and Y . In particular, we derive explicit expressions for R when the joint distribution is bivariate gamma. The calculations involve the use of special functions.
Incorporating measurement error in n = 1 psychological autoregressive modeling

Science.gov (United States)

Schuurman, Noémi K.; Houtveen, Jan H.; Hamaker, Ellen L.

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30–50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters. PMID:26283988
Adjusting for the Incidence of Measurement Errors in Multilevel ...

African Journals Online (AJOL)

the incidence of measurement errors using these techniques generally revealed coefficient estimates of ... physical, biological, social and medical science, measurement errors are found. The errors are ... (M) and Science and Technology (ST).
Slope Error Measurement Tool for Solar Parabolic Trough Collectors: Preprint

Energy Technology Data Exchange (ETDEWEB)

Stynes, J. K.; Ihas, B.

2012-04-01

The National Renewable Energy Laboratory (NREL) has developed an optical measurement tool for parabolic solar collectors that measures the combined errors due to absorber misalignment and reflector slope error. The combined absorber alignment and reflector slope errors are measured using a digital camera to photograph the reflected image of the absorber in the collector. Previous work using the image of the reflection of the absorber finds the reflector slope errors from the reflection of the absorber and an independent measurement of the absorber location. The accuracy of the reflector slope error measurement is thus dependent on the accuracy of the absorber location measurement. By measuring the combined reflector-absorber errors, the uncertainty in the absorber location measurement is eliminated. The related performance merit, the intercept factor, depends on the combined effects of the absorber alignment and reflector slope errors. Measuring the combined effect provides a simpler measurement and a more accurate input to the intercept factor estimate. The minimal equipment and setup required for this measurement technique make it ideal for field measurements.
Assessing errors related to characteristics of the items measured

International Nuclear Information System (INIS)

Liggett, W.

1980-01-01

Errors that are related to some intrinsic property of the items measured are often encountered in nuclear material accounting. An example is the error in nondestructive assay measurements caused by uncorrected matrix effects. Nuclear material accounting requires for each materials type one measurement method for which bounds on these errors can be determined. If such a method is available, a second method might be used to reduce costs or to improve precision. If the measurement error for the first method is longer-tailed than Gaussian, then precision might be improved by measuring all items by both methods. 8 refs
Aliasing errors in measurements of beam position and ellipticity

International Nuclear Information System (INIS)

Ekdahl, Carl

2005-01-01

Beam position monitors (BPMs) are used in accelerators and ion experiments to measure currents, position, and azimuthal asymmetry. These usually consist of discrete arrays of electromagnetic field detectors, with detectors located at several equally spaced azimuthal positions at the beam tube wall. The discrete nature of these arrays introduces systematic errors into the data, independent of uncertainties resulting from signal noise, lack of recording dynamic range, etc. Computer simulations were used to understand and quantify these aliasing errors. If required, aliasing errors can be significantly reduced by employing more than the usual four detectors in the BPMs. These simulations show that the error in measurements of the centroid position of a large beam is indistinguishable from the error in the position of a filament. The simulations also show that aliasing errors in the measurement of beam ellipticity are very large unless the beam is accurately centered. The simulations were used to quantify the aliasing errors in beam parameter measurements during early experiments on the DARHT-II accelerator, demonstrating that they affected the measurements only slightly, if at all
Aliasing errors in measurements of beam position and ellipticity

Science.gov (United States)

Ekdahl, Carl

2005-09-01

Beam position monitors (BPMs) are used in accelerators and ion experiments to measure currents, position, and azimuthal asymmetry. These usually consist of discrete arrays of electromagnetic field detectors, with detectors located at several equally spaced azimuthal positions at the beam tube wall. The discrete nature of these arrays introduces systematic errors into the data, independent of uncertainties resulting from signal noise, lack of recording dynamic range, etc. Computer simulations were used to understand and quantify these aliasing errors. If required, aliasing errors can be significantly reduced by employing more than the usual four detectors in the BPMs. These simulations show that the error in measurements of the centroid position of a large beam is indistinguishable from the error in the position of a filament. The simulations also show that aliasing errors in the measurement of beam ellipticity are very large unless the beam is accurately centered. The simulations were used to quantify the aliasing errors in beam parameter measurements during early experiments on the DARHT-II accelerator, demonstrating that they affected the measurements only slightly, if at all.
Practical application of the theory of errors in measurement

International Nuclear Information System (INIS)

Anon.

1991-01-01

This chapter addresses the practical application of the theory of errors in measurement. The topics of the chapter include fixing on a maximum desired error, selecting a maximum error, the procedure for limiting the error, utilizing a standard procedure, setting specifications for a standard procedure, and selecting the number of measurements to be made
Measurement error models with interactions

Science.gov (United States)

Midthune, Douglas; Carroll, Raymond J.; Freedman, Laurence S.; Kipnis, Victor

2016-01-01

An important use of measurement error models is to correct regression models for bias due to covariate measurement error. Most measurement error models assume that the observed error-prone covariate (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$W$\\end{document}) is a linear function of the unobserved true covariate (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$X$\\end{document}) plus other covariates (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$Z$\\end{document}) in the regression model. In this paper, we consider models for \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$W$\\end{document} that include interactions between \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$X$\\end{document} and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$Z$\\end{document}. We derive the conditional distribution of
Ordinal bivariate inequality

DEFF Research Database (Denmark)

Sonne-Schmidt, Christoffer Scavenius; Tarp, Finn; Østerdal, Lars Peter Raahave

This paper introduces a concept of inequality comparisons with ordinal bivariate categorical data. In our model, one population is more unequal than another when they have common arithmetic median outcomes and the first can be obtained from the second by correlationincreasing switches and/or median......-preserving spreads. For the canonical 2x2 case (with two binary indicators), we derive a simple operational procedure for checking ordinal inequality relations in practice. As an illustration, we apply the model to childhood deprivation in Mozambique....

Measurement Error Estimation for Capacitive Voltage Transformer by Insulation Parameters

Directory of Open Access Journals (Sweden)

Bin Chen

2017-03-01

Full Text Available Measurement errors of a capacitive voltage transformer (CVT are relevant to its equivalent parameters for which its capacitive divider contributes the most. In daily operation, dielectric aging, moisture, dielectric breakdown, etc., it will exert mixing effects on a capacitive divider’s insulation characteristics, leading to fluctuation in equivalent parameters which result in the measurement error. This paper proposes an equivalent circuit model to represent a CVT which incorporates insulation characteristics of a capacitive divider. After software simulation and laboratory experiments, the relationship between measurement errors and insulation parameters is obtained. It indicates that variation of insulation parameters in a CVT will cause a reasonable measurement error. From field tests and calculation, equivalent capacitance mainly affects magnitude error, while dielectric loss mainly affects phase error. As capacitance changes 0.2%, magnitude error can reach −0.2%. As dielectric loss factor changes 0.2%, phase error can reach 5′. An increase of equivalent capacitance and dielectric loss factor in the high-voltage capacitor will cause a positive real power measurement error. An increase of equivalent capacitance and dielectric loss factor in the low-voltage capacitor will cause a negative real power measurement error.
Beam induced vacuum measurement error in BEPC II

Institute of Scientific and Technical Information of China (English)

无

2011-01-01

When the beam in BEPCII storage ring aborts suddenly, the measured pressure of cold cathode gauges and ion pumps will drop suddenly and decrease to the base pressure gradually. This shows that there is a beam induced positive error in the pressure measurement during beam operation. The error is the difference between measured and real pressures. Right after the beam aborts, the error will disappear immediately and the measured pressure will then be equal to real pressure. For one gauge, we can fit a non-linear pressure-time curve with its measured pressure data 20 seconds after a sudden beam abortion. From this negative exponential decay pumping-down curve, real pressure at the time when the beam starts aborting is extrapolated. With the data of several sudden beam abortions we have got the errors of that gauge in different beam currents and found that the error is directly proportional to the beam current, as expected. And a linear data-fitting gives the proportion coefficient of the equation, which we derived to evaluate the real pressure all the time when the beam with varied currents is on.
Ordinal Bivariate Inequality

DEFF Research Database (Denmark)

Sonne-Schmidt, Christoffer Scavenius; Tarp, Finn; Østerdal, Lars Peter Raahave

2016-01-01

This paper introduces a concept of inequality comparisons with ordinal bivariate categorical data. In our model, one population is more unequal than another when they have common arithmetic median outcomes and the first can be obtained from the second by correlation-increasing switches and....../or median-preserving spreads. For the canonical 2 × 2 case (with two binary indicators), we derive a simple operational procedure for checking ordinal inequality relations in practice. As an illustration, we apply the model to childhood deprivation in Mozambique....
Measurement error models with uncertainty about the error variance

NARCIS (Netherlands)

Oberski, D.L.; Satorra, A.

2013-01-01

It is well known that measurement error in observable variables induces bias in estimates in standard regression analysis and that structural equation models are a typical solution to this problem. Often, multiple indicator equations are subsumed as part of the structural equation model, allowing
Errors and Correction of Precipitation Measurements in China

Institute of Scientific and Technical Information of China (English)

REN Zhihua; LI Mingqin

2007-01-01

In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the "horizontal precipitation gauge" was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper.A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.
Error evaluation method for material accountancy measurement. Evaluation of random and systematic errors based on material accountancy data

International Nuclear Information System (INIS)

Nidaira, Kazuo

2008-01-01

International Target Values (ITV) shows random and systematic measurement uncertainty components as a reference for routinely achievable measurement quality in the accountancy measurement. The measurement uncertainty, called error henceforth, needs to be periodically evaluated and checked against ITV for consistency as the error varies according to measurement methods, instruments, operators, certified reference samples, frequency of calibration, and so on. In the paper an error evaluation method was developed with focuses on (1) Specifying clearly error calculation model, (2) Getting always positive random and systematic error variances, (3) Obtaining probability density distribution of an error variance and (4) Confirming the evaluation method by simulation. In addition the method was demonstrated by applying real data. (author)
State-independent error-disturbance trade-off for measurement operators

International Nuclear Information System (INIS)

Zhou, S.S.; Wu, Shengjun; Chau, H.F.

2016-01-01

In general, classical measurement statistics of a quantum measurement is disturbed by performing an additional incompatible quantum measurement beforehand. Using this observation, we introduce a state-independent definition of disturbance by relating it to the distinguishability problem between two classical statistical distributions – one resulting from a single quantum measurement and the other from a succession of two quantum measurements. Interestingly, we find an error-disturbance trade-off relation for any measurements in two-dimensional Hilbert space and for measurements with mutually unbiased bases in any finite-dimensional Hilbert space. This relation shows that error should be reduced to zero in order to minimize the sum of error and disturbance. We conjecture that a similar trade-off relation with a slightly relaxed definition of error can be generalized to any measurements in an arbitrary finite-dimensional Hilbert space.
Bivariate copula in fitting rainfall data

Science.gov (United States)

Yee, Kong Ching; Suhaila, Jamaludin; Yusof, Fadhilah; Mean, Foo Hui

2014-07-01

The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC).
Genetics of Obesity Traits: A Bivariate Genome-Wide Association Analysis

DEFF Research Database (Denmark)

Wu, Yili; Duan, Haiping; Tian, Xiaocao

2018-01-01

Previous genome-wide association studies on anthropometric measurements have identified more than 100 related loci, but only a small portion of heritability in obesity was explained. Here we present a bivariate twin study to look for the genetic variants associated with body mass index and waist......-hip ratio, and to explore the obesity-related pathways in Northern Han Chinese. Cholesky decompositionmodel for 242monozygotic and 140 dizygotic twin pairs indicated a moderate genetic correlation (r = 0.53, 95%CI: 0.42–0.64) between body mass index and waist-hip ratio. Bivariate genome-wide association.......05. Expression quantitative trait loci analysis identified rs2242044 as a significant cis-eQTL in both the normal adipose-subcutaneous (P = 1.7 × 10−9) and adipose-visceral (P = 4.4 × 10−15) tissue. These findings may provide an important entry point to unravel genetic pleiotropy in obesity traits....
A non-parametric conditional bivariate reference region with an application to height/weight measurements on normal girls

DEFF Research Database (Denmark)

Petersen, Jørgen Holm

2009-01-01

A conceptually simple two-dimensional conditional reference curve is described. The curve gives a decision basis for determining whether a bivariate response from an individual is "normal" or "abnormal" when taking into account that a third (conditioning) variable may influence the bivariate...... response. The reference curve is not only characterized analytically but also by geometric properties that are easily communicated to medical doctors - the users of such curves. The reference curve estimator is completely non-parametric, so no distributional assumptions are needed about the two......-dimensional response. An example that will serve to motivate and illustrate the reference is the study of the height/weight distribution of 7-8-year-old Danish school girls born in 1930, 1950, or 1970....
Bivariable analysis of ventricular late potentials in high resolution ECG records

International Nuclear Information System (INIS)

Orosco, L; Laciar, E

2007-01-01

In this study the bivariable analysis for ventricular late potentials detection in high-resolution electrocardiographic records is proposed. The standard time-domain analysis and the application of the time-frequency technique to high-resolution ECG records are briefly described as well as their corresponding results. In the proposed technique the time-domain parameter, QRSD and the most significant time-frequency index, EN QRS are used like variables. A bivariable index is defined, that combines the previous parameters. The propose technique allows evaluating the risk of ventricular tachycardia in post-myocardial infarct patients. The results show that the used bivariable index allows discriminating between the patient's population with ventricular tachycardia and the subjects of the control group. Also, it was found that the bivariable technique obtains a good valuation as diagnostic test. It is concluded that comparatively, the valuation of the bivariable technique as diagnostic test is superior to that of the time-domain method and the time-frequency technique evaluated individually
REGRES: A FORTRAN-77 program to calculate nonparametric and ``structural'' parametric solutions to bivariate regression equations

Science.gov (United States)

Rock, N. M. S.; Duffy, T. R.

REGRES allows a range of regression equations to be calculated for paired sets of data values in which both variables are subject to error (i.e. neither is the "independent" variable). Nonparametric regressions, based on medians of all possible pairwise slopes and intercepts, are treated in detail. Estimated slopes and intercepts are output, along with confidence limits, Spearman and Kendall rank correlation coefficients. Outliers can be rejected with user-determined stringency. Parametric regressions can be calculated for any value of λ (the ratio of the variances of the random errors for y and x)—including: (1) major axis ( λ = 1); (2) reduced major axis ( λ = variance of y/variance of x); (3) Y on Xλ = infinity; or (4) X on Y ( λ = 0) solutions. Pearson linear correlation coefficients also are output. REGRES provides an alternative to conventional isochron assessment techniques where bivariate normal errors cannot be assumed, or weighting methods are inappropriate.
Unit of measurement used and parent medication dosing errors.

Science.gov (United States)

Yin, H Shonna; Dreyer, Benard P; Ugboaja, Donna C; Sanchez, Dayana C; Paul, Ian M; Moreira, Hannah A; Rodriguez, Luis; Mendelsohn, Alan L

2014-08-01

Adopting the milliliter as the preferred unit of measurement has been suggested as a strategy to improve the clarity of medication instructions; teaspoon and tablespoon units may inadvertently endorse nonstandard kitchen spoon use. We examined the association between unit used and parent medication errors and whether nonstandard instruments mediate this relationship. Cross-sectional analysis of baseline data from a larger study of provider communication and medication errors. English- or Spanish-speaking parents (n = 287) whose children were prescribed liquid medications in 2 emergency departments were enrolled. Medication error defined as: error in knowledge of prescribed dose, error in observed dose measurement (compared to intended or prescribed dose); >20% deviation threshold for error. Multiple logistic regression performed adjusting for parent age, language, country, race/ethnicity, socioeconomic status, education, health literacy (Short Test of Functional Health Literacy in Adults); child age, chronic disease; site. Medication errors were common: 39.4% of parents made an error in measurement of the intended dose, 41.1% made an error in the prescribed dose. Furthermore, 16.7% used a nonstandard instrument. Compared with parents who used milliliter-only, parents who used teaspoon or tablespoon units had twice the odds of making an error with the intended (42.5% vs 27.6%, P = .02; adjusted odds ratio=2.3; 95% confidence interval, 1.2-4.4) and prescribed (45.1% vs 31.4%, P = .04; adjusted odds ratio=1.9; 95% confidence interval, 1.03-3.5) dose; associations greater for parents with low health literacy and non-English speakers. Nonstandard instrument use partially mediated teaspoon and tablespoon-associated measurement errors. Findings support a milliliter-only standard to reduce medication errors. Copyright © 2014 by the American Academy of Pediatrics.
Measurement Error in Education and Growth Regressions

NARCIS (Netherlands)

Portela, Miguel; Alessie, Rob; Teulings, Coen

2010-01-01

The use of the perpetual inventory method for the construction of education data per country leads to systematic measurement error. This paper analyzes its effect on growth regressions. We suggest a methodology for correcting this error. The standard attenuation bias suggests that using these
Error-measure for anisotropic grid-adaptation in turbulence-resolving simulations

Science.gov (United States)

Toosi, Siavash; Larsson, Johan

2015-11-01

Grid-adaptation requires an error-measure that identifies where the grid should be refined. In the case of turbulence-resolving simulations (DES, LES, DNS), a simple error-measure is the small-scale resolved energy, which scales with both the modeled subgrid-stresses and the numerical truncation errors in many situations. Since this is a scalar measure, it does not carry any information on the anisotropy of the optimal grid-refinement. The purpose of this work is to introduce a new error-measure for turbulence-resolving simulations that is capable of predicting nearly-optimal anisotropic grids. Turbulent channel flow at Reτ ~ 300 is used to assess the performance of the proposed error-measure. The formulation is geometrically general, applicable to any type of unstructured grid.
Analysis on the dynamic error for optoelectronic scanning coordinate measurement network

Science.gov (United States)

Shi, Shendong; Yang, Linghui; Lin, Jiarui; Guo, Siyang; Ren, Yongjie

2018-01-01

Large-scale dynamic three-dimension coordinate measurement technique is eagerly demanded in equipment manufacturing. Noted for advantages of high accuracy, scale expandability and multitask parallel measurement, optoelectronic scanning measurement network has got close attention. It is widely used in large components jointing, spacecraft rendezvous and docking simulation, digital shipbuilding and automated guided vehicle navigation. At present, most research about optoelectronic scanning measurement network is focused on static measurement capacity and research about dynamic accuracy is insufficient. Limited by the measurement principle, the dynamic error is non-negligible and restricts the application. The workshop measurement and positioning system is a representative which can realize dynamic measurement function in theory. In this paper we conduct deep research on dynamic error resources and divide them two parts: phase error and synchronization error. Dynamic error model is constructed. Based on the theory above, simulation about dynamic error is carried out. Dynamic error is quantized and the rule of volatility and periodicity has been found. Dynamic error characteristics are shown in detail. The research result lays foundation for further accuracy improvement.
Building Bivariate Tables: The compareGroups Package for R

Directory of Open Access Journals (Sweden)

Isaac Subirana

2014-05-01

Full Text Available The R package compareGroups provides functions meant to facilitate the construction of bivariate tables (descriptives of several variables for comparison between groups and generates reports in several formats (LATEX, HTML or plain text CSV. Moreover, bivariate tables can be viewed directly on the R console in a nice format. A graphical user interface (GUI has been implemented to build the bivariate tables more easily for those users who are not familiar with the R software. Some new functions and methods have been incorporated in the newest version of the compareGroups package (version 1.x to deal with time-to-event variables, stratifying tables, merging several tables, and revising the statistical methods used. The GUI interface also has been improved, making it much easier and more intuitive to set the inputs for building the bivariate tables. The ?rst version (version 0.x and this version were presented at the 2010 useR! conference (Sanz, Subirana, and Vila 2010 and the 2011 useR! conference (Sanz, Subirana, and Vila 2011, respectively. Package compareGroups is available from the Comprehensive R Archive Network at http://CRAN.R-project.org/package=compareGroups.
The relative performance of bivariate causality tests in small samples

NARCIS (Netherlands)

Bult, J..R.; Leeflang, P.S.H.; Wittink, D.R.

1997-01-01

Causality tests have been applied to establish directional effects and to reduce the set of potential predictors, For the latter type of application only bivariate tests can be used, In this study we compare bivariate causality tests. Although the problem addressed is general and could benefit
Quantification and handling of sampling errors in instrumental measurements: a case study

DEFF Research Database (Denmark)

Andersen, Charlotte Møller; Bro, R.

2004-01-01

in certain situations, the effect of systematic errors is also considerable. The relevant errors contributing to the prediction error are: error in instrumental measurements (x-error), error in reference measurements (y-error), error in the estimated calibration model (regression coefficient error) and model...
A straightness error measurement method matched new generation GPS

International Nuclear Information System (INIS)

Zhang, X B; Lu, H; Jiang, X Q; Li, Z

2005-01-01

The axis of the non-diffracting beam produced by an axicon is very stable and can be adopted as the datum line to measure the spatial straightness error in continuous working distance, which may be short, medium or long. Though combining the non-diffracting beam datum-line with LVDT displace detector, a new straightness error measurement method is developed. Because the non-diffracting beam datum-line amends the straightness error gauged by LVDT, the straightness error is reliable and this method is matchs new generation GPS

Individual differences in error monitoring in healthy adults: psychological symptoms and antisocial personality characteristics.

Science.gov (United States)

Chang, Wen-Pin; Davies, Patricia L; Gavin, William J

2010-10-01

Recent studies have investigated the relationship between psychological symptoms and personality traits and error monitoring measured by error-related negativity (ERN) and error positivity (Pe) event-related potential (ERP) components, yet there remains a paucity of studies examining the collective simultaneous effects of psychological symptoms and personality traits on error monitoring. This present study, therefore, examined whether measures of hyperactivity-impulsivity, depression, anxiety and antisocial personality characteristics could collectively account for significant interindividual variability of both ERN and Pe amplitudes, in 29 healthy adults with no known disorders, ages 18-30 years. The bivariate zero-order correlation analyses found that only the anxiety measure was significantly related to both ERN and Pe amplitudes. However, multiple regression analyses that included all four characteristic measures while controlling for number of segments in the ERP average revealed that both depression and antisocial personality characteristics were significant predictors for the ERN amplitudes whereas antisocial personality was the only significant predictor for the Pe amplitude. These findings suggest that psychological symptoms and personality traits are associated with individual variations in error monitoring in healthy adults, and future studies should consider these variables when comparing group difference in error monitoring between adults with and without disabilities. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.
Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression.

Science.gov (United States)

Lao, Yunteng; Wu, Yao-Jan; Corey, Jonathan; Wang, Yinhai

2011-01-01

Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ(1), λ(2) and λ(3)). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs. Published by Elsevier Ltd.
Measurement errors in voice-key naming latency for Hiragana.

Science.gov (United States)

Yamada, Jun; Tamaoka, Katsuo

2003-12-01

This study makes explicit the limitations and possibilities of voice-key naming latency research on single hiragana symbols (a Japanese syllabic script) by examining three sets of voice-key naming data against Sakuma, Fushimi, and Tatsumi's 1997 speech-analyzer voice-waveform data. Analysis showed that voice-key measurement errors can be substantial in standard procedures as they may conceal the true effects of significant variables involved in hiragana-naming behavior. While one can avoid voice-key measurement errors to some extent by applying Sakuma, et al.'s deltas and by excluding initial phonemes which induce measurement errors, such errors may be ignored when test items are words and other higher-level linguistic materials.
Nonclassical measurements errors in nonlinear models

DEFF Research Database (Denmark)

Madsen, Edith; Mulalic, Ismir

Discrete choice models and in particular logit type models play an important role in understanding and quantifying individual or household behavior in relation to transport demand. An example is the choice of travel mode for a given trip under the budget and time restrictions that the individuals...... estimates of the income effect it is of interest to investigate the magnitude of the estimation bias and if possible use estimation techniques that take the measurement error problem into account. We use data from the Danish National Travel Survey (NTS) and merge it with administrative register data...... that contains very detailed information about incomes. This gives a unique opportunity to learn about the magnitude and nature of the measurement error in income reported by the respondents in the Danish NTS compared to income from the administrative register (correct measure). We find that the classical...
A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM.

Science.gov (United States)

Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei; Song, Houbing

2018-01-15

Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model's performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM's parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models' performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors.
Random measurement error: Why worry? An example of cardiovascular risk factors.

Science.gov (United States)

Brakenhoff, Timo B; van Smeden, Maarten; Visseren, Frank L J; Groenwold, Rolf H H

2018-01-01

With the increased use of data not originally recorded for research, such as routine care data (or 'big data'), measurement error is bound to become an increasingly relevant problem in medical research. A common view among medical researchers on the influence of random measurement error (i.e. classical measurement error) is that its presence leads to some degree of systematic underestimation of studied exposure-outcome relations (i.e. attenuation of the effect estimate). For the common situation where the analysis involves at least one exposure and one confounder, we demonstrate that the direction of effect of random measurement error on the estimated exposure-outcome relations can be difficult to anticipate. Using three example studies on cardiovascular risk factors, we illustrate that random measurement error in the exposure and/or confounder can lead to underestimation as well as overestimation of exposure-outcome relations. We therefore advise medical researchers to refrain from making claims about the direction of effect of measurement error in their manuscripts, unless the appropriate inferential tools are used to study or alleviate the impact of measurement error from the analysis.
Assessing Measurement Error in Medicare Coverage

Data.gov (United States)

U.S. Department of Health & Human Services — Assessing Measurement Error in Medicare Coverage From the National Health Interview Survey Using linked administrative data, to validate Medicare coverage estimates...
Influence of measurement errors and estimated parameters on combustion diagnosis

International Nuclear Information System (INIS)

Payri, F.; Molina, S.; Martin, J.; Armas, O.

2006-01-01

Thermodynamic diagnosis models are valuable tools for the study of Diesel combustion. Inputs required by such models comprise measured mean and instantaneous variables, together with suitable values for adjustable parameters used in different submodels. In the case of measured variables, one may estimate the uncertainty associated with measurement errors; however, the influence of errors in model parameter estimation may not be so easily established on an experimental basis. In this paper, a simulated pressure cycle has been used along with known input parameters, so that any uncertainty in the inputs is avoided. Then, the influence of errors in measured variables and geometric and heat transmission parameters on the results of a diagnosis combustion model for direct injection diesel engines have been studied. This procedure allowed to establish the relative importance of these parameters and to set limits to the maximal errors of the model, accounting for both the maximal expected errors in the input parameters and the sensitivity of the model to those errors
Estimation of the measurement error of eccentrically installed orifice plates

Energy Technology Data Exchange (ETDEWEB)

Barton, Neil; Hodgkinson, Edwin; Reader-Harris, Michael

2005-07-01

The presentation discusses methods for simulation and estimation of flow measurement errors. The main conclusions are: Computational Fluid Dynamics (CFD) simulation methods and published test measurements have been used to estimate the error of a metering system over a period when its orifice plates were eccentric and when leaking O-rings allowed some gas to bypass the meter. It was found that plate eccentricity effects would result in errors of between -2% and -3% for individual meters. Validation against test data suggests that these estimates of error should be within 1% of the actual error, but it is unclear whether the simulations over-estimate or under-estimate the error. Simulations were also run to assess how leakage at the periphery affects the metering error. Various alternative leakage scenarios were modelled and it was found that the leakage rate has an effect on the error, but that the leakage distribution does not. Correction factors, based on the CFD results, were then used to predict the system's mis-measurement over a three-year period (tk)
Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part I—Model Development

Science.gov (United States)

Calvo, Roque; D’Amato, Roberto; Gómez, Emilio; Domingo, Rosario

2016-01-01

The development of an error compensation model for coordinate measuring machines (CMMs) and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included. PMID:27690052
Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part I—Model Development

Directory of Open Access Journals (Sweden)

Roque Calvo

2016-09-01

Full Text Available The development of an error compensation model for coordinate measuring machines (CMMs and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included.
Random measurement error: Why worry? An example of cardiovascular risk factors.

Directory of Open Access Journals (Sweden)

Timo B Brakenhoff

Full Text Available With the increased use of data not originally recorded for research, such as routine care data (or 'big data', measurement error is bound to become an increasingly relevant problem in medical research. A common view among medical researchers on the influence of random measurement error (i.e. classical measurement error is that its presence leads to some degree of systematic underestimation of studied exposure-outcome relations (i.e. attenuation of the effect estimate. For the common situation where the analysis involves at least one exposure and one confounder, we demonstrate that the direction of effect of random measurement error on the estimated exposure-outcome relations can be difficult to anticipate. Using three example studies on cardiovascular risk factors, we illustrate that random measurement error in the exposure and/or confounder can lead to underestimation as well as overestimation of exposure-outcome relations. We therefore advise medical researchers to refrain from making claims about the direction of effect of measurement error in their manuscripts, unless the appropriate inferential tools are used to study or alleviate the impact of measurement error from the analysis.
Valuation Biases, Error Measures, and the Conglomerate Discount

NARCIS (Netherlands)

I. Dittmann (Ingolf); E.G. Maug (Ernst)

2006-01-01

textabstractWe document the importance of the choice of error measure (percentage vs. logarithmic errors) for the comparison of alternative valuation procedures. We demonstrate for several multiple valuation methods (averaging with the arithmetic mean, harmonic mean, median, geometric mean) that the
An in-process form error measurement system for precision machining

International Nuclear Information System (INIS)

Gao, Y; Huang, X; Zhang, Y

2010-01-01

In-process form error measurement for precision machining is studied. Due to two key problems, opaque barrier and vibration, the study of in-process form error optical measurement for precision machining has been a hard topic and so far very few existing research works can be found. In this project, an in-process form error measurement device is proposed to deal with the two key problems. Based on our existing studies, a prototype system has been developed. It is the first one of the kind that overcomes the two key problems. The prototype is based on a single laser sensor design of 50 nm resolution together with two techniques, a damping technique and a moving average technique, proposed for use with the device. The proposed damping technique is able to improve vibration attenuation by up to 21 times compared to the case of natural attenuation. The proposed moving average technique is able to reduce errors by seven to ten times without distortion to the form profile results. The two proposed techniques are simple but they are especially useful for the proposed device. For a workpiece sample, the measurement result under coolant condition is only 2.5% larger compared with the one under no coolant condition. For a certified Wyko test sample, the overall system measurement error can be as low as 0.3 µm. The measurement repeatability error can be as low as 2.2%. The experimental results give confidence in using the proposed in-process form error measurement device. For better results, further improvement in design and tests are necessary
Bivariate functional data clustering: grouping streams based on a varying coefficient model of the stream water and air temperature relationship

Science.gov (United States)

H. Li; X. Deng; Andy Dolloff; E. P. Smith

2015-01-01

A novel clustering method for bivariate functional data is proposed to group streams based on their waterâair temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...
Interval sampling methods and measurement error: a computer simulation.

Science.gov (United States)

Wirth, Oliver; Slaven, James; Taylor, Matthew A

2014-01-01

A simulation study was conducted to provide a more thorough account of measurement error associated with interval sampling methods. A computer program simulated the application of momentary time sampling, partial-interval recording, and whole-interval recording methods on target events randomly distributed across an observation period. The simulation yielded measures of error for multiple combinations of observation period, interval duration, event duration, and cumulative event duration. The simulations were conducted up to 100 times to yield measures of error variability. Although the present simulation confirmed some previously reported characteristics of interval sampling methods, it also revealed many new findings that pertain to each method's inherent strengths and weaknesses. The analysis and resulting error tables can help guide the selection of the most appropriate sampling method for observation-based behavioral assessments. © Society for the Experimental Analysis of Behavior.
Haplotype reconstruction error as a classical misclassification problem: introducing sensitivity and specificity as error measures.

Directory of Open Access Journals (Sweden)

Claudia Lamina

Full Text Available BACKGROUND: Statistically reconstructing haplotypes from single nucleotide polymorphism (SNP genotypes, can lead to falsely classified haplotypes. This can be an issue when interpreting haplotype association results or when selecting subjects with certain haplotypes for subsequent functional studies. It was our aim to quantify haplotype reconstruction error and to provide tools for it. METHODS AND RESULTS: By numerous simulation scenarios, we systematically investigated several error measures, including discrepancy, error rate, and R(2, and introduced the sensitivity and specificity to this context. We exemplified several measures in the KORA study, a large population-based study from Southern Germany. We find that the specificity is slightly reduced only for common haplotypes, while the sensitivity was decreased for some, but not all rare haplotypes. The overall error rate was generally increasing with increasing number of loci, increasing minor allele frequency of SNPs, decreasing correlation between the alleles and increasing ambiguity. CONCLUSIONS: We conclude that, with the analytical approach presented here, haplotype-specific error measures can be computed to gain insight into the haplotype uncertainty. This method provides the information, if a specific risk haplotype can be expected to be reconstructed with rather no or high misclassification and thus on the magnitude of expected bias in association estimates. We also illustrate that sensitivity and specificity separate two dimensions of the haplotype reconstruction error, which completely describe the misclassification matrix and thus provide the prerequisite for methods accounting for misclassification.
Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures

DEFF Research Database (Denmark)

Christiansen, Niels H.; Voie, Per Erlend Torbergsen; Winther, Ole

2014-01-01

Training of an artificial neural network (ANN) adjusts the internal weights of the network in order to minimize a predefined error measure. This error measure is given by an error function. Several different error functions are suggested in the literature. However, the far most common measure...
Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.

Science.gov (United States)

Samoli, Evangelia; Butland, Barbara K

2017-12-01

Outdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. We identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.
Using surrogate biomarkers to improve measurement error models in nutritional epidemiology

Science.gov (United States)

Keogh, Ruth H; White, Ian R; Rodwell, Sheila A

2013-01-01

Nutritional epidemiology relies largely on self-reported measures of dietary intake, errors in which give biased estimated diet–disease associations. Self-reported measurements come from questionnaires and food records. Unbiased biomarkers are scarce; however, surrogate biomarkers, which are correlated with intake but not unbiased, can also be useful. It is important to quantify and correct for the effects of measurement error on diet–disease associations. Challenges arise because there is no gold standard, and errors in self-reported measurements are correlated with true intake and each other. We describe an extended model for error in questionnaire, food record, and surrogate biomarker measurements. The focus is on estimating the degree of bias in estimated diet–disease associations due to measurement error. In particular, we propose using sensitivity analyses to assess the impact of changes in values of model parameters which are usually assumed fixed. The methods are motivated by and applied to measures of fruit and vegetable intake from questionnaires, 7-day diet diaries, and surrogate biomarker (plasma vitamin C) from over 25000 participants in the Norfolk cohort of the European Prospective Investigation into Cancer and Nutrition. Our results show that the estimated effects of error in self-reported measurements are highly sensitive to model assumptions, resulting in anything from a large attenuation to a small amplification in the diet–disease association. Commonly made assumptions could result in a large overcorrection for the effects of measurement error. Increased understanding of relationships between potential surrogate biomarkers and true dietary intake is essential for obtaining good estimates of the effects of measurement error in self-reported measurements on observed diet–disease associations. Copyright © 2013 John Wiley & Sons, Ltd. PMID:23553407

A heteroscedastic measurement error model for method comparison data with replicate measurements.

Science.gov (United States)

Nawarathna, Lakshika S; Choudhary, Pankaj K

2015-03-30

Measurement error models offer a flexible framework for modeling data collected in studies comparing methods of quantitative measurement. These models generally make two simplifying assumptions: (i) the measurements are homoscedastic, and (ii) the unobservable true values of the methods are linearly related. One or both of these assumptions may be violated in practice. In particular, error variabilities of the methods may depend on the magnitude of measurement, or the true values may be nonlinearly related. Data with these features call for a heteroscedastic measurement error model that allows nonlinear relationships in the true values. We present such a model for the case when the measurements are replicated, discuss its fitting, and explain how to evaluate similarity of measurement methods and agreement between them, which are two common goals of data analysis, under this model. Model fitting involves dealing with lack of a closed form for the likelihood function. We consider estimation methods that approximate either the likelihood or the model to yield approximate maximum likelihood estimates. The fitting methods are evaluated in a simulation study. The proposed methodology is used to analyze a cholesterol dataset. Copyright © 2015 John Wiley & Sons, Ltd.
An in-situ measuring method for planar straightness error

Science.gov (United States)

Chen, Xi; Fu, Luhua; Yang, Tongyu; Sun, Changku; Wang, Zhong; Zhao, Yan; Liu, Changjie

2018-01-01

According to some current problems in the course of measuring the plane shape error of workpiece, an in-situ measuring method based on laser triangulation is presented in this paper. The method avoids the inefficiency of traditional methods like knife straightedge as well as the time and cost requirements of coordinate measuring machine(CMM). A laser-based measuring head is designed and installed on the spindle of a numerical control(NC) machine. The measuring head moves in the path planning to measure measuring points. The spatial coordinates of the measuring points are obtained by the combination of the laser triangulation displacement sensor and the coordinate system of the NC machine, which could make the indicators of measurement come true. The method to evaluate planar straightness error adopts particle swarm optimization(PSO). To verify the feasibility and accuracy of the measuring method, simulation experiments were implemented with a CMM. Comparing the measurement results of measuring head with the corresponding measured values obtained by composite measuring machine, it is verified that the method can realize high-precise and automatic measurement of the planar straightness error of the workpiece.
Content Validity of a Tool Measuring Medication Errors.

Science.gov (United States)

Tabassum, Nishat; Allana, Saleema; Saeed, Tanveer; Dias, Jacqueline Maria

2015-08-01

The objective of this study was to determine content and face validity of a tool measuring medication errors among nursing students in baccalaureate nursing education. Data was collected from the Aga Khan University School of Nursing and Midwifery (AKUSoNaM), Karachi, from March to August 2014. The tool was developed utilizing literature and the expertise of the team members, expert in different areas. The developed tool was then sent to five experts from all over Karachi for ensuring the content validity of the tool, which was measured on relevance and clarity of the questions. The Scale Content Validity Index (S-CVI) for clarity and relevance of the questions was found to be 0.94 and 0.98, respectively. The tool measuring medication errors has an excellent content validity. This tool should be used for future studies on medication errors, with different study populations such as medical students, doctors, and nurses.
Correcting systematic errors in high-sensitivity deuteron polarization measurements

Science.gov (United States)

Brantjes, N. P. M.; Dzordzhadze, V.; Gebel, R.; Gonnella, F.; Gray, F. E.; van der Hoek, D. J.; Imig, A.; Kruithof, W. L.; Lazarus, D. M.; Lehrach, A.; Lorentz, B.; Messi, R.; Moricciani, D.; Morse, W. M.; Noid, G. A.; Onderwater, C. J. G.; Özben, C. S.; Prasuhn, D.; Levi Sandri, P.; Semertzidis, Y. K.; da Silva e Silva, M.; Stephenson, E. J.; Stockhorst, H.; Venanzoni, G.; Versolato, O. O.

2012-02-01

This paper reports deuteron vector and tensor beam polarization measurements taken to investigate the systematic variations due to geometric beam misalignments and high data rates. The experiments used the In-Beam Polarimeter at the KVI-Groningen and the EDDA detector at the Cooler Synchrotron COSY at Jülich. By measuring with very high statistical precision, the contributions that are second-order in the systematic errors become apparent. By calibrating the sensitivity of the polarimeter to such errors, it becomes possible to obtain information from the raw count rate values on the size of the errors and to use this information to correct the polarization measurements. During the experiment, it was possible to demonstrate that corrections were satisfactory at the level of 10 -5 for deliberately large errors. This may facilitate the real time observation of vector polarization changes smaller than 10 -6 in a search for an electric dipole moment using a storage ring.
Correcting systematic errors in high-sensitivity deuteron polarization measurements

Energy Technology Data Exchange (ETDEWEB)

Brantjes, N.P.M. [Kernfysisch Versneller Instituut, University of Groningen, NL-9747AA Groningen (Netherlands); Dzordzhadze, V. [Brookhaven National Laboratory, Upton, NY 11973 (United States); Gebel, R. [Institut fuer Kernphysik, Juelich Center for Hadron Physics, Forschungszentrum Juelich, D-52425 Juelich (Germany); Gonnella, F. [Physica Department of ' Tor Vergata' University, Rome (Italy); INFN-Sez. ' Roma tor Vergata,' Rome (Italy); Gray, F.E. [Regis University, Denver, CO 80221 (United States); Hoek, D.J. van der [Kernfysisch Versneller Instituut, University of Groningen, NL-9747AA Groningen (Netherlands); Imig, A. [Brookhaven National Laboratory, Upton, NY 11973 (United States); Kruithof, W.L. [Kernfysisch Versneller Instituut, University of Groningen, NL-9747AA Groningen (Netherlands); Lazarus, D.M. [Brookhaven National Laboratory, Upton, NY 11973 (United States); Lehrach, A.; Lorentz, B. [Institut fuer Kernphysik, Juelich Center for Hadron Physics, Forschungszentrum Juelich, D-52425 Juelich (Germany); Messi, R. [Physica Department of ' Tor Vergata' University, Rome (Italy); INFN-Sez. ' Roma tor Vergata,' Rome (Italy); Moricciani, D. [INFN-Sez. ' Roma tor Vergata,' Rome (Italy); Morse, W.M. [Brookhaven National Laboratory, Upton, NY 11973 (United States); Noid, G.A. [Indiana University Cyclotron Facility, Bloomington, IN 47408 (United States); and others

2012-02-01

This paper reports deuteron vector and tensor beam polarization measurements taken to investigate the systematic variations due to geometric beam misalignments and high data rates. The experiments used the In-Beam Polarimeter at the KVI-Groningen and the EDDA detector at the Cooler Synchrotron COSY at Juelich. By measuring with very high statistical precision, the contributions that are second-order in the systematic errors become apparent. By calibrating the sensitivity of the polarimeter to such errors, it becomes possible to obtain information from the raw count rate values on the size of the errors and to use this information to correct the polarization measurements. During the experiment, it was possible to demonstrate that corrections were satisfactory at the level of 10{sup -5} for deliberately large errors. This may facilitate the real time observation of vector polarization changes smaller than 10{sup -6} in a search for an electric dipole moment using a storage ring.
Varying coefficients model with measurement error.

Science.gov (United States)

Li, Liang; Greene, Tom

2008-06-01

We propose a semiparametric partially varying coefficient model to study the relationship between serum creatinine concentration and the glomerular filtration rate (GFR) among kidney donors and patients with chronic kidney disease. A regression model is used to relate serum creatinine to GFR and demographic factors in which coefficient of GFR is expressed as a function of age to allow its effect to be age dependent. GFR measurements obtained from the clearance of a radioactively labeled isotope are assumed to be a surrogate for the true GFR, with the relationship between measured and true GFR expressed using an additive error model. We use locally corrected score equations to estimate parameters and coefficient functions, and propose an expected generalized cross-validation (EGCV) method to select the kernel bandwidth. The performance of the proposed methods, which avoid distributional assumptions on the true GFR and residuals, is investigated by simulation. Accounting for measurement error using the proposed model reduced apparent inconsistencies in the relationship between serum creatinine and GFR among different clinical data sets derived from kidney donor and chronic kidney disease source populations.
The impact of measurement errors in the identification of regulatory networks

Directory of Open Access Journals (Sweden)

Sato João R

2009-12-01

Full Text Available Abstract Background There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent and non-time series (independent data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models and dependent (autoregressive models data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error. The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.
Accounting for measurement error: a critical but often overlooked process.

Science.gov (United States)

Harris, Edward F; Smith, Richard N

2009-12-01

Due to instrument imprecision and human inconsistencies, measurements are not free of error. Technical error of measurement (TEM) is the variability encountered between dimensions when the same specimens are measured at multiple sessions. A goal of a data collection regimen is to minimise TEM. The few studies that actually quantify TEM, regardless of discipline, report that it is substantial and can affect results and inferences. This paper reviews some statistical approaches for identifying and controlling TEM. Statistically, TEM is part of the residual ('unexplained') variance in a statistical test, so accounting for TEM, which requires repeated measurements, enhances the chances of finding a statistically significant difference if one exists. The aim of this paper was to review and discuss common statistical designs relating to types of error and statistical approaches to error accountability. This paper addresses issues of landmark location, validity, technical and systematic error, analysis of variance, scaled measures and correlation coefficients in order to guide the reader towards correct identification of true experimental differences. Researchers commonly infer characteristics about populations from comparatively restricted study samples. Most inferences are statistical and, aside from concerns about adequate accounting for known sources of variation with the research design, an important source of variability is measurement error. Variability in locating landmarks that define variables is obvious in odontometrics, cephalometrics and anthropometry, but the same concerns about measurement accuracy and precision extend to all disciplines. With increasing accessibility to computer-assisted methods of data collection, the ease of incorporating repeated measures into statistical designs has improved. Accounting for this technical source of variation increases the chance of finding biologically true differences when they exist.
Automatic diagnostic system for measuring ocular refractive errors

Science.gov (United States)

Ventura, Liliane; Chiaradia, Caio; de Sousa, Sidney J. F.; de Castro, Jarbas C.

1996-05-01

Ocular refractive errors (myopia, hyperopia and astigmatism) are automatic and objectively determined by projecting a light target onto the retina using an infra-red (850 nm) diode laser. The light vergence which emerges from the eye (light scattered from the retina) is evaluated in order to determine the corresponding ametropia. The system basically consists of projecting a target (ring) onto the retina and analyzing the scattered light with a CCD camera. The light scattered by the eye is divided into six portions (3 meridians) by using a mask and a set of six prisms. The distance between the two images provided by each of the meridians, leads to the refractive error of the referred meridian. Hence, it is possible to determine the refractive error at three different meridians, which gives the exact solution for the eye's refractive error (spherical and cylindrical components and the axis of the astigmatism). The computational basis used for the image analysis is a heuristic search, which provides satisfactory calculation times for our purposes. The peculiar shape of the target, a ring, provides a wider range of measurement and also saves parts of the retina from unnecessary laser irradiation. Measurements were done in artificial and in vivo eyes (using cicloplegics) and the results were in good agreement with the retinoscopic measurements.
Error Modelling for Multi-Sensor Measurements in Infrastructure-Free Indoor Navigation

Directory of Open Access Journals (Sweden)

Laura Ruotsalainen

2018-02-01

Full Text Available The long-term objective of our research is to develop a method for infrastructure-free simultaneous localization and mapping (SLAM and context recognition for tactical situational awareness. Localization will be realized by propagating motion measurements obtained using a monocular camera, a foot-mounted Inertial Measurement Unit (IMU, sonar, and a barometer. Due to the size and weight requirements set by tactical applications, Micro-Electro-Mechanical (MEMS sensors will be used. However, MEMS sensors suffer from biases and drift errors that may substantially decrease the position accuracy. Therefore, sophisticated error modelling and implementation of integration algorithms are key for providing a viable result. Algorithms used for multi-sensor fusion have traditionally been different versions of Kalman filters. However, Kalman filters are based on the assumptions that the state propagation and measurement models are linear with additive Gaussian noise. Neither of the assumptions is correct for tactical applications, especially for dismounted soldiers, or rescue personnel. Therefore, error modelling and implementation of advanced fusion algorithms are essential for providing a viable result. Our approach is to use particle filtering (PF, which is a sophisticated option for integrating measurements emerging from pedestrian motion having non-Gaussian error characteristics. This paper discusses the statistical modelling of the measurement errors from inertial sensors and vision based heading and translation measurements to include the correct error probability density functions (pdf in the particle filter implementation. Then, model fitting is used to verify the pdfs of the measurement errors. Based on the deduced error models of the measurements, particle filtering method is developed to fuse all this information, where the weights of each particle are computed based on the specific models derived. The performance of the developed method is
Bayesian modeling of measurement error in predictor variables using item response theory

NARCIS (Netherlands)

Fox, Gerardus J.A.; Glas, Cornelis A.W.

2000-01-01

This paper focuses on handling measurement error in predictor variables using item response theory (IRT). Measurement error is of great important in assessment of theoretical constructs, such as intelligence or the school climate. Measurement error is modeled by treating the predictors as unobserved
On the determinants of measurement error in time-driven costing

NARCIS (Netherlands)

Cardinaels, E.; Labro, E.

2008-01-01

Although time estimates are used extensively for costing purposes, they are prone to measurement error. In an experimental setting, we research how measurement error in time estimates varies with: (1) the level of aggregation in the definition of costing system activities (aggregated or
The regression-calibration method for fitting generalized linear models with additive measurement error

OpenAIRE

James W. Hardin; Henrik Schmeidiche; Raymond J. Carroll

2003-01-01

This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). Discussion will include specified measurement error, measurement error estimated by replicate error-prone proxies, and measurement error estimated by instrumental variables. The discussion focuses on s...
A generalized right truncated bivariate Poisson regression model with applications to health data.

Science.gov (United States)

Islam, M Ataharul; Chowdhury, Rafiqul I

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model.
Study of errors in absolute flux density measurements of Cassiopeia A

International Nuclear Information System (INIS)

Kanda, M.

1975-10-01

An error analysis for absolute flux density measurements of Cassiopeia A is discussed. The lower-bound quadrature-accumulation error for state-of-the-art measurements of the absolute flux density of Cas A around 7 GHz is estimated to be 1.71% for 3 sigma limits. The corresponding practicable error for the careful but not state-of-the-art measurement is estimated to be 4.46% for 3 sigma limits
Tests for detecting overdispersion in models with measurement error in covariates.

Science.gov (United States)

Yang, Yingsi; Wong, Man Yu

2015-11-30

Measurement error in covariates can affect the accuracy in count data modeling and analysis. In overdispersion identification, the true mean-variance relationship can be obscured under the influence of measurement error in covariates. In this paper, we propose three tests for detecting overdispersion when covariates are measured with error: a modified score test and two score tests based on the proposed approximate likelihood and quasi-likelihood, respectively. The proposed approximate likelihood is derived under the classical measurement error model, and the resulting approximate maximum likelihood estimator is shown to have superior efficiency. Simulation results also show that the score test based on approximate likelihood outperforms the test based on quasi-likelihood and other alternatives in terms of empirical power. By analyzing a real dataset containing the health-related quality-of-life measurements of a particular group of patients, we demonstrate the importance of the proposed methods by showing that the analyses with and without measurement error correction yield significantly different results. Copyright © 2015 John Wiley & Sons, Ltd.
A comparison of bivariate and univariate QTL mapping in livestock populations

Directory of Open Access Journals (Sweden)

Sorensen Daniel

2003-11-01

Full Text Available Abstract This study presents a multivariate, variance component-based QTL mapping model implemented via restricted maximum likelihood (REML. The method was applied to investigate bivariate and univariate QTL mapping analyses, using simulated data. Specifically, we report results on the statistical power to detect a QTL and on the precision of parameter estimates using univariate and bivariate approaches. The model and methodology were also applied to study the effectiveness of partitioning the overall genetic correlation between two traits into a component due to many genes of small effect, and one due to the QTL. It is shown that when the QTL has a pleiotropic effect on two traits, a bivariate analysis leads to a higher statistical power of detecting the QTL and to a more precise estimate of the QTL's map position, in particular in the case when the QTL has a small effect on the trait. The increase in power is most marked in cases where the contributions of the QTL and of the polygenic components to the genetic correlation have opposite signs. The bivariate REML analysis can successfully partition the two components contributing to the genetic correlation between traits.
Effects of Shame and Guilt on Error Reporting Among Obstetric Clinicians.

Science.gov (United States)

Zabari, Mara Lynne; Southern, Nancy L

2018-04-17

To understand how the experiences of shame and guilt, coupled with organizational factors, affect error reporting by obstetric clinicians. Descriptive cross-sectional. A sample of 84 obstetric clinicians from three maternity units in Washington State. In this quantitative inquiry, a variant of the Test of Self-Conscious Affect was used to measure proneness to guilt and shame. In addition, we developed questions to assess attitudes regarding concerns about damaging one's reputation if an error was reported and the choice to keep an error to oneself. Both assessments were analyzed separately and then correlated to identify relationships between constructs. Interviews were used to identify organizational factors that affect error reporting. As a group, mean scores indicated that obstetric clinicians would not choose to keep errors to themselves. However, bivariate correlations showed that proneness to shame was positively correlated to concerns about one's reputation if an error was reported, and proneness to guilt was negatively correlated with keeping errors to oneself. Interview data analysis showed that Past Experience with Responses to Errors, Management and Leadership Styles, Professional Hierarchy, and Relationships With Colleagues were influential factors in error reporting. Although obstetric clinicians want to report errors, their decisions to report are influenced by their proneness to guilt and shame and perceptions of the degree to which organizational factors facilitate or create barriers to restore their self-images. Findings underscore the influence of the organizational context on clinicians' decisions to report errors. Copyright © 2018 AWHONN, the Association of Women’s Health, Obstetric and Neonatal Nurses. Published by Elsevier Inc. All rights reserved.
A bivariate Chebyshev spectral collocation quasilinearization method for nonlinear evolution parabolic equations.

Science.gov (United States)

Motsa, S S; Magagula, V M; Sibanda, P

2014-01-01

This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs). The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature.
A Bivariate Chebyshev Spectral Collocation Quasilinearization Method for Nonlinear Evolution Parabolic Equations

Directory of Open Access Journals (Sweden)

S. S. Motsa

2014-01-01

Full Text Available This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs. The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature.

Measurement Error in Income and Schooling and the Bias of Linear Estimators

DEFF Research Database (Denmark)

Bingley, Paul; Martinello, Alessandro

2017-01-01

and Retirement in Europe data with Danish administrative registers. Contrary to most validation studies, we find that measurement error in income is classical once we account for imperfect validation data. We find nonclassical measurement error in schooling, causing a 38% amplification bias in IV estimators......We propose a general framework for determining the extent of measurement error bias in ordinary least squares and instrumental variable (IV) estimators of linear models while allowing for measurement error in the validation source. We apply this method by validating Survey of Health, Ageing...
Analysis of measured data of human body based on error correcting frequency

Science.gov (United States)

Jin, Aiyan; Peipei, Gao; Shang, Xiaomei

2014-04-01

Anthropometry is to measure all parts of human body surface, and the measured data is the basis of analysis and study of the human body, establishment and modification of garment size and formulation and implementation of online clothing store. In this paper, several groups of the measured data are gained, and analysis of data error is gotten by analyzing the error frequency and using analysis of variance method in mathematical statistics method. Determination of the measured data accuracy and the difficulty of measured parts of human body, further studies of the causes of data errors, and summarization of the key points to minimize errors possibly are also mentioned in the paper. This paper analyses the measured data based on error frequency, and in a way , it provides certain reference elements to promote the garment industry development.
Measurements of stem diameter: implications for individual- and stand-level errors.

Science.gov (United States)

Paul, Keryn I; Larmour, John S; Roxburgh, Stephen H; England, Jacqueline R; Davies, Micah J; Luck, Hamish D

2017-08-01

Stem diameter is one of the most common measurements made to assess the growth of woody vegetation, and the commercial and environmental benefits that it provides (e.g. wood or biomass products, carbon sequestration, landscape remediation). Yet inconsistency in its measurement is a continuing source of error in estimates of stand-scale measures such as basal area, biomass, and volume. Here we assessed errors in stem diameter measurement through repeated measurements of individual trees and shrubs of varying size and form (i.e. single- and multi-stemmed) across a range of contrasting stands, from complex mixed-species plantings to commercial single-species plantations. We compared a standard diameter tape with a Stepped Diameter Gauge (SDG) for time efficiency and measurement error. Measurement errors in diameter were slightly (but significantly) influenced by size and form of the tree or shrub, and stem height at which the measurement was made. Compared to standard tape measurement, the mean systematic error with SDG measurement was only -0.17 cm, but varied between -0.10 and -0.52 cm. Similarly, random error was relatively large, with standard deviations (and percentage coefficients of variation) averaging only 0.36 cm (and 3.8%), but varying between 0.14 and 0.61 cm (and 1.9 and 7.1%). However, at the stand scale, sampling errors (i.e. how well individual trees or shrubs selected for measurement of diameter represented the true stand population in terms of the average and distribution of diameter) generally had at least a tenfold greater influence on random errors in basal area estimates than errors in diameter measurements. This supports the use of diameter measurement tools that have high efficiency, such as the SDG. Use of the SDG almost halved the time required for measurements compared to the diameter tape. Based on these findings, recommendations include the following: (i) use of a tape to maximise accuracy when developing allometric models, or when
Comparison between two bivariate Poisson distributions through the ...

African Journals Online (AJOL)

These two models express themselves by their probability mass function. ... To remedy this problem, Berkhout and Plug proposed a bivariate Poisson distribution accepting the correlation as well negative, equal to zero, that positive.
Sensor Interaction as a Source of the Electromagnetic Field Measurement Error

Directory of Open Access Journals (Sweden)

Hartansky R.

2014-12-01

Full Text Available The article deals with analytical calculation and numerical simulation of interactive influence of electromagnetic sensors. Sensors are components of field probe, whereby their interactive influence causes the measuring error. Electromagnetic field probe contains three mutually perpendicular spaced sensors in order to measure the vector of electrical field. Error of sensors is enumerated with dependence on interactive position of sensors. Based on that, proposed were recommendations for electromagnetic field probe construction to minimize the sensor interaction and measuring error.
MEASURING LOCAL GRADIENT AND SKEW QUADRUPOLE ERRORS IN RHIC IRS

International Nuclear Information System (INIS)

CARDONA, J.; PEGGS, S.; PILAT, R.; PTITSYN, V.

2004-01-01

The measurement of local linear errors at RHIC interaction regions using an ''action and phase'' analysis of difference orbits has already been presented [2]. This paper evaluates the accuracy of this technique using difference orbits that were taken when known gradient errors and skew quadrupole errors were intentionally introduced. It also presents action and phase analysis of simulated orbits when controlled errors are intentionally placed in a RHIC simulation model
Bivariate least squares linear regression: Towards a unified analytic formalism. I. Functional models

Science.gov (United States)

Caimmi, R.

2011-08-01

Concerning bivariate least squares linear regression, the classical approach pursued for functional models in earlier attempts ( York, 1966, 1969) is reviewed using a new formalism in terms of deviation (matrix) traces which, for unweighted data, reduce to usual quantities leaving aside an unessential (but dimensional) multiplicative factor. Within the framework of classical error models, the dependent variable relates to the independent variable according to the usual additive model. The classes of linear models considered are regression lines in the general case of correlated errors in X and in Y for weighted data, and in the opposite limiting situations of (i) uncorrelated errors in X and in Y, and (ii) completely correlated errors in X and in Y. The special case of (C) generalized orthogonal regression is considered in detail together with well known subcases, namely: (Y) errors in X negligible (ideally null) with respect to errors in Y; (X) errors in Y negligible (ideally null) with respect to errors in X; (O) genuine orthogonal regression; (R) reduced major-axis regression. In the limit of unweighted data, the results determined for functional models are compared with their counterparts related to extreme structural models i.e. the instrumental scatter is negligible (ideally null) with respect to the intrinsic scatter ( Isobe et al., 1990; Feigelson and Babu, 1992). While regression line slope and intercept estimators for functional and structural models necessarily coincide, the contrary holds for related variance estimators even if the residuals obey a Gaussian distribution, with the exception of Y models. An example of astronomical application is considered, concerning the [O/H]-[Fe/H] empirical relations deduced from five samples related to different stars and/or different methods of oxygen abundance determination. For selected samples and assigned methods, different regression models yield consistent results within the errors (∓ σ) for both
Application of round grating angle measurement composite error amendment in the online measurement accuracy improvement of large diameter

Science.gov (United States)

Wang, Biao; Yu, Xiaofen; Li, Qinzhao; Zheng, Yu

2008-10-01

The paper aiming at the influence factor of round grating dividing error, rolling-wheel produce eccentricity and surface shape errors provides an amendment method based on rolling-wheel to get the composite error model which includes all influence factors above, and then corrects the non-circle measurement angle error of the rolling-wheel. We make soft simulation verification and have experiment; the result indicates that the composite error amendment method can improve the diameter measurement accuracy with rolling-wheel theory. It has wide application prospect for the measurement accuracy higher than 5 μm/m.
Causal networks clarify productivity-richness interrelations, bivariate plots do not

Science.gov (United States)

Grace, James B.; Adler, Peter B.; Harpole, W. Stanley; Borer, Elizabeth T.; Seabloom, Eric W.

2014-01-01

Perhaps no other pair of variables in ecology has generated as much discussion as species richness and ecosystem productivity, as illustrated by the reactions by Pierce (2013) and others to Adler et al.'s (2011) report that empirical patterns are weak and inconsistent. Adler et al. (2011) argued we need to move beyond a focus on simplistic bivariate relationships and test mechanistic, multivariate causal hypotheses. We feel the continuing debate over productivity–richness relationships (PRRs) provides a focused context for illustrating the fundamental difficulties of using bivariate relationships to gain scientific understanding.
Laser tracker error determination using a network measurement

International Nuclear Information System (INIS)

Hughes, Ben; Forbes, Alistair; Lewis, Andrew; Sun, Wenjuan; Veal, Dan; Nasr, Karim

2011-01-01

We report on a fast, easily implemented method to determine all the geometrical alignment errors of a laser tracker, to high precision. The technique requires no specialist equipment and can be performed in less than an hour. The technique is based on the determination of parameters of a geometric model of the laser tracker, using measurements of a set of fixed target locations, from multiple locations of the tracker. After fitting of the model parameters to the observed data, the model can be used to perform error correction of the raw laser tracker data or to derive correction parameters in the format of the tracker manufacturer's internal error map. In addition to determination of the model parameters, the method also determines the uncertainties and correlations associated with the parameters. We have tested the technique on a commercial laser tracker in the following way. We disabled the tracker's internal error compensation, and used a five-position, fifteen-target network to estimate all the geometric errors of the instrument. Using the error map generated from this network test, the tracker was able to pass a full performance validation test, conducted according to a recognized specification standard (ASME B89.4.19-2006). We conclude that the error correction determined from the network test is as effective as the manufacturer's own error correction methodologies
A bivariate model for analyzing recurrent multi-type automobile failures

Science.gov (United States)

Sunethra, A. A.; Sooriyarachchi, M. R.

2017-09-01

The failure mechanism in an automobile can be defined as a system of multi-type recurrent failures where failures can occur due to various multi-type failure modes and these failures are repetitive such that more than one failure can occur from each failure mode. In analysing such automobile failures, both the time and type of the failure serve as response variables. However, these two response variables are highly correlated with each other since the timing of failures has an association with the mode of the failure. When there are more than one correlated response variables, the fitting of a multivariate model is more preferable than separate univariate models. Therefore, a bivariate model of time and type of failure becomes appealing for such automobile failure data. When there are multiple failure observations pertaining to a single automobile, such data cannot be treated as independent data because failure instances of a single automobile are correlated with each other while failures among different automobiles can be treated as independent. Therefore, this study proposes a bivariate model consisting time and type of failure as responses adjusted for correlated data. The proposed model was formulated following the approaches of shared parameter models and random effects models for joining the responses and for representing the correlated data respectively. The proposed model is applied to a sample of automobile failures with three types of failure modes and up to five failure recurrences. The parametric distributions that were suitable for the two responses of time to failure and type of failure were Weibull distribution and multinomial distribution respectively. The proposed bivariate model was programmed in SAS Procedure Proc NLMIXED by user programming appropriate likelihood functions. The performance of the bivariate model was compared with separate univariate models fitted for the two responses and it was identified that better performance is secured by
Improved characterisation and modelling of measurement errors in electrical resistivity tomography (ERT) surveys

Science.gov (United States)

Tso, Chak-Hau Michael; Kuras, Oliver; Wilkinson, Paul B.; Uhlemann, Sebastian; Chambers, Jonathan E.; Meldrum, Philip I.; Graham, James; Sherlock, Emma F.; Binley, Andrew

2017-11-01

Measurement errors can play a pivotal role in geophysical inversion. Most inverse models require users to prescribe or assume a statistical model of data errors before inversion. Wrongly prescribed errors can lead to over- or under-fitting of data; however, the derivation of models of data errors is often neglected. With the heightening interest in uncertainty estimation within hydrogeophysics, better characterisation and treatment of measurement errors is needed to provide improved image appraisal. Here we focus on the role of measurement errors in electrical resistivity tomography (ERT). We have analysed two time-lapse ERT datasets: one contains 96 sets of direct and reciprocal data collected from a surface ERT line within a 24 h timeframe; the other is a two-year-long cross-borehole survey at a UK nuclear site with 246 sets of over 50,000 measurements. Our study includes the characterisation of the spatial and temporal behaviour of measurement errors using autocorrelation and correlation coefficient analysis. We find that, in addition to well-known proportionality effects, ERT measurements can also be sensitive to the combination of electrodes used, i.e. errors may not be uncorrelated as often assumed. Based on these findings, we develop a new error model that allows grouping based on electrode number in addition to fitting a linear model to transfer resistance. The new model explains the observed measurement errors better and shows superior inversion results and uncertainty estimates in synthetic examples. It is robust, because it groups errors together based on the electrodes used to make the measurements. The new model can be readily applied to the diagonal data weighting matrix widely used in common inversion methods, as well as to the data covariance matrix in a Bayesian inversion framework. We demonstrate its application using extensive ERT monitoring datasets from the two aforementioned sites.
Statistical analysis with measurement error or misclassification strategy, method and application

CERN Document Server

Yi, Grace Y

2017-01-01

This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems. Readers with diverse backgrounds and objectives can utilize th...
Bivariate quadratic method in quantifying the differential capacitance and energy capacity of supercapacitors under high current operation

Science.gov (United States)

Goh, Chin-Teng; Cruden, Andrew

2014-11-01

Capacitance and resistance are the fundamental electrical parameters used to evaluate the electrical characteristics of a supercapacitor, namely the dynamic voltage response, energy capacity, state of charge and health condition. In the British Standards EN62391 and EN62576, the constant capacitance method can be further improved with a differential capacitance that more accurately describes the dynamic voltage response of supercapacitors. This paper presents a novel bivariate quadratic based method to model the dynamic voltage response of supercapacitors under high current charge-discharge cycling, and to enable the derivation of the differential capacitance and energy capacity directly from terminal measurements, i.e. voltage and current, rather than from multiple pulsed-current or excitation signal tests across different bias levels. The estimation results the author achieves are in close agreement with experimental measurements, within a relative error of 0.2%, at various high current levels (25-200 A), more accurate than the constant capacitance method (4-7%). The archival value of this paper is the introduction of an improved quantification method for the electrical characteristics of supercapacitors, and the disclosure of the distinct properties of supercapacitors: the nonlinear capacitance-voltage characteristic, capacitance variation between charging and discharging, and distribution of energy capacity across the operating voltage window.
Utilizing measure-based feedback in control-mastery theory: A clinical error.

Science.gov (United States)

Snyder, John; Aafjes-van Doorn, Katie

2016-09-01

Clinical errors and ruptures are an inevitable part of clinical practice. Often times, therapists are unaware that a clinical error or rupture has occurred, leaving no space for repair, and potentially leading to patient dropout and/or less effective treatment. One way to overcome our blind spots is by frequently and systematically collecting measure-based feedback from the patient. Patient feedback measures that focus on the process of psychotherapy such as the Patient's Experience of Attunement and Responsiveness scale (PEAR) can be used in conjunction with treatment outcome measures such as the Outcome Questionnaire 45.2 (OQ-45.2) to monitor the patient's therapeutic experience and progress. The regular use of these types of measures can aid clinicians in the identification of clinical errors and the associated patient deterioration that might otherwise go unnoticed and unaddressed. The current case study describes an instance of clinical error that occurred during the 2-year treatment of a highly traumatized young woman. The clinical error was identified using measure-based feedback and subsequently understood and addressed from the theoretical standpoint of the control-mastery theory of psychotherapy. An alternative hypothetical response is also presented and explained using control-mastery theory. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Measurement of the magnetic field errors on TCV

International Nuclear Information System (INIS)

Piras, F.; Moret, J.-M.; Rossel, J.X.

2010-01-01

A set of 24 saddle loops is used on the Tokamak a Configuration Variable (TCV) to measure the radial magnetic flux at different toroidal and vertical positions. The new system is calibrated together with the standard magnetic diagnostics on TCV. Based on the results of this calibration, the effective current in the poloidal field coils and their position is computed. These corrections are then used to compute the distribution of the error field inside the vacuum vessel for a typical TCV discharge. Since the saddle loops measure the magnetic flux at different toroidal positions, the non-axisymmetric error field is also estimated and correlated to a shift or a tilt of the poloidal field coils.
Measurement error in pressure-decay leak testing

International Nuclear Information System (INIS)

Robinson, J.N.

1979-04-01

The effect of measurement error in presssure-decay leak testing is considered, and examples are presented to demonstrate how it can be properly accomodated in analyzing data from such tests. Suggestions for more effective specification and conduct of leak tests are presented
Accounting for covariate measurement error in a Cox model analysis of recurrence of depression.

Science.gov (United States)

Liu, K; Mazumdar, S; Stone, R A; Dew, M A; Houck, P R; Reynolds, C F

2001-01-01

When a covariate measured with error is used as a predictor in a survival analysis using the Cox model, the parameter estimate is usually biased. In clinical research, covariates measured without error such as treatment procedure or sex are often used in conjunction with a covariate measured with error. In a randomized clinical trial of two types of treatments, we account for the measurement error in the covariate, log-transformed total rapid eye movement (REM) activity counts, in a Cox model analysis of the time to recurrence of major depression in an elderly population. Regression calibration and two variants of a likelihood-based approach are used to account for measurement error. The likelihood-based approach is extended to account for the correlation between replicate measures of the covariate. Using the replicate data decreases the standard error of the parameter estimate for log(total REM) counts while maintaining the bias reduction of the estimate. We conclude that covariate measurement error and the correlation between replicates can affect results in a Cox model analysis and should be accounted for. In the depression data, these methods render comparable results that have less bias than the results when measurement error is ignored.
Measurement error in longitudinal film badge data

International Nuclear Information System (INIS)

Marsh, J.L.

2002-04-01

The classical measurement error model is that of a simple linear regression with unobservable variables. Information about the covariates is available only through error-prone measurements, usually with an additive structure. Ignoring errors has been shown to result in biased regression coefficients, reduced power of hypothesis tests and increased variability of parameter estimates. Radiation is known to be a causal factor for certain types of leukaemia. This link is mainly substantiated by the Atomic Bomb Survivor study, the Ankylosing Spondylitis Patients study, and studies of various other patients irradiated for therapeutic purposes. The carcinogenic relationship is believed to be a linear or quadratic function of dose but the risk estimates differ widely for the different studies. Previous cohort studies of the Sellafield workforce have used the cumulative annual exposure data for their risk estimates. The current 1:4 matched case-control study also uses the individual worker's film badge data, the majority of which has been unavailable in computerised form. The results from the 1:4 matched (on dates of birth and employment, sex and industrial status) case-control study are compared and contrasted with those for a 1:4 nested (within the worker cohort and matched on the same factors) case-control study using annual doses. The data consist of 186 cases and 744 controls from the work forces of four BNFL sites: Springfields, Sellafield, Capenhurst and Chapelcross. Initial logistic regressions turned up some surprising contradictory results which led to a re-sampling of Sellafield mortality controls without the date of employment matching factor. It is suggested that over matching is the cause of the contradictory results. Comparisons of the two measurements of radiation exposure suggest a strongly linear relationship with non-Normal errors. A method has been developed using the technique of Regression Calibration to deal with these in a case-control study context
Probability distributions with truncated, log and bivariate extensions

CERN Document Server

Thomopoulos, Nick T

2018-01-01

This volume presents a concise and practical overview of statistical methods and tables not readily available in other publications. It begins with a review of the commonly used continuous and discrete probability distributions. Several useful distributions that are not so common and less understood are described with examples and applications in full detail: discrete normal, left-partial, right-partial, left-truncated normal, right-truncated normal, lognormal, bivariate normal, and bivariate lognormal. Table values are provided with examples that enable researchers to easily apply the distributions to real applications and sample data. The left- and right-truncated normal distributions offer a wide variety of shapes in contrast to the symmetrically shaped normal distribution, and a newly developed spread ratio enables analysts to determine which of the three distributions best fits a particular set of sample data. The book will be highly useful to anyone who does statistical and probability analysis. This in...

Swath-altimetry measurements of the main stem Amazon River: measurement errors and hydraulic implications

Science.gov (United States)

Wilson, M. D.; Durand, M.; Jung, H. C.; Alsdorf, D.

2015-04-01

The Surface Water and Ocean Topography (SWOT) mission, scheduled for launch in 2020, will provide a step-change improvement in the measurement of terrestrial surface-water storage and dynamics. In particular, it will provide the first, routine two-dimensional measurements of water-surface elevations. In this paper, we aimed to (i) characterise and illustrate in two dimensions the errors which may be found in SWOT swath measurements of terrestrial surface water, (ii) simulate the spatio-temporal sampling scheme of SWOT for the Amazon, and (iii) assess the impact of each of these on estimates of water-surface slope and river discharge which may be obtained from SWOT imagery. We based our analysis on a virtual mission for a ~260 km reach of the central Amazon (Solimões) River, using a hydraulic model to provide water-surface elevations according to SWOT spatio-temporal sampling to which errors were added based on a two-dimensional height error spectrum derived from the SWOT design requirements. We thereby obtained water-surface elevation measurements for the Amazon main stem as may be observed by SWOT. Using these measurements, we derived estimates of river slope and discharge and compared them to those obtained directly from the hydraulic model. We found that cross-channel and along-reach averaging of SWOT measurements using reach lengths greater than 4 km for the Solimões and 7.5 km for Purus reduced the effect of systematic height errors, enabling discharge to be reproduced accurately from the water height, assuming known bathymetry and friction. Using cross-sectional averaging and 20 km reach lengths, results show Nash-Sutcliffe model efficiency values of 0.99 for the Solimões and 0.88 for the Purus, with 2.6 and 19.1 % average overall error in discharge, respectively. We extend the results to other rivers worldwide and infer that SWOT-derived discharge estimates may be more accurate for rivers with larger channel widths (permitting a greater level of cross
Linear and nonlinear magnetic error measurements using action and phase jump analysis

Directory of Open Access Journals (Sweden)

Javier F. Cardona

2009-01-01

Full Text Available “Action and phase jump” analysis is presented—a beam based method that uses amplitude and phase knowledge of a particle trajectory to locate and measure magnetic errors in an accelerator lattice. The expected performance of the method is first tested using single-particle simulations in the optical lattice of the Relativistic Heavy Ion Collider (RHIC. Such simulations predict that under ideal conditions typical quadrupole errors can be estimated within an uncertainty of 0.04%. Other simulations suggest that sextupole errors can be estimated within a 3% uncertainty. Then the action and phase jump analysis is applied to real RHIC orbits with known quadrupole errors, and to real Super Proton Synchrotron (SPS orbits with known sextupole errors. It is possible to estimate the strength of a skew quadrupole error from measured RHIC orbits within a 1.2% uncertainty, and to estimate the strength of a strong sextupole component from the measured SPS orbits within a 7% uncertainty.
Period, epoch, and prediction errors of ephemerides from continuous sets of timing measurements

Science.gov (United States)

Deeg, H. J.

2015-06-01

Space missions such as Kepler and CoRoT have led to large numbers of eclipse or transit measurements in nearly continuous time series. This paper shows how to obtain the period error in such measurements from a basic linear least-squares fit, and how to correctly derive the timing error in the prediction of future transit or eclipse events. Assuming strict periodicity, a formula for the period error of these time series is derived, σP = σT (12 / (N3-N))1 / 2, where σP is the period error, σT the timing error of a single measurement, and N the number of measurements. Compared to the iterative method for period error estimation by Mighell & Plavchan (2013), this much simpler formula leads to smaller period errors, whose correctness has been verified through simulations. For the prediction of times of future periodic events, usual linear ephemeris were epoch errors are quoted for the first time measurement, are prone to an overestimation of the error of that prediction. This may be avoided by a correction for the duration of the time series. An alternative is the derivation of ephemerides whose reference epoch and epoch error are given for the centre of the time series. For long continuous or near-continuous time series whose acquisition is completed, such central epochs should be the preferred way for the quotation of linear ephemerides. While this work was motivated from the analysis of eclipse timing measures in space-based light curves, it should be applicable to any other problem with an uninterrupted sequence of discrete timings for which the determination of a zero point, of a constant period and of the associated errors is needed.
Development of an Experimental Measurement System for Human Error Characteristics and a Pilot Test

International Nuclear Information System (INIS)

Jang, Tong-Il; Lee, Hyun-Chul; Moon, Kwangsu

2017-01-01

Some items out of individual and team characteristics were partially selected, and a pilot test was performed to measure and evaluate them using the experimental measurement system of human error characteristics. It is one of the processes to produce input data to the Eco-DBMS. And also, through the pilot test, it was tried to take methods to measure and acquire the physiological data, and to develop data format and quantification methods for the database. In this study, a pilot test to measure the stress and the tension level, and team cognitive characteristics out of human error characteristics was performed using the human error characteristics measurement and experimental evaluation system. In an experiment measuring the stress level, physiological characteristics using EEG was measured in a simulated unexpected situation. As shown in results, although this experiment was pilot, it was validated that relevant results for evaluating human error coping effects of workers’ FFD management guidelines and unexpected situation against guidelines can be obtained. In following researches, additional experiments including other human error characteristics will be conducted. Furthermore, the human error characteristics measurement and experimental evaluation system will be utilized to validate various human error coping solutions such as human factors criteria, design, and guidelines as well as supplement the human error characteristics database.
Design and application of location error teaching aids in measuring and visualization

Directory of Open Access Journals (Sweden)

Yu Fengning

2015-01-01

Full Text Available As an abstract concept, ‘location error’ in is considered to be an important element with great difficult to understand and apply. The paper designs and develops an instrument to measure the location error. The location error is affected by different position methods and reference selection. So we choose position element by rotating the disk. The tiny movement transfers by grating ruler and programming by PLC can show the error on text display, which also helps students understand the position principle and related concepts of location error. After comparing measurement results with theoretical calculations and analyzing the measurement accuracy, the paper draws a conclusion that the teaching aid owns reliability and a promotion of high value.
Francesca Hughes: Architecture of Error: Matter, Measure and the Misadventure of Precision

DEFF Research Database (Denmark)

Foote, Jonathan

2016-01-01

Review of "Architecture of Error: Matter, Measure and the Misadventure of Precision" by Francesca Hughes (MIT Press, 2014)......Review of "Architecture of Error: Matter, Measure and the Misadventure of Precision" by Francesca Hughes (MIT Press, 2014)...
Errors due to random noise in velocity measurement using incoherent-scatter radar

Directory of Open Access Journals (Sweden)

P. J. S. Williams

1996-12-01

Full Text Available The random-noise errors involved in measuring the Doppler shift of an 'incoherent-scatter' spectrum are predicted theoretically for all values of Te/Ti from 1.0 to 3.0. After correction has been made for the effects of convolution during transmission and reception and the additional errors introduced by subtracting the average of the background gates, the rms errors can be expressed by a simple semi-empirical formula. The observed errors are determined from a comparison of simultaneous EISCAT measurements using an identical pulse code on several adjacent frequencies. The plot of observed versus predicted error has a slope of 0.991 and a correlation coefficient of 99.3%. The prediction also agrees well with the mean of the error distribution reported by the standard EISCAT analysis programme.
Errors in measuring transverse and energy jitter by beam position monitors

Energy Technology Data Exchange (ETDEWEB)

Balandin, V.; Decking, W.; Golubeva, N.

2010-02-15

The problem of errors, arising due to finite BPMresolution, in the difference orbit parameters, which are found as a least squares fit to the BPM data, is one of the standard and important problems of accelerator physics. Even so for the case of transversely uncoupled motion the covariance matrix of reconstruction errors can be calculated ''by hand'', the direct usage of obtained solution, as a tool for designing of a ''good measurement system'', does not look to be fairly straightforward. It seems that a better understanding of the nature of the problem is still desirable. We make a step in this direction introducing dynamic into this problem, which at the first glance seems to be static. We consider a virtual beam consisting of virtual particles obtained as a result of application of reconstruction procedure to ''all possible values'' of BPM reading errors. This beam propagates along the beam line according to the same rules as any real beam and has all beam dynamical characteristics, such as emittances, energy spread, dispersions, betatron functions and etc. All these values become the properties of the BPM measurement system. One can compare two BPM systems comparing their error emittances and rms error energy spreads, or, for a given measurement system, one can achieve needed balance between coordinate and momentum reconstruction errors by matching the error betatron functions in the point of interest to the desired values. (orig.)
Errors in measuring transverse and energy jitter by beam position monitors

International Nuclear Information System (INIS)

Balandin, V.; Decking, W.; Golubeva, N.

2010-02-01

The problem of errors, arising due to finite BPMresolution, in the difference orbit parameters, which are found as a least squares fit to the BPM data, is one of the standard and important problems of accelerator physics. Even so for the case of transversely uncoupled motion the covariance matrix of reconstruction errors can be calculated ''by hand'', the direct usage of obtained solution, as a tool for designing of a ''good measurement system'', does not look to be fairly straightforward. It seems that a better understanding of the nature of the problem is still desirable. We make a step in this direction introducing dynamic into this problem, which at the first glance seems to be static. We consider a virtual beam consisting of virtual particles obtained as a result of application of reconstruction procedure to ''all possible values'' of BPM reading errors. This beam propagates along the beam line according to the same rules as any real beam and has all beam dynamical characteristics, such as emittances, energy spread, dispersions, betatron functions and etc. All these values become the properties of the BPM measurement system. One can compare two BPM systems comparing their error emittances and rms error energy spreads, or, for a given measurement system, one can achieve needed balance between coordinate and momentum reconstruction errors by matching the error betatron functions in the point of interest to the desired values. (orig.)
Local and omnibus goodness-of-fit tests in classical measurement error models

KAUST Repository

Ma, Yanyuan; Hart, Jeffrey D.; Janicki, Ryan; Carroll, Raymond J.

2010-01-01

We consider functional measurement error models, i.e. models where covariates are measured with error and yet no distributional assumptions are made about the mismeasured variable. We propose and study a score-type local test and an orthogonal
Confounding and exposure measurement error in air pollution epidemiology.

Science.gov (United States)

Sheppard, Lianne; Burnett, Richard T; Szpiro, Adam A; Kim, Sun-Young; Jerrett, Michael; Pope, C Arden; Brunekreef, Bert

2012-06-01

Studies in air pollution epidemiology may suffer from some specific forms of confounding and exposure measurement error. This contribution discusses these, mostly in the framework of cohort studies. Evaluation of potential confounding is critical in studies of the health effects of air pollution. The association between long-term exposure to ambient air pollution and mortality has been investigated using cohort studies in which subjects are followed over time with respect to their vital status. In such studies, control for individual-level confounders such as smoking is important, as is control for area-level confounders such as neighborhood socio-economic status. In addition, there may be spatial dependencies in the survival data that need to be addressed. These issues are illustrated using the American Cancer Society Cancer Prevention II cohort. Exposure measurement error is a challenge in epidemiology because inference about health effects can be incorrect when the measured or predicted exposure used in the analysis is different from the underlying true exposure. Air pollution epidemiology rarely if ever uses personal measurements of exposure for reasons of cost and feasibility. Exposure measurement error in air pollution epidemiology comes in various dominant forms, which are different for time-series and cohort studies. The challenges are reviewed and a number of suggested solutions are discussed for both study domains.
The error analysis of coke moisture measured by neutron moisture gauge

International Nuclear Information System (INIS)

Tian Huixing

1995-01-01

The error of coke moisture measured by neutron method in the iron and steel industry is analyzed. The errors are caused by inaccurate sampling location in the calibration procedure on site. By comparison, the instrument error and the statistical fluctuation error are smaller. So the sampling proportion should be increased as large as possible in the calibration procedure on site, and a satisfied calibration effect can be obtained on a suitable size hopper
Bayesian Semiparametric Density Deconvolution in the Presence of Conditionally Heteroscedastic Measurement Errors

KAUST Repository

Sarkar, Abhra

2014-10-02

We consider the problem of estimating the density of a random variable when precise measurements on the variable are not available, but replicated proxies contaminated with measurement error are available for sufficiently many subjects. Under the assumption of additive measurement errors this reduces to a problem of deconvolution of densities. Deconvolution methods often make restrictive and unrealistic assumptions about the density of interest and the distribution of measurement errors, e.g., normality and homoscedasticity and thus independence from the variable of interest. This article relaxes these assumptions and introduces novel Bayesian semiparametric methodology based on Dirichlet process mixture models for robust deconvolution of densities in the presence of conditionally heteroscedastic measurement errors. In particular, the models can adapt to asymmetry, heavy tails and multimodality. In simulation experiments, we show that our methods vastly outperform a recent Bayesian approach based on estimating the densities via mixtures of splines. We apply our methods to data from nutritional epidemiology. Even in the special case when the measurement errors are homoscedastic, our methodology is novel and dominates other methods that have been proposed previously. Additional simulation results, instructions on getting access to the data set and R programs implementing our methods are included as part of online supplemental materials.
Bayesian Semiparametric Density Deconvolution in the Presence of Conditionally Heteroscedastic Measurement Errors

KAUST Repository

Sarkar, Abhra; Mallick, Bani K.; Staudenmayer, John; Pati, Debdeep; Carroll, Raymond J.

2014-01-01

We consider the problem of estimating the density of a random variable when precise measurements on the variable are not available, but replicated proxies contaminated with measurement error are available for sufficiently many subjects. Under the assumption of additive measurement errors this reduces to a problem of deconvolution of densities. Deconvolution methods often make restrictive and unrealistic assumptions about the density of interest and the distribution of measurement errors, e.g., normality and homoscedasticity and thus independence from the variable of interest. This article relaxes these assumptions and introduces novel Bayesian semiparametric methodology based on Dirichlet process mixture models for robust deconvolution of densities in the presence of conditionally heteroscedastic measurement errors. In particular, the models can adapt to asymmetry, heavy tails and multimodality. In simulation experiments, we show that our methods vastly outperform a recent Bayesian approach based on estimating the densities via mixtures of splines. We apply our methods to data from nutritional epidemiology. Even in the special case when the measurement errors are homoscedastic, our methodology is novel and dominates other methods that have been proposed previously. Additional simulation results, instructions on getting access to the data set and R programs implementing our methods are included as part of online supplemental materials.
Measurement error in income and schooling, and the bias of linear estimators

DEFF Research Database (Denmark)

Bingley, Paul; Martinello, Alessandro

The characteristics of measurement error determine the bias of linear estimators. We propose a method for validating economic survey data allowing for measurement error in the validation source, and we apply this method by validating Survey of Health, Ageing and Retirement in Europe (SHARE) data...... with Danish administrative registers. We find that measurement error in surveys is classical for annual gross income but non-classical for years of schooling, causing a 21% amplification bias in IV estimators of returns to schooling. Using a 1958 Danish schooling reform, we contextualize our result...
GIS-Based bivariate statistical techniques for groundwater potential ...

Indian Academy of Sciences (India)

24

This study shows the potency of two GIS-based data driven bivariate techniques namely ... In the view of these weaknesses , there is a strong requirement for reassessment of .... Font color: Text 1, Not Expanded by / Condensed by , ...... West Bengal (India) using remote sensing, geographical information system and multi-.
Tracking and shape errors measurement of concentrating heliostats

Science.gov (United States)

Coquand, Mathieu; Caliot, Cyril; Hénault, François

2017-09-01

In solar tower power plants, factors such as tracking accuracy, facets misalignment and surface shape errors of concentrating heliostats are of prime importance on the efficiency of the system. At industrial scale, one critical issue is the time and effort required to adjust the different mirrors of the faceted heliostats, which could take several months using current techniques. Thus, methods enabling quick adjustment of a field with a huge number of heliostats are essential for the rise of solar tower technology. In this communication is described a new method for heliostat characterization that makes use of four cameras located near the solar receiver and simultaneously recording images of the sun reflected by the optical surfaces. From knowledge of a measured sun profile, data processing of the acquired images allows reconstructing the slope and shape errors of the heliostats, including tracking and canting errors. The mathematical basis of this shape reconstruction process is explained comprehensively. Numerical simulations demonstrate that the measurement accuracy of this "backward-gazing method" is compliant with the requirements of solar concentrating optics. Finally, we present our first experimental results obtained at the THEMIS experimental solar tower plant in Targasonne, France.
Image pre-filtering for measurement error reduction in digital image correlation

Science.gov (United States)

Zhou, Yihao; Sun, Chen; Song, Yuntao; Chen, Jubing

2015-02-01

In digital image correlation, the sub-pixel intensity interpolation causes a systematic error in the measured displacements. The error increases toward high-frequency component of the speckle pattern. In practice, a captured image is usually corrupted by additive white noise. The noise introduces additional energy in the high frequencies and therefore raises the systematic error. Meanwhile, the noise also elevates the random error which increases with the noise power. In order to reduce the systematic error and the random error of the measurements, we apply a pre-filtering to the images prior to the correlation so that the high-frequency contents are suppressed. Two spatial-domain filters (binomial and Gaussian) and two frequency-domain filters (Butterworth and Wiener) are tested on speckle images undergoing both simulated and real-world translations. By evaluating the errors of the various combinations of speckle patterns, interpolators, noise levels, and filter configurations, we come to the following conclusions. All the four filters are able to reduce the systematic error. Meanwhile, the random error can also be reduced if the signal power is mainly distributed around DC. For high-frequency speckle patterns, the low-pass filters (binomial, Gaussian and Butterworth) slightly increase the random error and Butterworth filter produces the lowest random error among them. By using Wiener filter with over-estimated noise power, the random error can be reduced but the resultant systematic error is higher than that of low-pass filters. In general, Butterworth filter is recommended for error reduction due to its flexibility of passband selection and maximal preservation of the allowed frequencies. Binomial filter enables efficient implementation and thus becomes a good option if computational cost is a critical issue. While used together with pre-filtering, B-spline interpolator produces lower systematic error than bicubic interpolator and similar level of the random
Towards New Empirical Versions of Financial and Accounting Models Corrected for Measurement Errors

OpenAIRE

Francois-Éric Racicot; Raymond Théoret; Alain Coen

2006-01-01

In this paper, we propose a new empirical version of the Fama and French Model based on the Hausman (1978) specification test and aimed at discarding measurement errors in the variables. The proposed empirical framework is general enough to be used for correcting other financial and accounting models of measurement errors. Removing measurement errors is important at many levels as information disclosure, corporate governance and protection of investors.
Measurement Error Correction for Predicted Spatiotemporal Air Pollution Exposures.

Science.gov (United States)

Keller, Joshua P; Chang, Howard H; Strickland, Matthew J; Szpiro, Adam A

2017-05-01

Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data. We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap. Third trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35). This study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.

Metrological Array of Cyber-Physical Systems. Part 11. Remote Error Correction of Measuring Channel

Directory of Open Access Journals (Sweden)

Yuriy YATSUK

2015-09-01

Full Text Available The multi-channel measuring instruments with both the classical structure and the isolated one is identified their errors major factors basing on general it metrological properties analysis. Limiting possibilities of the remote automatic method for additive and multiplicative errors correction of measuring instruments with help of code-control measures are studied. For on-site calibration of multi- channel measuring instruments, the portable voltage calibrators structures are suggested and their metrological properties while automatic errors adjusting are analysed. It was experimentally envisaged that unadjusted error value does not exceed ± 1 mV that satisfies most industrial applications. This has confirmed the main approval concerning the possibilities of remote errors self-adjustment as well multi- channel measuring instruments as calibration tools for proper verification.
Assessing the copula selection for bivariate frequency analysis ...

Indian Academy of Sciences (India)

58

Copulas are applied to overcome the restriction of traditional bivariate frequency ... frequency analysis methods cannot describe the random variable properties that ... In order to overcome the limitation of multivariate distributions, a copula is a ..... The Mann-Kendall (M-K) test is a non-parametric statistical test which is used ...
Local and omnibus goodness-of-fit tests in classical measurement error models

KAUST Repository

Ma, Yanyuan

2010-09-14

We consider functional measurement error models, i.e. models where covariates are measured with error and yet no distributional assumptions are made about the mismeasured variable. We propose and study a score-type local test and an orthogonal series-based, omnibus goodness-of-fit test in this context, where no likelihood function is available or calculated-i.e. all the tests are proposed in the semiparametric model framework. We demonstrate that our tests have optimality properties and computational advantages that are similar to those of the classical score tests in the parametric model framework. The test procedures are applicable to several semiparametric extensions of measurement error models, including when the measurement error distribution is estimated non-parametrically as well as for generalized partially linear models. The performance of the local score-type and omnibus goodness-of-fit tests is demonstrated through simulation studies and analysis of a nutrition data set.
Bivariate Genomic Footprinting Detects Changes in Transcription Factor Activity

Directory of Open Access Journals (Sweden)

Songjoon Baek

2017-05-01

Full Text Available In response to activating signals, transcription factors (TFs bind DNA and regulate gene expression. TF binding can be measured by protection of the bound sequence from DNase digestion (i.e., footprint. Here, we report that 80% of TF binding motifs do not show a measurable footprint, partly because of a variable cleavage pattern within the motif sequence. To more faithfully portray the effect of TFs on chromatin, we developed an algorithm that captures two TF-dependent effects on chromatin accessibility: footprinting and motif-flanking accessibility. The algorithm, termed bivariate genomic footprinting (BaGFoot, efficiently detects TF activity. BaGFoot is robust to different accessibility assays (DNase-seq, ATAC-seq, all examined peak-calling programs, and a variety of cut bias correction approaches. BaGFoot reliably predicts TF binding and provides valuable information regarding the TFs affecting chromatin accessibility in various biological systems and following various biological events, including in cases where an absolute footprint cannot be determined.
Influence of video compression on the measurement error of the television system

Science.gov (United States)

Sotnik, A. V.; Yarishev, S. N.; Korotaev, V. V.

2015-05-01

Video data require a very large memory capacity. Optimal ratio quality / volume video encoding method is one of the most actual problem due to the urgent need to transfer large amounts of video over various networks. The technology of digital TV signal compression reduces the amount of data used for video stream representation. Video compression allows effective reduce the stream required for transmission and storage. It is important to take into account the uncertainties caused by compression of the video signal in the case of television measuring systems using. There are a lot digital compression methods. The aim of proposed work is research of video compression influence on the measurement error in television systems. Measurement error of the object parameter is the main characteristic of television measuring systems. Accuracy characterizes the difference between the measured value abd the actual parameter value. Errors caused by the optical system can be selected as a source of error in the television systems measurements. Method of the received video signal processing is also a source of error. Presence of error leads to large distortions in case of compression with constant data stream rate. Presence of errors increases the amount of data required to transmit or record an image frame in case of constant quality. The purpose of the intra-coding is reducing of the spatial redundancy within a frame (or field) of television image. This redundancy caused by the strong correlation between the elements of the image. It is possible to convert an array of image samples into a matrix of coefficients that are not correlated with each other, if one can find corresponding orthogonal transformation. It is possible to apply entropy coding to these uncorrelated coefficients and achieve a reduction in the digital stream. One can select such transformation that most of the matrix coefficients will be almost zero for typical images . Excluding these zero coefficients also
A new accuracy measure based on bounded relative error for time series forecasting.

Science.gov (United States)

Chen, Chao; Twycross, Jamie; Garibaldi, Jonathan M

2017-01-01

Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising commonly used accuracy measures, a special review is made on the symmetric mean absolute percentage error. Moreover, a new accuracy measure called the Unscaled Mean Bounded Relative Absolute Error (UMBRAE), which combines the best features of various alternative measures, is proposed to address the common issues of existing measures. A comparative evaluation on the proposed and related measures has been made with both synthetic and real-world data. The results indicate that the proposed measure, with user selectable benchmark, performs as well as or better than other measures on selected criteria. Though it has been commonly accepted that there is no single best accuracy measure, we suggest that UMBRAE could be a good choice to evaluate forecasting methods, especially for cases where measures based on geometric mean of relative errors, such as the geometric mean relative absolute error, are preferred.
Error Analysis of Ceramographic Sample Preparation for Coating Thickness Measurement of Coated Fuel Particles

International Nuclear Information System (INIS)

Liu Xiaoxue; Li Ziqiang; Zhao Hongsheng; Zhang Kaihong; Tang Chunhe

2014-01-01

The thicknesses of four coatings of HTR coated fuel particle are very important parameters. It is indispensable to control the thickness of four coatings of coated fuel particles for the safety of HTR. A measurement method, ceramographic sample-microanalysis method, to analyze the thickness of coatings was developed. During the process of ceramographic sample-microanalysis, there are two main errors, including ceramographic sample preparation error and thickness measurement error. With the development of microscopic techniques, thickness measurement error can be easily controlled to meet the design requirements. While, due to the coated particles are spherical particles of different diameters ranged from 850 to 1000μm, the sample preparation process will introduce an error. And this error is different from one sample to another. It’s also different from one particle to another in the same sample. In this article, the error of the ceramographic sample preparation was calculated and analyzed. Results show that the error introduced by sample preparation is minor. The minor error of sample preparation guarantees the high accuracy of the mentioned method, which indicates this method is a proper method to measure the thickness of four coatings of coated particles. (author)
Investigation on coupling error characteristics in angular rate matching based ship deformation measurement approach

Science.gov (United States)

Yang, Shuai; Wu, Wei; Wang, Xingshu; Xu, Zhiguang

2018-01-01

The coupling error in the measurement of ship hull deformation can significantly influence the attitude accuracy of the shipborne weapons and equipments. It is therefore important to study the characteristics of the coupling error. In this paper, an comprehensive investigation on the coupling error is reported, which has a potential of deducting the coupling error in the future. Firstly, the causes and characteristics of the coupling error are analyzed theoretically based on the basic theory of measuring ship deformation. Then, simulations are conducted for verifying the correctness of the theoretical analysis. Simulation results show that the cross-correlation between dynamic flexure and ship angular motion leads to the coupling error in measuring ship deformation, and coupling error increases with the correlation value between them. All the simulation results coincide with the theoretical analysis.
Error Ellipsoid Analysis for the Diameter Measurement of Cylindroid Components Using a Laser Radar Measurement System

Directory of Open Access Journals (Sweden)

Zhengchun Du

2016-05-01

Full Text Available The use of three-dimensional (3D data in the industrial measurement field is becoming increasingly popular because of the rapid development of laser scanning techniques based on the time-of-flight principle. However, the accuracy and uncertainty of these types of measurement methods are seldom investigated. In this study, a mathematical uncertainty evaluation model for the diameter measurement of standard cylindroid components has been proposed and applied to a 3D laser radar measurement system (LRMS. First, a single-point error ellipsoid analysis for the LRMS was established. An error ellipsoid model and algorithm for diameter measurement of cylindroid components was then proposed based on the single-point error ellipsoid. Finally, four experiments were conducted using the LRMS to measure the diameter of a standard cylinder in the laboratory. The experimental results of the uncertainty evaluation consistently matched well with the predictions. The proposed uncertainty evaluation model for cylindrical diameters can provide a reliable method for actual measurements and support further accuracy improvement of the LRMS.
Unadjusted Bivariate Two-Group Comparisons: When Simpler is Better.

Science.gov (United States)

Vetter, Thomas R; Mascha, Edward J

2018-01-01

Hypothesis testing involves posing both a null hypothesis and an alternative hypothesis. This basic statistical tutorial discusses the appropriate use, including their so-called assumptions, of the common unadjusted bivariate tests for hypothesis testing and thus comparing study sample data for a difference or association. The appropriate choice of a statistical test is predicated on the type of data being analyzed and compared. The unpaired or independent samples t test is used to test the null hypothesis that the 2 population means are equal, thereby accepting the alternative hypothesis that the 2 population means are not equal. The unpaired t test is intended for comparing dependent continuous (interval or ratio) data from 2 study groups. A common mistake is to apply several unpaired t tests when comparing data from 3 or more study groups. In this situation, an analysis of variance with post hoc (posttest) intragroup comparisons should instead be applied. Another common mistake is to apply a series of unpaired t tests when comparing sequentially collected data from 2 study groups. In this situation, a repeated-measures analysis of variance, with tests for group-by-time interaction, and post hoc comparisons, as appropriate, should instead be applied in analyzing data from sequential collection points. The paired t test is used to assess the difference in the means of 2 study groups when the sample observations have been obtained in pairs, often before and after an intervention in each study subject. The Pearson chi-square test is widely used to test the null hypothesis that 2 unpaired categorical variables, each with 2 or more nominal levels (values), are independent of each other. When the null hypothesis is rejected, 1 concludes that there is a probable association between the 2 unpaired categorical variables. When comparing 2 groups on an ordinal or nonnormally distributed continuous outcome variable, the 2-sample t test is usually not appropriate. The
Dissociable genetic contributions to error processing: a multimodal neuroimaging study.

Directory of Open Access Journals (Sweden)

Yigal Agam

Full Text Available Neuroimaging studies reliably identify two markers of error commission: the error-related negativity (ERN, an event-related potential, and functional MRI activation of the dorsal anterior cingulate cortex (dACC. While theorized to reflect the same neural process, recent evidence suggests that the ERN arises from the posterior cingulate cortex not the dACC. Here, we tested the hypothesis that these two error markers also have different genetic mediation.We measured both error markers in a sample of 92 comprised of healthy individuals and those with diagnoses of schizophrenia, obsessive-compulsive disorder or autism spectrum disorder. Participants performed the same task during functional MRI and simultaneously acquired magnetoencephalography and electroencephalography. We examined the mediation of the error markers by two single nucleotide polymorphisms: dopamine D4 receptor (DRD4 C-521T (rs1800955, which has been associated with the ERN and methylenetetrahydrofolate reductase (MTHFR C677T (rs1801133, which has been associated with error-related dACC activation. We then compared the effects of each polymorphism on the two error markers modeled as a bivariate response.We replicated our previous report of a posterior cingulate source of the ERN in healthy participants in the schizophrenia and obsessive-compulsive disorder groups. The effect of genotype on error markers did not differ significantly by diagnostic group. DRD4 C-521T allele load had a significant linear effect on ERN amplitude, but not on dACC activation, and this difference was significant. MTHFR C677T allele load had a significant linear effect on dACC activation but not ERN amplitude, but the difference in effects on the two error markers was not significant.DRD4 C-521T, but not MTHFR C677T, had a significant differential effect on two canonical error markers. Together with the anatomical dissociation between the ERN and error-related dACC activation, these findings suggest that
About some properties of bivariate splines with shape parameters

Science.gov (United States)

Caliò, F.; Marchetti, E.

2017-07-01

The paper presents and proves geometrical properties of a particular bivariate function spline, built and algorithmically implemented in previous papers. The properties typical of this family of splines impact the field of computer graphics in particular that of the reverse engineering.
Uncertainty quantification for radiation measurements: Bottom-up error variance estimation using calibration information

International Nuclear Information System (INIS)

Burr, T.; Croft, S.; Krieger, T.; Martin, K.; Norman, C.; Walsh, S.

2016-01-01

One example of top-down uncertainty quantification (UQ) involves comparing two or more measurements on each of multiple items. One example of bottom-up UQ expresses a measurement result as a function of one or more input variables that have associated errors, such as a measured count rate, which individually (or collectively) can be evaluated for impact on the uncertainty in the resulting measured value. In practice, it is often found that top-down UQ exhibits larger error variances than bottom-up UQ, because some error sources are present in the fielded assay methods used in top-down UQ that are not present (or not recognized) in the assay studies used in bottom-up UQ. One would like better consistency between the two approaches in order to claim understanding of the measurement process. The purpose of this paper is to refine bottom-up uncertainty estimation by using calibration information so that if there are no unknown error sources, the refined bottom-up uncertainty estimate will agree with the top-down uncertainty estimate to within a specified tolerance. Then, in practice, if the top-down uncertainty estimate is larger than the refined bottom-up uncertainty estimate by more than the specified tolerance, there must be omitted sources of error beyond those predicted from calibration uncertainty. The paper develops a refined bottom-up uncertainty approach for four cases of simple linear calibration: (1) inverse regression with negligible error in predictors, (2) inverse regression with non-negligible error in predictors, (3) classical regression followed by inversion with negligible error in predictors, and (4) classical regression followed by inversion with non-negligible errors in predictors. Our illustrations are of general interest, but are drawn from our experience with nuclear material assay by non-destructive assay. The main example we use is gamma spectroscopy that applies the enrichment meter principle. Previous papers that ignore error in predictors
Validation of the measurement model concept for error structure identification

International Nuclear Information System (INIS)

Shukla, Pavan K.; Orazem, Mark E.; Crisalle, Oscar D.

2004-01-01

The development of different forms of measurement models for impedance has allowed examination of key assumptions on which the use of such models to assess error structure are based. The stochastic error structures obtained using the transfer-function and Voigt measurement models were identical, even when non-stationary phenomena caused some of the data to be inconsistent with the Kramers-Kronig relations. The suitability of the measurement model for assessment of consistency with the Kramers-Kronig relations, however, was found to be more sensitive to the confidence interval for the parameter estimates than to the number of parameters in the model. A tighter confidence interval was obtained for Voigt measurement model, which made the Voigt measurement model a more sensitive tool for identification of inconsistencies with the Kramers-Kronig relations
Errors in causal inference: an organizational schema for systematic error and random error.

Science.gov (United States)

Suzuki, Etsuji; Tsuda, Toshihide; Mitsuhashi, Toshiharu; Mansournia, Mohammad Ali; Yamamoto, Eiji

2016-11-01

To provide an organizational schema for systematic error and random error in estimating causal measures, aimed at clarifying the concept of errors from the perspective of causal inference. We propose to divide systematic error into structural error and analytic error. With regard to random error, our schema shows its four major sources: nondeterministic counterfactuals, sampling variability, a mechanism that generates exposure events and measurement variability. Structural error is defined from the perspective of counterfactual reasoning and divided into nonexchangeability bias (which comprises confounding bias and selection bias) and measurement bias. Directed acyclic graphs are useful to illustrate this kind of error. Nonexchangeability bias implies a lack of "exchangeability" between the selected exposed and unexposed groups. A lack of exchangeability is not a primary concern of measurement bias, justifying its separation from confounding bias and selection bias. Many forms of analytic errors result from the small-sample properties of the estimator used and vanish asymptotically. Analytic error also results from wrong (misspecified) statistical models and inappropriate statistical methods. Our organizational schema is helpful for understanding the relationship between systematic error and random error from a previously less investigated aspect, enabling us to better understand the relationship between accuracy, validity, and precision. Copyright © 2016 Elsevier Inc. All rights reserved.
Compensation for positioning error of industrial robot for flexible vision measuring system

Science.gov (United States)

Guo, Lei; Liang, Yajun; Song, Jincheng; Sun, Zengyu; Zhu, Jigui

2013-01-01

Positioning error of robot is a main factor of accuracy of flexible coordinate measuring system which consists of universal industrial robot and visual sensor. Present compensation methods for positioning error based on kinematic model of robot have a significant limitation that it isn't effective in the whole measuring space. A new compensation method for positioning error of robot based on vision measuring technique is presented. One approach is setting global control points in measured field and attaching an orientation camera to vision sensor. Then global control points are measured by orientation camera to calculate the transformation relation from the current position of sensor system to global coordinate system and positioning error of robot is compensated. Another approach is setting control points on vision sensor and two large field cameras behind the sensor. Then the three dimensional coordinates of control points are measured and the pose and position of sensor is calculated real-timely. Experiment result shows the RMS of spatial positioning is 3.422mm by single camera and 0.031mm by dual cameras. Conclusion is arithmetic of single camera method needs to be improved for higher accuracy and accuracy of dual cameras method is applicable.
Using Generalizability Theory to Disattenuate Correlation Coefficients for Multiple Sources of Measurement Error.

Science.gov (United States)

Vispoel, Walter P; Morris, Carrie A; Kilinc, Murat

2018-05-02

Over the years, research in the social sciences has been dominated by reporting of reliability coefficients that fail to account for key sources of measurement error. Use of these coefficients, in turn, to correct for measurement error can hinder scientific progress by misrepresenting true relationships among the underlying constructs being investigated. In the research reported here, we addressed these issues using generalizability theory (G-theory) in both traditional and new ways to account for the three key sources of measurement error (random-response, specific-factor, and transient) that affect scores from objectively scored measures. Results from 20 widely used measures of personality, self-concept, and socially desirable responding showed that conventional indices consistently misrepresented reliability and relationships among psychological constructs by failing to account for key sources of measurement error and correlated transient errors within occasions. The results further revealed that G-theory served as an effective framework for remedying these problems. We discuss possible extensions in future research and provide code from the computer package R in an online supplement to enable readers to apply the procedures we demonstrate to their own research.
Measurement Model Specification Error in LISREL Structural Equation Models.

Science.gov (United States)

Baldwin, Beatrice; Lomax, Richard

This LISREL study examines the robustness of the maximum likelihood estimates under varying degrees of measurement model misspecification. A true model containing five latent variables (two endogenous and three exogenous) and two indicator variables per latent variable was used. Measurement model misspecification considered included errors of…
Optimizing an objective function under a bivariate probability model

NARCIS (Netherlands)

X. Brusset; N.M. Temme (Nico)

2007-01-01

htmlabstractThe motivation of this paper is to obtain an analytical closed form of a quadratic objective function arising from a stochastic decision process with bivariate exponential probability distribution functions that may be dependent. This method is applicable when results need to be
About Error in Measuring Oxygen Concentration by Solid-Electrolyte Sensors

Directory of Open Access Journals (Sweden)

V. I. Nazarov

2008-01-01

Full Text Available The paper evaluates additional errors while measuring oxygen concentration in a gas mixture by a solid-electrolyte cell. Experimental dependences of additional errors caused by changes in temperature in a sensor zone, discharge of gas mixture supplied to a sensor zone, partial pressure in the gas mixture and fluctuations in oxygen concentrations in the air.

#2 - An Empirical Assessment of Exposure Measurement Error ...

Science.gov (United States)

Background• Differing degrees of exposure error acrosspollutants• Previous focus on quantifying and accounting forexposure error in single-pollutant models• Examine exposure errors for multiple pollutantsand provide insights on the potential for bias andattenuation of effect estimates in single and bipollutantepidemiological models The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Validation and Error Characterization for the Global Precipitation Measurement

Science.gov (United States)

Bidwell, Steven W.; Adams, W. J.; Everett, D. F.; Smith, E. A.; Yuter, S. E.

2003-01-01

The Global Precipitation Measurement (GPM) is an international effort to increase scientific knowledge on the global water cycle with specific goals of improving the understanding and the predictions of climate, weather, and hydrology. These goals will be achieved through several satellites specifically dedicated to GPM along with the integration of numerous meteorological satellite data streams from international and domestic partners. The GPM effort is led by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan. In addition to the spaceborne assets, international and domestic partners will provide ground-based resources for validating the satellite observations and retrievals. This paper describes the validation effort of Global Precipitation Measurement to provide quantitative estimates on the errors of the GPM satellite retrievals. The GPM validation approach will build upon the research experience of the Tropical Rainfall Measuring Mission (TRMM) retrieval comparisons and its validation program. The GPM ground validation program will employ instrumentation, physical infrastructure, and research capabilities at Supersites located in important meteorological regimes of the globe. NASA will provide two Supersites, one in a tropical oceanic and the other in a mid-latitude continental regime. GPM international partners will provide Supersites for other important regimes. Those objectives or regimes not addressed by Supersites will be covered through focused field experiments. This paper describes the specific errors that GPM ground validation will address, quantify, and relate to the GPM satellite physical retrievals. GPM will attempt to identify the source of errors within retrievals including those of instrument calibration, retrieval physical assumptions, and algorithm applicability. With the identification of error sources, improvements will be made to the respective calibration
Spectrum-based estimators of the bivariate Hurst exponent

Czech Academy of Sciences Publication Activity Database

Krištoufek, Ladislav

2014-01-01

Roč. 90, č. 6 (2014), art. 062802 ISSN 1539-3755 R&D Projects: GA ČR(CZ) GP14-11402P Institutional support: RVO:67985556 Keywords : bivariate Hurst exponent * power- law cross-correlations * estimation Subject RIV: AH - Economics Impact factor: 2.288, year: 2014 http://library.utia.cas.cz/separaty/2014/E/kristoufek-0436818.pdf
Conditional Standard Errors of Measurement for Scale Scores.

Science.gov (United States)

Kolen, Michael J.; And Others

1992-01-01

A procedure is described for estimating the reliability and conditional standard errors of measurement of scale scores incorporating the discrete transformation of raw scores to scale scores. The method is illustrated using a strong true score model, and practical applications are described. (SLD)
System tuning and measurement error detection testing

International Nuclear Information System (INIS)

Krejci, Petr; Machek, Jindrich

2008-09-01

The project includes the use of the PEANO (Process Evaluation and Analysis by Neural Operators) system to verify the monitoring of the status of dependent measurements with a view to early measurement fault detection and estimation of selected signal levels. At the present stage, the system's capabilities of detecting measurement errors was assessed and the quality of the estimates was evaluated for various system configurations and the formation of empiric models, and rules were sought for system training at chosen process data recording parameters and operating modes. The aim was to find a suitable system configuration and to document the quality of the tuned system on artificial failures
A Model of Self-Monitoring Blood Glucose Measurement Error.

Science.gov (United States)

Vettoretti, Martina; Facchinetti, Andrea; Sparacino, Giovanni; Cobelli, Claudio

2017-07-01

A reliable model of the probability density function (PDF) of self-monitoring of blood glucose (SMBG) measurement error would be important for several applications in diabetes, like testing in silico insulin therapies. In the literature, the PDF of SMBG error is usually described by a Gaussian function, whose symmetry and simplicity are unable to properly describe the variability of experimental data. Here, we propose a new methodology to derive more realistic models of SMBG error PDF. The blood glucose range is divided into zones where error (absolute or relative) presents a constant standard deviation (SD). In each zone, a suitable PDF model is fitted by maximum-likelihood to experimental data. Model validation is performed by goodness-of-fit tests. The method is tested on two databases collected by the One Touch Ultra 2 (OTU2; Lifescan Inc, Milpitas, CA) and the Bayer Contour Next USB (BCN; Bayer HealthCare LLC, Diabetes Care, Whippany, NJ). In both cases, skew-normal and exponential models are used to describe the distribution of errors and outliers, respectively. Two zones were identified: zone 1 with constant SD absolute error; zone 2 with constant SD relative error. Goodness-of-fit tests confirmed that identified PDF models are valid and superior to Gaussian models used so far in the literature. The proposed methodology allows to derive realistic models of SMBG error PDF. These models can be used in several investigations of present interest in the scientific community, for example, to perform in silico clinical trials to compare SMBG-based with nonadjunctive CGM-based insulin treatments.
Covariate measurement error correction methods in mediation analysis with failure time data.

Science.gov (United States)

Zhao, Shanshan; Prentice, Ross L

2014-12-01

Mediation analysis is important for understanding the mechanisms whereby one variable causes changes in another. Measurement error could obscure the ability of the potential mediator to explain such changes. This article focuses on developing correction methods for measurement error in the mediator with failure time outcomes. We consider a broad definition of measurement error, including technical error, and error associated with temporal variation. The underlying model with the "true" mediator is assumed to be of the Cox proportional hazards model form. The induced hazard ratio for the observed mediator no longer has a simple form independent of the baseline hazard function, due to the conditioning event. We propose a mean-variance regression calibration approach and a follow-up time regression calibration approach, to approximate the partial likelihood for the induced hazard function. Both methods demonstrate value in assessing mediation effects in simulation studies. These methods are generalized to multiple biomarkers and to both case-cohort and nested case-control sampling designs. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of several serum sex hormone measures on the relationship between postmenopausal hormone therapy and breast cancer risk. © 2014, The International Biometric Society.
Consequences of exposure measurement error for confounder identification in environmental epidemiology

DEFF Research Database (Denmark)

Budtz-Jørgensen, Esben; Keiding, Niels; Grandjean, Philippe

2003-01-01

Non-differential measurement error in the exposure variable is known to attenuate the dose-response relationship. The amount of attenuation introduced in a given situation is not only a function of the precision of the exposure measurement but also depends on the conditional variance of the true...... exposure given the other independent variables. In addition, confounder effects may also be affected by the exposure measurement error. These difficulties in statistical model development are illustrated by examples from a epidemiological study performed in the Faroe Islands to investigate the adverse...
Reducing systematic errors in measurements made by a SQUID magnetometer

International Nuclear Information System (INIS)

Kiss, L.F.; Kaptás, D.; Balogh, J.

2014-01-01

A simple method is described which reduces those systematic errors of a superconducting quantum interference device (SQUID) magnetometer that arise from possible radial displacements of the sample in the second-order gradiometer superconducting pickup coil. By rotating the sample rod (and hence the sample) around its axis into a position where the best fit is obtained to the output voltage of the SQUID as the sample is moved through the pickup coil, the accuracy of measuring magnetic moments can be increased significantly. In the cases of an examined Co 1.9 Fe 1.1 Si Heusler alloy, pure iron and nickel samples, the accuracy could be increased over the value given in the specification of the device. The suggested method is only meaningful if the measurement uncertainty is dominated by systematic errors – radial displacement in particular – and not by instrumental or environmental noise. - Highlights: • A simple method is described which reduces systematic errors of a SQUID. • The errors arise from a radial displacement of the sample in the gradiometer coil. • The procedure is to rotate the sample rod (with the sample) around its axis. • The best fit to the SQUID voltage has to be attained moving the sample through the coil. • The accuracy of measuring magnetic moment can be increased significantly
Characterization of measurement errors using structure-from-motion and photogrammetry to measure marine habitat structural complexity.

Science.gov (United States)

Bryson, Mitch; Ferrari, Renata; Figueira, Will; Pizarro, Oscar; Madin, Josh; Williams, Stefan; Byrne, Maria

2017-08-01

Habitat structural complexity is one of the most important factors in determining the makeup of biological communities. Recent advances in structure-from-motion and photogrammetry have resulted in a proliferation of 3D digital representations of habitats from which structural complexity can be measured. Little attention has been paid to quantifying the measurement errors associated with these techniques, including the variability of results under different surveying and environmental conditions. Such errors have the potential to confound studies that compare habitat complexity over space and time. This study evaluated the accuracy, precision, and bias in measurements of marine habitat structural complexity derived from structure-from-motion and photogrammetric measurements using repeated surveys of artificial reefs (with known structure) as well as natural coral reefs. We quantified measurement errors as a function of survey image coverage, actual surface rugosity, and the morphological community composition of the habitat-forming organisms (reef corals). Our results indicated that measurements could be biased by up to 7.5% of the total observed ranges of structural complexity based on the environmental conditions present during any particular survey. Positive relationships were found between measurement errors and actual complexity, and the strength of these relationships was increased when coral morphology and abundance were also used as predictors. The numerous advantages of structure-from-motion and photogrammetry techniques for quantifying and investigating marine habitats will mean that they are likely to replace traditional measurement techniques (e.g., chain-and-tape). To this end, our results have important implications for data collection and the interpretation of measurements when examining changes in habitat complexity using structure-from-motion and photogrammetry.
Modeling and estimation of measurement errors

International Nuclear Information System (INIS)

Neuilly, M.

1998-01-01

Any person in charge of taking measures is aware of the inaccuracy of the results however cautiously he may handle. Sensibility, accuracy, reproducibility define the significance of a result. The use of statistical methods is one of the important tools to improve the quality of measurement. The accuracy due to these methods revealed the little difference in the isotopic composition of uranium ore which led to the discovery of Oklo fossil reactor. This book is dedicated to scientists and engineers interested in measurement whatever their investigation interests are. Experimental results are presented as random variables and their laws of probability are approximated by normal law, Poison law or Pearson distribution. The impact of 1 or more parameters on the total error can be evaluated by drawing factorial plans and by using variance analysis methods. This method is also used in intercomparison procedures between laboratories and to detect any abnormal shift in a series of measurement. (A.C.)
QUALITATIVE DATA AND ERROR MEASUREMENT IN INPUT-OUTPUT-ANALYSIS

NARCIS (Netherlands)

NIJKAMP, P; OOSTERHAVEN, J; OUWERSLOOT, H; RIETVELD, P

1992-01-01

This paper is a contribution to the rapidly emerging field of qualitative data analysis in economics. Ordinal data techniques and error measurement in input-output analysis are here combined in order to test the reliability of a low level of measurement and precision of data by means of a stochastic
Propagation of Radiosonde Pressure Sensor Errors to Ozonesonde Measurements

Science.gov (United States)

Stauffer, R. M.; Morris, G.A.; Thompson, A. M.; Joseph, E.; Coetzee, G. J. R.; Nalli, N. R.

2014-01-01

Several previous studies highlight pressure (or equivalently, pressure altitude) discrepancies between the radiosonde pressure sensor and that derived from a GPS flown with the radiosonde. The offsets vary during the ascent both in absolute and percent pressure differences. To investigate this problem further, a total of 731 radiosonde-ozonesonde launches from the Southern Hemisphere subtropics to Northern mid-latitudes are considered, with launches between 2005 - 2013 from both longer-term and campaign-based intensive stations. Five series of radiosondes from two manufacturers (International Met Systems: iMet, iMet-P, iMet-S, and Vaisala: RS80-15N and RS92-SGP) are analyzed to determine the magnitude of the pressure offset. Additionally, electrochemical concentration cell (ECC) ozonesondes from three manufacturers (Science Pump Corporation; SPC and ENSCI-Droplet Measurement Technologies; DMT) are analyzed to quantify the effects these offsets have on the calculation of ECC ozone (O3) mixing ratio profiles (O3MR) from the ozonesonde-measured partial pressure. Approximately half of all offsets are 0.6 hPa in the free troposphere, with nearly a third 1.0 hPa at 26 km, where the 1.0 hPa error represents 5 persent of the total atmospheric pressure. Pressure offsets have negligible effects on O3MR below 20 km (96 percent of launches lie within 5 percent O3MR error at 20 km). Ozone mixing ratio errors above 10 hPa (30 km), can approach greater than 10 percent ( 25 percent of launches that reach 30 km exceed this threshold). These errors cause disagreement between the integrated ozonesonde-only column O3 from the GPS and radiosonde pressure profile by an average of +6.5 DU. Comparisons of total column O3 between the GPS and radiosonde pressure profiles yield average differences of +1.1 DU when the O3 is integrated to burst with addition of the McPeters and Labow (2012) above-burst O3 column climatology. Total column differences are reduced to an average of -0.5 DU when
Analysis and improvement of gas turbine blade temperature measurement error

International Nuclear Information System (INIS)

Gao, Shan; Wang, Lixin; Feng, Chi; Daniel, Ketui

2015-01-01

Gas turbine blade components are easily damaged; they also operate in harsh high-temperature, high-pressure environments over extended durations. Therefore, ensuring that the blade temperature remains within the design limits is very important. In this study, measurement errors in turbine blade temperatures were analyzed, taking into account detector lens contamination, the reflection of environmental energy from the target surface, the effects of the combustion gas, and the emissivity of the blade surface. In this paper, each of the above sources of measurement error is discussed, and an iterative computing method for calculating blade temperature is proposed. (paper)
Analysis and improvement of gas turbine blade temperature measurement error

Science.gov (United States)

Gao, Shan; Wang, Lixin; Feng, Chi; Daniel, Ketui

2015-10-01

Gas turbine blade components are easily damaged; they also operate in harsh high-temperature, high-pressure environments over extended durations. Therefore, ensuring that the blade temperature remains within the design limits is very important. In this study, measurement errors in turbine blade temperatures were analyzed, taking into account detector lens contamination, the reflection of environmental energy from the target surface, the effects of the combustion gas, and the emissivity of the blade surface. In this paper, each of the above sources of measurement error is discussed, and an iterative computing method for calculating blade temperature is proposed.
Cost-Sensitive Feature Selection of Numeric Data with Measurement Errors

Directory of Open Access Journals (Sweden)

Hong Zhao

2013-01-01

Full Text Available Feature selection is an essential process in data mining applications since it reduces a model’s complexity. However, feature selection with various types of costs is still a new research topic. In this paper, we study the cost-sensitive feature selection problem of numeric data with measurement errors. The major contributions of this paper are fourfold. First, a new data model is built to address test costs and misclassification costs as well as error boundaries. It is distinguished from the existing models mainly on the error boundaries. Second, a covering-based rough set model with normal distribution measurement errors is constructed. With this model, coverings are constructed from data rather than assigned by users. Third, a new cost-sensitive feature selection problem is defined on this model. It is more realistic than the existing feature selection problems. Fourth, both backtracking and heuristic algorithms are proposed to deal with the new problem. Experimental results show the efficiency of the pruning techniques for the backtracking algorithm and the effectiveness of the heuristic algorithm. This study is a step toward realistic applications of the cost-sensitive learning.
Bivariate generalized Pareto distribution for extreme atmospheric particulate matter

Science.gov (United States)

Amin, Nor Azrita Mohd; Adam, Mohd Bakri; Ibrahim, Noor Akma; Aris, Ahmad Zaharin

2015-02-01

The high particulate matter (PM10) level is the prominent issue causing various impacts to human health and seriously affecting the economics. The asymptotic theory of extreme value is apply for analyzing the relation of extreme PM10 data from two nearby air quality monitoring stations. The series of daily maxima PM10 for Johor Bahru and Pasir Gudang stations are consider for year 2001 to 2010 databases. The 85% and 95% marginal quantile apply to determine the threshold values and hence construct the series of exceedances over the chosen threshold. The logistic, asymmetric logistic, negative logistic and asymmetric negative logistic models areconsidered as the dependence function to the joint distribution of a bivariate observation. Maximum likelihood estimation is employed for parameter estimations. The best fitted model is chosen based on the Akaike Information Criterion and the quantile plots. It is found that the asymmetric logistic model gives the best fitted model for bivariate extreme PM10 data and shows the weak dependence between two stations.
Bivariational calculations for radiation transfer in an inhomogeneous participating media

International Nuclear Information System (INIS)

El Wakil, S.A.; Machali, H.M.; Haggag, M.H.; Attia, M.T.

1986-07-01

Equations for radiation transfer are obtained for dispersive media with space dependent albedo. Bivariational bound principle is used to calculate the reflection and transmission coefficients for such media. Numerical results are given and compared. (author)
Measuring Articulatory Error Consistency in Children with Developmental Apraxia of Speech

Science.gov (United States)

Betz, Stacy K.; Stoel-Gammon, Carol

2005-01-01

Error inconsistency is often cited as a characteristic of children with speech disorders, particularly developmental apraxia of speech (DAS); however, few researchers operationally define error inconsistency and the definitions that do exist are not standardized across studies. This study proposes three formulas for measuring various aspects of…
An introduction to the measurement errors and data handling

International Nuclear Information System (INIS)

Rubio, J.A.

1979-01-01

Some usual methods to estimate and correlate measurement errors are presented. An introduction to the theory of parameter determination and goodness of the estimates is also presented. Some examples are discussed. (author)

Spectral density regression for bivariate extremes

KAUST Repository

Castro Camilo, Daniela

2016-05-11

We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods. © 2016 Springer-Verlag Berlin Heidelberg
Measurement error and timing of predictor values for multivariable risk prediction models are poorly reported.

Science.gov (United States)

Whittle, Rebecca; Peat, George; Belcher, John; Collins, Gary S; Riley, Richard D

2018-05-18

Measurement error in predictor variables may threaten the validity of clinical prediction models. We sought to evaluate the possible extent of the problem. A secondary objective was to examine whether predictors are measured at the intended moment of model use. A systematic search of Medline was used to identify a sample of articles reporting the development of a clinical prediction model published in 2015. After screening according to a predefined inclusion criteria, information on predictors, strategies to control for measurement error and intended moment of model use were extracted. Susceptibility to measurement error for each predictor was classified into low and high risk. Thirty-three studies were reviewed, including 151 different predictors in the final prediction models. Fifty-one (33.7%) predictors were categorised as high risk of error, however this was not accounted for in the model development. Only 8 (24.2%) studies explicitly stated the intended moment of model use and when the predictors were measured. Reporting of measurement error and intended moment of model use is poor in prediction model studies. There is a need to identify circumstances where ignoring measurement error in prediction models is consequential and whether accounting for the error will improve the predictions. Copyright © 2018. Published by Elsevier Inc.
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.
A measurement strategy and an error-compensation model for the on-machine laser measurement of large-scale free-form surfaces

International Nuclear Information System (INIS)

Li, Bin; Li, Feng; Liu, Hongqi; Cai, Hui; Mao, Xinyong; Peng, Fangyu

2014-01-01

This study presents a novel measurement strategy and an error-compensation model for the measurement of large-scale free-form surfaces in on-machine laser measurement systems. To improve the measurement accuracy, the effects of the scan depth, surface roughness, incident angle and azimuth angle on the measurement results were investigated experimentally, and a practical measurement strategy considering the position and orientation of the sensor is presented. Also, a semi-quantitative model based on geometrical optics is proposed to compensate for the measurement error associated with the incident angle. The normal vector of the measurement point is determined using a cross-curve method from the acquired surface data. Then, the azimuth angle and incident angle are calculated to inform the measurement strategy and error-compensation model, respectively. The measurement strategy and error-compensation model are verified through the measurement of a large propeller blade on a heavy machine tool in a factory environment. The results demonstrate that the strategy and the model are effective in increasing the measurement accuracy. (paper)
Bayesian modeling of measurement error in predictor variables

NARCIS (Netherlands)

Fox, Gerardus J.A.; Glas, Cornelis A.W.

2003-01-01

It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between
Quantitative shearography: error reduction by using more than three measurement channels

International Nuclear Information System (INIS)

Charrett, Tom O. H.; Francis, Daniel; Tatam, Ralph P.

2011-01-01

Shearography is a noncontact optical technique used to measure surface displacement derivatives. Full surface strain characterization can be achieved using shearography configurations employing at least three measurement channels. Each measurement channel is sensitive to a single displacement gradient component defined by its sensitivity vector. A matrix transformation is then required to convert the measured components to the orthogonal displacement gradients required for quantitative strain measurement. This transformation, conventionally performed using three measurement channels, amplifies any errors present in the measurement. This paper investigates the use of additional measurement channels using the results of a computer model and an experimental shearography system. Results are presented showing that the addition of a fourth channel can reduce the errors in the computed orthogonal components by up to 33% and that, by using 10 channels, reductions of around 45% should be possible.
Relating Tropical Cyclone Track Forecast Error Distributions with Measurements of Forecast Uncertainty

Science.gov (United States)

2016-03-01

CYCLONE TRACK FORECAST ERROR DISTRIBUTIONS WITH MEASUREMENTS OF FORECAST UNCERTAINTY by Nicholas M. Chisler March 2016 Thesis Advisor...March 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE RELATING TROPICAL CYCLONE TRACK FORECAST ERROR DISTRIBUTIONS...WITH MEASUREMENTS OF FORECAST UNCERTAINTY 5. FUNDING NUMBERS 6. AUTHOR(S) Nicholas M. Chisler 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES
Measurement error in CT assessment of appendix diameter

Energy Technology Data Exchange (ETDEWEB)

Trout, Andrew T.; Towbin, Alexander J. [Cincinnati Children' s Hospital Medical Center, Department of Radiology, MLC 5031, Cincinnati, OH (United States); Zhang, Bin [Cincinnati Children' s Hospital Medical Center, Department of Biostatistics and Epidemiology, Cincinnati, OH (United States)

2016-12-15

Appendiceal diameter continues to be cited as an important criterion for diagnosis of appendicitis by computed tomography (CT). To assess sources of error and variability in appendiceal diameter measurements by CT. In this institutional review board-approved review of imaging and medical records, we reviewed CTs performed in children <18 years of age between Jan. 1 and Dec. 31, 2010. Appendiceal diameter was measured in the axial and coronal planes by two reviewers (R1, R2). One year later, 10% of cases were remeasured. For patients who had multiple CTs, serial measurements were made to assess within patient variability. Measurement differences between planes, within and between reviewers, within patients and between CT and pathological measurements were assessed using correlation coefficients and paired t-tests. Six hundred thirty-one CTs performed in 519 patients (mean age: 10.9 ± 4.9 years, 50.8% female) were reviewed. Axial and coronal measurements were strongly correlated (r = 0.92-0.94, P < 0.0001) with coronal plane measurements significantly larger (P < 0.0001). Measurements were strongly correlated between reviewers (r = 0.89-0.9, P < 0.0001) but differed significantly in both planes (axial: +0.2 mm, P=0.003; coronal: +0.1 mm, P=0.007). Repeat measurements were significantly different for one reviewer only in the axial plane (0.3 mm difference, P<0.05). Within patients imaged multiple times, measured appendix diameters differed significantly in the axial plane for both reviewers (R1: 0.5 mm, P = 0.031; R2: 0.7 mm, P = 0.022). Multiple potential sources of measurement error raise concern about the use of rigid diameter cutoffs for the diagnosis of acute appendicitis by CT. (orig.)
Bivariate extreme value with application to PM10 concentration analysis

Science.gov (United States)

Amin, Nor Azrita Mohd; Adam, Mohd Bakri; Ibrahim, Noor Akma; Aris, Ahmad Zaharin

2015-05-01

This study is focus on a bivariate extreme of renormalized componentwise maxima with generalized extreme value distribution as a marginal function. The limiting joint distribution of several parametric models are presented. Maximum likelihood estimation is employed for parameter estimations and the best model is selected based on the Akaike Information Criterion. The weekly and monthly componentwise maxima series are extracted from the original observations of daily maxima PM10 data for two air quality monitoring stations located in Pasir Gudang and Johor Bahru. The 10 years data are considered for both stations from year 2001 to 2010. The asymmetric negative logistic model is found as the best fit bivariate extreme model for both weekly and monthly maxima componentwise series. However the dependence parameters show that the variables for weekly maxima series is more dependence to each other compared to the monthly maxima.
A methodology for translating positional error into measures of attribute error, and combining the two error sources

Science.gov (United States)

Yohay Carmel; Curtis Flather; Denis Dean

2006-01-01

This paper summarizes our efforts to investigate the nature, behavior, and implications of positional error and attribute error in spatiotemporal datasets. Estimating the combined influence of these errors on map analysis has been hindered by the fact that these two error types are traditionally expressed in different units (distance units, and categorical units,...
Adjustment of Measurements with Multiplicative Errors: Error Analysis, Estimates of the Variance of Unit Weight, and Effect on Volume Estimation from LiDAR-Type Digital Elevation Models

Directory of Open Access Journals (Sweden)

Yun Shi

2014-01-01

Full Text Available Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM.
Accounting for measurement error in human life history trade-offs using structural equation modeling.

Science.gov (United States)

Helle, Samuli

2018-03-01

Revealing causal effects from correlative data is very challenging and a contemporary problem in human life history research owing to the lack of experimental approach. Problems with causal inference arising from measurement error in independent variables, whether related either to inaccurate measurement technique or validity of measurements, seem not well-known in this field. The aim of this study is to show how structural equation modeling (SEM) with latent variables can be applied to account for measurement error in independent variables when the researcher has recorded several indicators of a hypothesized latent construct. As a simple example of this approach, measurement error in lifetime allocation of resources to reproduction in Finnish preindustrial women is modelled in the context of the survival cost of reproduction. In humans, lifetime energetic resources allocated in reproduction are almost impossible to quantify with precision and, thus, typically used measures of lifetime reproductive effort (e.g., lifetime reproductive success and parity) are likely to be plagued by measurement error. These results are contrasted with those obtained from a traditional regression approach where the single best proxy of lifetime reproductive effort available in the data is used for inference. As expected, the inability to account for measurement error in women's lifetime reproductive effort resulted in the underestimation of its underlying effect size on post-reproductive survival. This article emphasizes the advantages that the SEM framework can provide in handling measurement error via multiple-indicator latent variables in human life history studies. © 2017 Wiley Periodicals, Inc.
Measuring Error Identification and Recovery Skills in Surgical Residents.

Science.gov (United States)

Sternbach, Joel M; Wang, Kevin; El Khoury, Rym; Teitelbaum, Ezra N; Meyerson, Shari L

2017-02-01

Although error identification and recovery skills are essential for the safe practice of surgery, they have not traditionally been taught or evaluated in residency training. This study validates a method for assessing error identification and recovery skills in surgical residents using a thoracoscopic lobectomy simulator. We developed a 5-station, simulator-based examination containing the most commonly encountered cognitive and technical errors occurring during division of the superior pulmonary vein for left upper lobectomy. Successful completion of each station requires identification and correction of these errors. Examinations were video recorded and scored in a blinded fashion using an examination-specific rating instrument evaluating task performance as well as error identification and recovery skills. Evidence of validity was collected in the categories of content, response process, internal structure, and relationship to other variables. Fifteen general surgical residents (9 interns and 6 third-year residents) completed the examination. Interrater reliability was high, with an intraclass correlation coefficient of 0.78 between 4 trained raters. Station scores ranged from 64% to 84% correct. All stations adequately discriminated between high- and low-performing residents, with discrimination ranging from 0.35 to 0.65. The overall examination score was significantly higher for intermediate residents than for interns (mean, 74 versus 64 of 90 possible; p = 0.03). The described simulator-based examination with embedded errors and its accompanying assessment tool can be used to measure error identification and recovery skills in surgical residents. This examination provides a valid method for comparing teaching strategies designed to improve error recognition and recovery to enhance patient safety. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
Bayesian Estimation and Selection of Nonlinear Vector Error Correction Models: The Case of the Sugar-Ethanol-Oil Nexus in Brazil

OpenAIRE

Kelvin Balcombe; George Rapsomanikis

2008-01-01

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest ...
Bivariate Rayleigh Distribution and its Properties

Directory of Open Access Journals (Sweden)

Ahmad Saeed Akhter

2007-01-01

Full Text Available Rayleigh (1880 observed that the sea waves follow no law because of the complexities of the sea, but it has been seen that the probability distributions of wave heights, wave length, wave induce pitch, wave and heave motions of the ships follow the Rayleigh distribution. At present, several different quantities are in use for describing the state of the sea; for example, the mean height of the waves, the root mean square height, the height of the “significant waves” (the mean height of the highest one-third of all the waves the maximum height over a given interval of the time, and so on. At present, the ship building industry knows less than any other construction industry about the service conditions under which it must operate. Only small efforts have been made to establish the stresses and motions and to incorporate the result of such studies in to design. This is due to the complexity of the problem caused by the extensive variability of the sea and the corresponding response of the ships. Although the problem appears feasible, yet it is possible to predict service conditions for ships in an orderly and relatively simple manner Rayleigh (1980 derived it from the amplitude of sound resulting from many independent sources. This distribution is also connected with one or two dimensions and is sometimes referred to as “random walk” frequency distribution. The Rayleigh distribution can be derived from the bivariate normal distribution when the variate are independent and random with equal variances. We try to construct bivariate Rayleigh distribution with marginal Rayleigh distribution function and discuss its fundamental properties.
Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

Science.gov (United States)

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2016-01-15

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.
Statistical methods for biodosimetry in the presence of both Berkson and classical measurement error

Science.gov (United States)

Miller, Austin

In radiation epidemiology, the true dose received by those exposed cannot be assessed directly. Physical dosimetry uses a deterministic function of the source term, distance and shielding to estimate dose. For the atomic bomb survivors, the physical dosimetry system is well established. The classical measurement errors plaguing the location and shielding inputs to the physical dosimetry system are well known. Adjusting for the associated biases requires an estimate for the classical measurement error variance, for which no data-driven estimate exists. In this case, an instrumental variable solution is the most viable option to overcome the classical measurement error indeterminacy. Biological indicators of dose may serve as instrumental variables. Specification of the biodosimeter dose-response model requires identification of the radiosensitivity variables, for which we develop statistical definitions and variables. More recently, researchers have recognized Berkson error in the dose estimates, introduced by averaging assumptions for many components in the physical dosimetry system. We show that Berkson error induces a bias in the instrumental variable estimate of the dose-response coefficient, and then address the estimation problem. This model is specified by developing an instrumental variable mixed measurement error likelihood function, which is then maximized using a Monte Carlo EM Algorithm. These methods produce dose estimates that incorporate information from both physical and biological indicators of dose, as well as the first instrumental variable based data-driven estimate for the classical measurement error variance.
The Influence of Training Phase on Error of Measurement in Jump Performance.

Science.gov (United States)

Taylor, Kristie-Lee; Hopkins, Will G; Chapman, Dale W; Cronin, John B

2016-03-01

The purpose of this study was to calculate the coefficients of variation in jump performance for individual participants in multiple trials over time to determine the extent to which there are real differences in the error of measurement between participants. The effect of training phase on measurement error was also investigated. Six subjects participated in a resistance-training intervention for 12 wk with mean power from a countermovement jump measured 6 d/wk. Using a mixed-model meta-analysis, differences between subjects, within-subject changes between training phases, and the mean error values during different phases of training were examined. Small, substantial factor differences of 1.11 were observed between subjects; however, the finding was unclear based on the width of the confidence limits. The mean error was clearly higher during overload training than baseline training, by a factor of ×/÷ 1.3 (confidence limits 1.0-1.6). The random factor representing the interaction between subjects and training phases revealed further substantial differences of ×/÷ 1.2 (1.1-1.3), indicating that on average, the error of measurement in some subjects changes more than in others when overload training is introduced. The results from this study provide the first indication that within-subject variability in performance is substantially different between training phases and, possibly, different between individuals. The implications of these findings for monitoring individuals and estimating sample size are discussed.
Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach.

Science.gov (United States)

Mohammadi, Tayeb; Kheiri, Soleiman; Sedehi, Morteza

2016-01-01

Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables "number of blood donation" and "number of blood deferral": as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models.

Assessment of salivary flow rate: biologic variation and measure error.

NARCIS (Netherlands)

Jongerius, P.H.; Limbeek, J. van; Rotteveel, J.J.

2004-01-01

OBJECTIVE: To investigate the applicability of the swab method in the measurement of salivary flow rate in multiple-handicap drooling children. To quantify the measurement error of the procedure and the biologic variation in the population. STUDY DESIGN: Cohort study. METHODS: In a repeated
Performance of bias-correction methods for exposure measurement error using repeated measurements with and without missing data.

Science.gov (United States)

Batistatou, Evridiki; McNamee, Roseanne

2012-12-10

It is known that measurement error leads to bias in assessing exposure effects, which can however, be corrected if independent replicates are available. For expensive replicates, two-stage (2S) studies that produce data 'missing by design', may be preferred over a single-stage (1S) study, because in the second stage, measurement of replicates is restricted to a sample of first-stage subjects. Motivated by an occupational study on the acute effect of carbon black exposure on respiratory morbidity, we compare the performance of several bias-correction methods for both designs in a simulation study: an instrumental variable method (EVROS IV) based on grouping strategies, which had been recommended especially when measurement error is large, the regression calibration and the simulation extrapolation methods. For the 2S design, either the problem of 'missing' data was ignored or the 'missing' data were imputed using multiple imputations. Both in 1S and 2S designs, in the case of small or moderate measurement error, regression calibration was shown to be the preferred approach in terms of root mean square error. For 2S designs, regression calibration as implemented by Stata software is not recommended in contrast to our implementation of this method; the 'problematic' implementation of regression calibration although substantially improved with use of multiple imputations. The EVROS IV method, under a good/fairly good grouping, outperforms the regression calibration approach in both design scenarios when exposure mismeasurement is severe. Both in 1S and 2S designs with moderate or large measurement error, simulation extrapolation severely failed to correct for bias. Copyright © 2012 John Wiley & Sons, Ltd.
Metrological Array of Cyber-Physical Systems. Part 7. Additive Error Correction for Measuring Instrument

Directory of Open Access Journals (Sweden)

Yuriy YATSUK

2015-06-01

Full Text Available Since during design it is impossible to use the uncertainty approach because the measurement results are still absent and as noted the error approach that can be successfully applied taking as true the nominal value of instruments transformation function. Limiting possibilities of additive error correction of measuring instruments for Cyber-Physical Systems are studied basing on general and special methods of measurement. Principles of measuring circuit maximal symmetry and its minimal reconfiguration are proposed for measurement or/and calibration. It is theoretically justified for the variety of correction methods that minimum additive error of measuring instruments exists under considering the real equivalent parameters of input electronic switches. Terms of self-calibrating and verification the measuring instruments in place are studied.
Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

Science.gov (United States)

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.
Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis

Directory of Open Access Journals (Sweden)

Jacques Duchêne

2008-05-01

Full Text Available The aim of this paper was to compare empirical mode decomposition (EMD and two new extended methods of Ã¢Â€Â‰EMD named complex empirical mode decomposition (complex-EMD and bivariate empirical mode decomposition (bivariate-EMD. All methods were used to analyze stabilogram center of pressure (COP time series. The two new methods are suitable to be applied to complex time series to extract complex intrinsic mode functions (IMFs before the Hilbert transform is subsequently applied on the IMFs. The trace of the analytic IMF in the complex plane has a circular form, with each IMF having its own rotation frequency. The area of the circle and the average rotation frequency of IMFs represent efficient indicators of the postural stability status of subjects. Experimental results show the effectiveness of these indicators to identify differences in standing posture between groups.
Design of roundness measurement model with multi-systematic error for cylindrical components with large radius.

Science.gov (United States)

Sun, Chuanzhi; Wang, Lei; Tan, Jiubin; Zhao, Bo; Tang, Yangchao

2016-02-01

The paper designs a roundness measurement model with multi-systematic error, which takes eccentricity, probe offset, radius of tip head of probe, and tilt error into account for roundness measurement of cylindrical components. The effects of the systematic errors and radius of components are analysed in the roundness measurement. The proposed method is built on the instrument with a high precision rotating spindle. The effectiveness of the proposed method is verified by experiment with the standard cylindrical component, which is measured on a roundness measuring machine. Compared to the traditional limacon measurement model, the accuracy of roundness measurement can be increased by about 2.2 μm using the proposed roundness measurement model for the object with a large radius of around 37 mm. The proposed method can improve the accuracy of roundness measurement and can be used for error separation, calibration, and comparison, especially for cylindrical components with a large radius.
Identification and estimation of nonlinear models using two samples with nonclassical measurement errors

KAUST Repository

Carroll, Raymond J.

2010-05-01

This paper considers identification and estimation of a general nonlinear Errors-in-Variables (EIV) model using two samples. Both samples consist of a dependent variable, some error-free covariates, and an error-prone covariate, for which the measurement error has unknown distribution and could be arbitrarily correlated with the latent true values; and neither sample contains an accurate measurement of the corresponding true variable. We assume that the regression model of interest - the conditional distribution of the dependent variable given the latent true covariate and the error-free covariates - is the same in both samples, but the distributions of the latent true covariates vary with observed error-free discrete covariates. We first show that the general latent nonlinear model is nonparametrically identified using the two samples when both could have nonclassical errors, without either instrumental variables or independence between the two samples. When the two samples are independent and the nonlinear regression model is parameterized, we propose sieve Quasi Maximum Likelihood Estimation (Q-MLE) for the parameter of interest, and establish its root-n consistency and asymptotic normality under possible misspecification, and its semiparametric efficiency under correct specification, with easily estimated standard errors. A Monte Carlo simulation and a data application are presented to show the power of the approach.
Semi-automated detection of aberrant chromosomes in bivariate flow karyotypes

NARCIS (Netherlands)

Boschman, G. A.; Manders, E. M.; Rens, W.; Slater, R.; Aten, J. A.

1992-01-01

A method is described that is designed to compare, in a standardized procedure, bivariate flow karyotypes of Hoechst 33258 (HO)/Chromomycin A3 (CA) stained human chromosomes from cells with aberrations with a reference flow karyotype of normal chromosomes. In addition to uniform normalization of
A measurement error model for physical activity level as measured by a questionnaire with application to the 1999-2006 NHANES questionnaire.

Science.gov (United States)

Tooze, Janet A; Troiano, Richard P; Carroll, Raymond J; Moshfegh, Alanna J; Freedman, Laurence S

2013-06-01

Systematic investigations into the structure of measurement error of physical activity questionnaires are lacking. We propose a measurement error model for a physical activity questionnaire that uses physical activity level (the ratio of total energy expenditure to basal energy expenditure) to relate questionnaire-based reports of physical activity level to true physical activity levels. The 1999-2006 National Health and Nutrition Examination Survey physical activity questionnaire was administered to 433 participants aged 40-69 years in the Observing Protein and Energy Nutrition (OPEN) Study (Maryland, 1999-2000). Valid estimates of participants' total energy expenditure were also available from doubly labeled water, and basal energy expenditure was estimated from an equation; the ratio of those measures estimated true physical activity level ("truth"). We present a measurement error model that accommodates the mixture of errors that arise from assuming a classical measurement error model for doubly labeled water and a Berkson error model for the equation used to estimate basal energy expenditure. The method was then applied to the OPEN Study. Correlations between the questionnaire-based physical activity level and truth were modest (r = 0.32-0.41); attenuation factors (0.43-0.73) indicate that the use of questionnaire-based physical activity level would lead to attenuated estimates of effect size. Results suggest that sample sizes for estimating relationships between physical activity level and disease should be inflated, and that regression calibration can be used to provide measurement error-adjusted estimates of relationships between physical activity and disease.
Confounding and exposure measurement error in air pollution epidemiology

NARCIS (Netherlands)

Sheppard, L.; Burnett, R.T.; Szpiro, A.A.; Kim, J.Y.; Jerrett, M.; Pope, C.; Brunekreef, B.|info:eu-repo/dai/nl/067548180

2012-01-01

Studies in air pollution epidemiology may suffer from some specific forms of confounding and exposure measurement error. This contribution discusses these, mostly in the framework of cohort studies. Evaluation of potential confounding is critical in studies of the health effects of air pollution.
Statistical method for quality control in presence of measurement errors

International Nuclear Information System (INIS)

Lauer-Peccoud, M.R.

1998-01-01

In a quality inspection of a set of items where the measurements of values of a quality characteristic of the item are contaminated by random errors, one can take wrong decisions which are damageable to the quality. So of is important to control the risks in such a way that a final quality level is insured. We consider that an item is defective or not if the value G of its quality characteristic is larger or smaller than a given level g. We assume that, due to the lack of precision of the measurement instrument, the measurement M of this characteristic is expressed by ∫ (G) + ξ where f is an increasing function such that the value ∫ (g 0 ) is known and ξ is a random error with mean zero and given variance. First we study the problem of the determination of a critical measure m such that a specified quality target is reached after the classification of a lot of items where each item is accepted or rejected depending on whether its measurement is smaller or greater than m. Then we analyse the problem of testing the global quality of a lot from the measurements for a example of items taken from the lot. For these two kinds of problems and for different quality targets, we propose solutions emphasizing on the case where the function ∫ is linear and the error ξ and the variable G are Gaussian. Simulation results allow to appreciate the efficiency of the different considered control procedures and their robustness with respect to deviations from the assumptions used in the theoretical derivations. (author)
M/T method based incremental encoder velocity measurement error analysis and self-adaptive error elimination algorithm

DEFF Research Database (Denmark)

Chen, Yangyang; Yang, Ming; Long, Jiang

2017-01-01

For motor control applications, the speed loop performance is largely depended on the accuracy of speed feedback signal. M/T method, due to its high theoretical accuracy, is the most widely used in incremental encoder adopted speed measurement. However, the inherent encoder optical grating error...
Computational fluid dynamics analysis and experimental study of a low measurement error temperature sensor used in climate observation.

Science.gov (United States)

Yang, Jie; Liu, Qingquan; Dai, Wei

2017-02-01

To improve the air temperature observation accuracy, a low measurement error temperature sensor is proposed. A computational fluid dynamics (CFD) method is implemented to obtain temperature errors under various environmental conditions. Then, a temperature error correction equation is obtained by fitting the CFD results using a genetic algorithm method. The low measurement error temperature sensor, a naturally ventilated radiation shield, a thermometer screen, and an aspirated temperature measurement platform are characterized in the same environment to conduct the intercomparison. The aspirated platform served as an air temperature reference. The mean temperature errors of the naturally ventilated radiation shield and the thermometer screen are 0.74 °C and 0.37 °C, respectively. In contrast, the mean temperature error of the low measurement error temperature sensor is 0.11 °C. The mean absolute error and the root mean square error between the corrected results and the measured results are 0.008 °C and 0.01 °C, respectively. The correction equation allows the temperature error of the low measurement error temperature sensor to be reduced by approximately 93.8%. The low measurement error temperature sensor proposed in this research may be helpful to provide a relatively accurate air temperature result.
The error sources appearing for the gamma radioactive source measurement in dynamic condition

International Nuclear Information System (INIS)

Sirbu, M.

1977-01-01

The error analysis for the measurement of the gamma radioactive sources, placed on the soil, with the help of the helicopter are presented. The analysis is based on a new formula that takes account of the attenuation gamma ray factor in the helicopter walls. They give a complete error formula and an error diagram. (author)
Model-based bootstrapping when correcting for measurement error with application to logistic regression.

Science.gov (United States)

Buonaccorsi, John P; Romeo, Giovanni; Thoresen, Magne

2018-03-01

When fitting regression models, measurement error in any of the predictors typically leads to biased coefficients and incorrect inferences. A plethora of methods have been proposed to correct for this. Obtaining standard errors and confidence intervals using the corrected estimators can be challenging and, in addition, there is concern about remaining bias in the corrected estimators. The bootstrap, which is one option to address these problems, has received limited attention in this context. It has usually been employed by simply resampling observations, which, while suitable in some situations, is not always formally justified. In addition, the simple bootstrap does not allow for estimating bias in non-linear models, including logistic regression. Model-based bootstrapping, which can potentially estimate bias in addition to being robust to the original sampling or whether the measurement error variance is constant or not, has received limited attention. However, it faces challenges that are not present in handling regression models with no measurement error. This article develops new methods for model-based bootstrapping when correcting for measurement error in logistic regression with replicate measures. The methodology is illustrated using two examples, and a series of simulations are carried out to assess and compare the simple and model-based bootstrap methods, as well as other standard methods. While not always perfect, the model-based approaches offer some distinct improvements over the other methods. © 2017, The International Biometric Society.
The effect of misclassification errors on case mix measurement.

Science.gov (United States)

Sutherland, Jason M; Botz, Chas K

2006-12-01

Case mix systems have been implemented for hospital reimbursement and performance measurement across Europe and North America. Case mix categorizes patients into discrete groups based on clinical information obtained from patient charts in an attempt to identify clinical or cost difference amongst these groups. The diagnosis related group (DRG) case mix system is the most common methodology, with variants adopted in many countries. External validation studies of coding quality have confirmed that widespread variability exists between originally recorded diagnoses and re-abstracted clinical information. DRG assignment errors in hospitals that share patient level cost data for the purpose of establishing cost weights affects cost weight accuracy. The purpose of this study is to estimate bias in cost weights due to measurement error of reported clinical information. DRG assignment error rates are simulated based on recent clinical re-abstraction study results. Our simulation study estimates that 47% of cost weights representing the least severe cases are over weight by 10%, while 32% of cost weights representing the most severe cases are under weight by 10%. Applying the simulated weights to a cross-section of hospitals, we find that teaching hospitals tend to be under weight. Since inaccurate cost weights challenges the ability of case mix systems to accurately reflect patient mix and may lead to potential distortions in hospital funding, bias in hospital case mix measurement highlights the role clinical data quality plays in hospital funding in countries that use DRG-type case mix systems. Quality of clinical information should be carefully considered from hospitals that contribute financial data for establishing cost weights.
Formulation of uncertainty relation of error and disturbance in quantum measurement by using quantum estimation theory

International Nuclear Information System (INIS)

Yu Watanabe; Masahito Ueda

2012-01-01

Full text: When we try to obtain information about a quantum system, we need to perform measurement on the system. The measurement process causes unavoidable state change. Heisenberg discussed a thought experiment of the position measurement of a particle by using a gamma-ray microscope, and found a trade-off relation between the error of the measured position and the disturbance in the momentum caused by the measurement process. The trade-off relation epitomizes the complementarity in quantum measurements: we cannot perform a measurement of an observable without causing disturbance in its canonically conjugate observable. However, at the time Heisenberg found the complementarity, quantum measurement theory was not established yet, and Kennard and Robertson's inequality erroneously interpreted as a mathematical formulation of the complementarity. Kennard and Robertson's inequality actually implies the indeterminacy of the quantum state: non-commuting observables cannot have definite values simultaneously. However, Kennard and Robertson's inequality reflects the inherent nature of a quantum state alone, and does not concern any trade-off relation between the error and disturbance in the measurement process. In this talk, we report a resolution to the complementarity in quantum measurements. First, we find that it is necessary to involve the estimation process from the outcome of the measurement for quantifying the error and disturbance in the quantum measurement. We clarify the implicitly involved estimation process in Heisenberg's gamma-ray microscope and other measurement schemes, and formulate the error and disturbance for an arbitrary quantum measurement by using quantum estimation theory. The error and disturbance are defined in terms of the Fisher information, which gives the upper bound of the accuracy of the estimation. Second, we obtain uncertainty relations between the measurement errors of two observables [1], and between the error and disturbance in the
Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

Science.gov (United States)

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…
Continuous glucose monitoring in newborn infants: how do errors in calibration measurements affect detected hypoglycemia?

Science.gov (United States)

Thomas, Felicity; Signal, Mathew; Harris, Deborah L; Weston, Philip J; Harding, Jane E; Shaw, Geoffrey M; Chase, J Geoffrey

2014-05-01

Neonatal hypoglycemia is common and can cause serious brain injury. Continuous glucose monitoring (CGM) could improve hypoglycemia detection, while reducing blood glucose (BG) measurements. Calibration algorithms use BG measurements to convert sensor signals into CGM data. Thus, inaccuracies in calibration BG measurements directly affect CGM values and any metrics calculated from them. The aim was to quantify the effect of timing delays and calibration BG measurement errors on hypoglycemia metrics in newborn infants. Data from 155 babies were used. Two timing and 3 BG meter error models (Abbott Optium Xceed, Roche Accu-Chek Inform II, Nova Statstrip) were created using empirical data. Monte-Carlo methods were employed, and each simulation was run 1000 times. Each set of patient data in each simulation had randomly selected timing and/or measurement error added to BG measurements before CGM data were calibrated. The number of hypoglycemic events, duration of hypoglycemia, and hypoglycemic index were then calculated using the CGM data and compared to baseline values. Timing error alone had little effect on hypoglycemia metrics, but measurement error caused substantial variation. Abbott results underreported the number of hypoglycemic events by up to 8 and Roche overreported by up to 4 where the original number reported was 2. Nova results were closest to baseline. Similar trends were observed in the other hypoglycemia metrics. Errors in blood glucose concentration measurements used for calibration of CGM devices can have a clinically important impact on detection of hypoglycemia. If CGM devices are going to be used for assessing hypoglycemia it is important to understand of the impact of these errors on CGM data. © 2014 Diabetes Technology Society.
Volumetric error modeling, identification and compensation based on screw theory for a large multi-axis propeller-measuring machine

Science.gov (United States)

Zhong, Xuemin; Liu, Hongqi; Mao, Xinyong; Li, Bin; He, Songping; Peng, Fangyu

2018-05-01

Large multi-axis propeller-measuring machines have two types of geometric error, position-independent geometric errors (PIGEs) and position-dependent geometric errors (PDGEs), which both have significant effects on the volumetric error of the measuring tool relative to the worktable. This paper focuses on modeling, identifying and compensating for the volumetric error of the measuring machine. A volumetric error model in the base coordinate system is established based on screw theory considering all the geometric errors. In order to fully identify all the geometric error parameters, a new method for systematic measurement and identification is proposed. All the PIGEs of adjacent axes and the six PDGEs of the linear axes are identified with a laser tracker using the proposed model. Finally, a volumetric error compensation strategy is presented and an inverse kinematic solution for compensation is proposed. The final measuring and compensation experiments have further verified the efficiency and effectiveness of the measuring and identification method, indicating that the method can be used in volumetric error compensation for large machine tools.

Measurement error of spiral CT volumetry: influence of low dose CT technique

International Nuclear Information System (INIS)

Chung, Myung Jin; Cho, Jae Min; Lee, Tae Gyu; Cho, Sung Bum; Kim, Seog Joon; Baik, Sang Hyun

2004-01-01

To examine the possible measurement errors of lung nodule volumetry at the various scan parameters by using a small nodule phantom. We obtained images of a nodule phantom using a spiral CT scanner. The nodule phantom was made of paraffin and urethane and its real volume was known. For the CT scanning experiments, we used three different values for both the pitch of the table feed, i.e. 1:1, 1:15 and 1:2, and the tube current, i.e. 40 mA, 80 mA and 120 mA. All of the images acquired through CT scanning were reconstructed three dimensionally and measured with volumetry software. We tested the correlation between the true volume and the measured volume for each set of parameters using linear regression analysis. For the pitches of table feed of 1:1, 1:1.5 and 1:2, the mean relative errors were 23.3%, 22.8% and 22.6%, respectively. There were perfect correlations among the three sets of measurements (Pearson's coefficient = 1.000, p< 0.001). For the tube currents of 40 mA, 80 mA and 120 mA, the mean relative errors were 22.6%, 22.6% and 22.9%, respectively. There were perfect correlations among them (Pearson's coefficient=1.000, p<0.001). In the measurement of the volume of the lung nodule using spiral CT, the measurement error was not increased in spite of the tube current being decreased or the pitch of table feed being increased
Correction for Measurement Error from Genotyping-by-Sequencing in Genomic Variance and Genomic Prediction Models

DEFF Research Database (Denmark)

Ashraf, Bilal; Janss, Luc; Jensen, Just

sample). The GBSeq data can be used directly in genomic models in the form of individual SNP allele-frequency estimates (e.g., reference reads/total reads per polymorphic site per individual), but is subject to measurement error due to the low sequencing depth per individual. Due to technical reasons....... In the current work we show how the correction for measurement error in GBSeq can also be applied in whole genome genomic variance and genomic prediction models. Bayesian whole-genome random regression models are proposed to allow implementation of large-scale SNP-based models with a per-SNP correction...... for measurement error. We show correct retrieval of genomic explained variance, and improved genomic prediction when accounting for the measurement error in GBSeq data...
Correction for dynamic bias error in transmission measurements of void fraction

International Nuclear Information System (INIS)

Andersson, P.; Sundén, E. Andersson; Svärd, S. Jacobsson; Sjöstrand, H.

2012-01-01

Dynamic bias errors occur in transmission measurements, such as X-ray, gamma, or neutron radiography or tomography. This is observed when the properties of the object are not stationary in time and its average properties are assessed. The nonlinear measurement response to changes in transmission within the time scale of the measurement implies a bias, which can be difficult to correct for. A typical example is the tomographic or radiographic mapping of void content in dynamic two-phase flow systems. In this work, the dynamic bias error is described and a method to make a first-order correction is derived. A prerequisite for this method is variance estimates of the system dynamics, which can be obtained using high-speed, time-resolved data acquisition. However, in the absence of such acquisition, a priori knowledge might be used to substitute the time resolved data. Using synthetic data, a void fraction measurement case study has been simulated to demonstrate the performance of the suggested method. The transmission length of the radiation in the object under study and the type of fluctuation of the void fraction have been varied. Significant decreases in the dynamic bias error were achieved to the expense of marginal decreases in precision.
Error of the slanted edge method for measuring the modulation transfer function of imaging systems.

Science.gov (United States)

Xie, Xufen; Fan, Hongda; Wang, Hongyuan; Wang, Zebin; Zou, Nianyu

2018-03-01

The slanted edge method is a basic approach for measuring the modulation transfer function (MTF) of imaging systems; however, its measurement accuracy is limited in practice. Theoretical analysis of the slanted edge MTF measurement method performed in this paper reveals that inappropriate edge angles and random noise reduce this accuracy. The error caused by edge angles is analyzed using sampling and reconstruction theory. Furthermore, an error model combining noise and edge angles is proposed. We verify the analyses and model with respect to (i) the edge angle, (ii) a statistical analysis of the measurement error, (iii) the full width at half-maximum of a point spread function, and (iv) the error model. The experimental results verify the theoretical findings. This research can be referential for applications of the slanted edge MTF measurement method.
Application of a repeat-measure biomarker measurement error model to 2 validation studies: examination of the effect of within-person variation in biomarker measurements.

Science.gov (United States)

Preis, Sarah Rosner; Spiegelman, Donna; Zhao, Barbara Bojuan; Moshfegh, Alanna; Baer, David J; Willett, Walter C

2011-03-15

Repeat-biomarker measurement error models accounting for systematic correlated within-person error can be used to estimate the correlation coefficient (ρ) and deattenuation factor (λ), used in measurement error correction. These models account for correlated errors in the food frequency questionnaire (FFQ) and the 24-hour diet recall and random within-person variation in the biomarkers. Failure to account for within-person variation in biomarkers can exaggerate correlated errors between FFQs and 24-hour diet recalls. For 2 validation studies, ρ and λ were calculated for total energy and protein density. In the Automated Multiple-Pass Method Validation Study (n=471), doubly labeled water (DLW) and urinary nitrogen (UN) were measured twice in 52 adults approximately 16 months apart (2002-2003), yielding intraclass correlation coefficients of 0.43 for energy (DLW) and 0.54 for protein density (UN/DLW). The deattenuated correlation coefficient for protein density was 0.51 for correlation between the FFQ and the 24-hour diet recall and 0.49 for correlation between the FFQ and the biomarker. Use of repeat-biomarker measurement error models resulted in a ρ of 0.42. These models were similarly applied to the Observing Protein and Energy Nutrition Study (1999-2000). In conclusion, within-person variation in biomarkers can be substantial, and to adequately assess the impact of correlated subject-specific error, this variation should be assessed in validation studies of FFQs. © The Author 2011. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
Unaccounted source of systematic errors in measurements of the Newtonian gravitational constant G

Science.gov (United States)

DeSalvo, Riccardo

2015-06-01

Many precision measurements of G have produced a spread of results incompatible with measurement errors. Clearly an unknown source of systematic errors is at work. It is proposed here that most of the discrepancies derive from subtle deviations from Hooke's law, caused by avalanches of entangled dislocations. The idea is supported by deviations from linearity reported by experimenters measuring G, similarly to what is observed, on a larger scale, in low-frequency spring oscillators. Some mitigating experimental apparatus modifications are suggested.
Low-frequency Periodic Error Identification and Compensation for Star Tracker Attitude Measurement

Institute of Scientific and Technical Information of China (English)

WANG Jiongqi; XIONG Kai; ZHOU Haiyin

2012-01-01

The low-frequency periodic error of star tracker is one of the most critical problems for high-accuracy satellite attitude determination.In this paper an approach is proposed to identify and compensate the low-frequency periodic error for star tracker in attitude measurement.The analytical expression between the estimated gyro drift and the low-frequency periodic error of star tracker is derived firstly.And then the low-frequency periodic error,which can be expressed by Fourier series,is identified by the frequency spectrum of the estimated gyro drift according to the solution of the first step.Furthermore,the compensated model of the low-frequency periodic error is established based on the identified parameters to improve the attitude determination accuracy.Finally,promising simulated experimental results demonstrate the validity and effectiveness of the proposed method.The periodic error for attitude determination is eliminated basically and the estimation precision is improved greatly.
Comparing Johnson’s SBB, Weibull and Logit-Logistic bivariate distributions for modeling tree diameters and heights using copulas

Energy Technology Data Exchange (ETDEWEB)

Cardil Forradellas, A.; Molina Terrén, D.M.; Oliveres, J.; Castellnou, M.

2016-07-01

Aim of study: In this study we compare the accuracy of three bivariate distributions: Johnson’s SBB, Weibull-2P and LL-2P functions for characterizing the joint distribution of tree diameters and heights. Area of study: North-West of Spain. Material and methods: Diameter and height measurements of 128 plots of pure and even-aged Tasmanian blue gum (Eucalyptus globulus Labill.) stands located in the North-west of Spain were considered in the present study. The SBB bivariate distribution was obtained from SB marginal distributions using a Normal Copula based on a four-parameter logistic transformation. The Plackett Copula was used to obtain the bivariate models from the Weibull and Logit-logistic univariate marginal distributions. The negative logarithm of the maximum likelihood function was used to compare the results and the Wilcoxon signed-rank test was used to compare the related samples of these logarithms calculated for each sample plot and each distribution. Main results: The best results were obtained by using the Plackett copula and the best marginal distribution was the Logit-logistic. Research highlights: The copulas used in this study have shown a good performance for modeling the joint distribution of tree diameters and heights. They could be easily extended for modelling multivariate distributions involving other tree variables, such as tree volume or biomass. (Author)
On the matched pairs sign test using bivariate ranked set sampling ...

African Journals Online (AJOL)

BVRSS) is introduced and investigated. We show that this test is asymptotically more efficient than its counterpart sign test based on a bivariate simple random sample (BVSRS). The asymptotic null distribution and the efficiency of the test are derived.
Accounting for the measurement error of spectroscopically inferred soil carbon data for improved precision of spatial predictions.

Science.gov (United States)

Somarathna, P D S N; Minasny, Budiman; Malone, Brendan P; Stockmann, Uta; McBratney, Alex B

2018-08-01

Spatial modelling of environmental data commonly only considers spatial variability as the single source of uncertainty. In reality however, the measurement errors should also be accounted for. In recent years, infrared spectroscopy has been shown to offer low cost, yet invaluable information needed for digital soil mapping at meaningful spatial scales for land management. However, spectrally inferred soil carbon data are known to be less accurate compared to laboratory analysed measurements. This study establishes a methodology to filter out the measurement error variability by incorporating the measurement error variance in the spatial covariance structure of the model. The study was carried out in the Lower Hunter Valley, New South Wales, Australia where a combination of laboratory measured, and vis-NIR and MIR inferred topsoil and subsoil soil carbon data are available. We investigated the applicability of residual maximum likelihood (REML) and Markov Chain Monte Carlo (MCMC) simulation methods to generate parameters of the Matérn covariance function directly from the data in the presence of measurement error. The results revealed that the measurement error can be effectively filtered-out through the proposed technique. When the measurement error was filtered from the data, the prediction variance almost halved, which ultimately yielded a greater certainty in spatial predictions of soil carbon. Further, the MCMC technique was successfully used to define the posterior distribution of measurement error. This is an important outcome, as the MCMC technique can be used to estimate the measurement error if it is not explicitly quantified. Although this study dealt with soil carbon data, this method is amenable for filtering the measurement error of any kind of continuous spatial environmental data. Copyright © 2018 Elsevier B.V. All rights reserved.
Estimation of heading gyrocompass error using a GPS 3DF system: Impact on ADCP measurements

Directory of Open Access Journals (Sweden)

Simón Ruiz

2002-12-01

Full Text Available Traditionally the horizontal orientation in a ship (heading has been obtained from a gyrocompass. This instrument is still used on research vessels but has an estimated error of about 2-3 degrees, inducing a systematic error in the cross-track velocity measured by an Acoustic Doppler Current Profiler (ADCP. The three-dimensional positioning system (GPS 3DF provides an independent heading measurement with accuracy better than 0.1 degree. The Spanish research vessel BIO Hespérides has been operating with this new system since 1996. For the first time on this vessel, the data from this new instrument are used to estimate gyrocompass error. The methodology we use follows the scheme developed by Griffiths (1994, which compares data from the gyrocompass and the GPS system in order to obtain an interpolated error function. In the present work we apply this methodology on mesoscale surveys performed during the observational phase of the OMEGA project, in the Alboran Sea. The heading-dependent gyrocompass error dominated. Errors in gyrocompass heading of 1.4-3.4 degrees have been found, which give a maximum error in measured cross-track ADCP velocity of 24 cm s-1.
Getting satisfied with "satisfaction of search": How to measure errors during multiple-target visual search.

Science.gov (United States)

Biggs, Adam T

2017-07-01

Visual search studies are common in cognitive psychology, and the results generally focus upon accuracy, response times, or both. Most research has focused upon search scenarios where no more than 1 target will be present for any single trial. However, if multiple targets can be present on a single trial, it introduces an additional source of error because the found target can interfere with subsequent search performance. These errors have been studied thoroughly in radiology for decades, although their emphasis in cognitive psychology studies has been more recent. One particular issue with multiple-target search is that these subsequent search errors (i.e., specific errors which occur following a found target) are measured differently by different studies. There is currently no guidance as to which measurement method is best or what impact different measurement methods could have upon various results and conclusions. The current investigation provides two efforts to address these issues. First, the existing literature is reviewed to clarify the appropriate scenarios where subsequent search errors could be observed. Second, several different measurement methods are used with several existing datasets to contrast and compare how each method would have affected the results and conclusions of those studies. The evidence is then used to provide appropriate guidelines for measuring multiple-target search errors in future studies.
Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

Science.gov (United States)

Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

2018-04-15

For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.
The role of errors in the measurements performed at the reprocessing plant head-end for material accountancy purposes

International Nuclear Information System (INIS)

Foggi, C.; Liebetrau, A.M.; Petraglia, E.

1999-01-01

One of the most common procedures used in determining the amount of nuclear material contained in solutions consists of first measuring the volume and the density of the solution, and then determining the concentrations of this material. This presentation will focus on errors generated at the process lime in the measurement of volume and density. These errors and their associated uncertainties can be grouped into distinct categories depending on their origin: those attributable to measuring instruments; those attributable to operational procedures; variability in measurement conditions; errors in the analysis and interpretation of results. Possible errors sources, their relative magnitudes, and an error propagation rationale are discussed, with emphasis placed on bases and errors of the last three types called systematic errors [ru
Simultaneous Treatment of Missing Data and Measurement Error in HIV Research Using Multiple Overimputation.

Science.gov (United States)

Schomaker, Michael; Hogger, Sara; Johnson, Leigh F; Hoffmann, Christopher J; Bärnighausen, Till; Heumann, Christian

2015-09-01

Both CD4 count and viral load in HIV-infected persons are measured with error. There is no clear guidance on how to deal with this measurement error in the presence of missing data. We used multiple overimputation, a method recently developed in the political sciences, to account for both measurement error and missing data in CD4 count and viral load measurements from four South African cohorts of a Southern African HIV cohort collaboration. Our knowledge about the measurement error of ln CD4 and log10 viral load is part of an imputation model that imputes both missing and mismeasured data. In an illustrative example, we estimate the association of CD4 count and viral load with the hazard of death among patients on highly active antiretroviral therapy by means of a Cox model. Simulation studies evaluate the extent to which multiple overimputation is able to reduce bias in survival analyses. Multiple overimputation emphasizes more strongly the influence of having high baseline CD4 counts compared to both a complete case analysis and multiple imputation (hazard ratio for >200 cells/mm vs. <25 cells/mm: 0.21 [95% confidence interval: 0.18, 0.24] vs. 0.38 [0.29, 0.48], and 0.29 [0.25, 0.34], respectively). Similar results are obtained when varying assumptions about measurement error, when using p-splines, and when evaluating time-updated CD4 count in a longitudinal analysis. The estimates of the association with viral load are slightly more attenuated when using multiple imputation instead of multiple overimputation. Our simulation studies suggest that multiple overimputation is able to reduce bias and mean squared error in survival analyses. Multiple overimputation, which can be used with existing software, offers a convenient approach to account for both missing and mismeasured data in HIV research.
Direct measurement of the poliovirus RNA polymerase error frequency in vitro

International Nuclear Information System (INIS)

Ward, C.D.; Stokes, M.A.M.; Flanegan, J.B.

1988-01-01

The fidelity of RNA replication by the poliovirus-RNA-dependent RNA polymerase was examined by copying homopolymeric RNA templates in vitro. The poliovirus RNA polymerase was extensively purified and used to copy poly(A), poly(C), or poly(I) templates with equimolar concentrations of noncomplementary and complementary ribonucleotides. The error frequency was expressed as the amount of a noncomplementary nucleotide incorporated divided by the total amount of complementary and noncomplementary nucleotide incorporated. The polymerase error frequencies were very high, depending on the specific reaction conditions. The activity of the polymerase on poly(U) and poly(G) was too low to measure error frequencies on these templates. A fivefold increase in the error frequency was observed when the reaction conditions were changed from 3.0 mM Mg 2+ (pH 7.0) to 7.0 mM Mg 2+ (pH 8.0). This increase in the error frequency correlates with an eightfold increase in the elongation rate that was observed under the same conditions in a previous study
Error Characterization of Altimetry Measurements at Climate Scales

Science.gov (United States)

Ablain, Michael; Larnicol, Gilles; Faugere, Yannice; Cazenave, Anny; Meyssignac, Benoit; Picot, Nicolas; Benveniste, Jerome

2013-09-01

Thanks to studies performed in the framework of the SALP project (supported by CNES) since the TOPEX era and more recently in the framework of the Sea- Level Climate Change Initiative project (supported by ESA), strong improvements have been provided on the estimation of the global and regional mean sea level over the whole altimeter period for all the altimetric missions. Thanks to these efforts, a better characterization of altimeter measurements errors at climate scales has been performed and presented in this paper. These errors have been compared to user requirements in order to know if scientific goals are reached by altimeter missions. The main issue of this paper is the importance to enhance the link between altimeter and climate communities to improve or refine user requirements, to better specify future altimeter system for climate applications but also to reprocess older missions beyond their original specifications.
To Error Problem Concerning Measuring Concentration of Carbon Oxide by Thermo-Chemical Sen

Directory of Open Access Journals (Sweden)

V. I. Nazarov

2007-01-01

Full Text Available The paper gives additional errors in respect of measuring concentration of carbon oxide by thermo-chemical sensors. A number of analytical expressions for calculation of error data and corrections for environmental factor deviations from admissible ones have been obtained in the paper
Analysis and compensation of synchronous measurement error for multi-channel laser interferometer

International Nuclear Information System (INIS)

Du, Shengwu; Hu, Jinchun; Zhu, Yu; Hu, Chuxiong

2017-01-01

Dual-frequency laser interferometer has been widely used in precision motion system as a displacement sensor, to achieve nanoscale positioning or synchronization accuracy. In a multi-channel laser interferometer synchronous measurement system, signal delays are different in the different channels, which will cause asynchronous measurement, and then lead to measurement error, synchronous measurement error (SME). Based on signal delay analysis of the measurement system, this paper presents a multi-channel SME framework for synchronous measurement, and establishes the model between SME and motion velocity. Further, a real-time compensation method for SME is proposed. This method has been verified in a self-developed laser interferometer signal processing board (SPB). The experiment result showed that, using this compensation method, at a motion velocity 0.89 m s −1 , the max SME between two measuring channels in the SPB is 1.1 nm. This method is more easily implemented and applied to engineering than the method of directly testing smaller signal delay. (paper)
Analysis and compensation of synchronous measurement error for multi-channel laser interferometer

Science.gov (United States)

Du, Shengwu; Hu, Jinchun; Zhu, Yu; Hu, Chuxiong

2017-05-01

Dual-frequency laser interferometer has been widely used in precision motion system as a displacement sensor, to achieve nanoscale positioning or synchronization accuracy. In a multi-channel laser interferometer synchronous measurement system, signal delays are different in the different channels, which will cause asynchronous measurement, and then lead to measurement error, synchronous measurement error (SME). Based on signal delay analysis of the measurement system, this paper presents a multi-channel SME framework for synchronous measurement, and establishes the model between SME and motion velocity. Further, a real-time compensation method for SME is proposed. This method has been verified in a self-developed laser interferometer signal processing board (SPB). The experiment result showed that, using this compensation method, at a motion velocity 0.89 m s-1, the max SME between two measuring channels in the SPB is 1.1 nm. This method is more easily implemented and applied to engineering than the method of directly testing smaller signal delay.

Testing independence of bivariate interval-censored data using modified Kendall's tau statistic.

Science.gov (United States)

Kim, Yuneung; Lim, Johan; Park, DoHwan

2015-11-01

In this paper, we study a nonparametric procedure to test independence of bivariate interval censored data; for both current status data (case 1 interval-censored data) and case 2 interval-censored data. To do it, we propose a score-based modification of the Kendall's tau statistic for bivariate interval-censored data. Our modification defines the Kendall's tau statistic with expected numbers of concordant and disconcordant pairs of data. The performance of the modified approach is illustrated by simulation studies and application to the AIDS study. We compare our method to alternative approaches such as the two-stage estimation method by Sun et al. (Scandinavian Journal of Statistics, 2006) and the multiple imputation method by Betensky and Finkelstein (Statistics in Medicine, 1999b). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Research on Error Modelling and Identification of 3 Axis NC Machine Tools Based on Cross Grid Encoder Measurement

International Nuclear Information System (INIS)

Du, Z C; Lv, C F; Hong, M S

2006-01-01

A new error modelling and identification method based on the cross grid encoder is proposed in this paper. Generally, there are 21 error components in the geometric error of the 3 axis NC machine tools. However according our theoretical analysis, the squareness error among different guide ways affects not only the translation error component, but also the rotational ones. Therefore, a revised synthetic error model is developed. And the mapping relationship between the error component and radial motion error of round workpiece manufactured on the NC machine tools are deduced. This mapping relationship shows that the radial error of circular motion is the comprehensive function result of all the error components of link, worktable, sliding table and main spindle block. Aiming to overcome the solution singularity shortcoming of traditional error component identification method, a new multi-step identification method of error component by using the Cross Grid Encoder measurement technology is proposed based on the kinematic error model of NC machine tool. Firstly, the 12 translational error components of the NC machine tool are measured and identified by using the least square method (LSM) when the NC machine tools go linear motion in the three orthogonal planes: XOY plane, XOZ plane and YOZ plane. Secondly, the circular error tracks are measured when the NC machine tools go circular motion in the same above orthogonal planes by using the cross grid encoder Heidenhain KGM 182. Therefore 9 rotational errors can be identified by using LSM. Finally the experimental validation of the above modelling theory and identification method is carried out in the 3 axis CNC vertical machining centre Cincinnati 750 Arrow. The entire 21 error components have been successfully measured out by the above method. Research shows the multi-step modelling and identification method is very suitable for 'on machine measurement'
Three-point method for measuring the geometric error components of linear and rotary axes based on sequential multilateration

International Nuclear Information System (INIS)

Zhang, Zhenjiu; Hu, Hong

2013-01-01

The linear and rotary axes are fundamental parts of multi-axis machine tools. The geometric error components of the axes must be measured for motion error compensation to improve the accuracy of the machine tools. In this paper, a simple method named the three point method is proposed to measure the geometric error of the linear and rotary axes of the machine tools using a laser tracker. A sequential multilateration method, where uncertainty is verified through simulation, is applied to measure the 3D coordinates. Three noncollinear points fixed on the stage of each axis are selected. The coordinates of these points are simultaneously measured using a laser tracker to obtain their volumetric errors by comparing these coordinates with ideal values. Numerous equations can be established using the geometric error models of each axis. The geometric error components can be obtained by solving these equations. The validity of the proposed method is verified through a series of experiments. The results indicate that the proposed method can measure the geometric error of the axes to compensate for the errors in multi-axis machine tools.
A Bivariate return period for levee failure monitoring

Science.gov (United States)

Isola, M.; Caporali, E.

2017-12-01

Levee breaches are strongly linked with the interaction processes among water, soil and structure, thus many are the factors that affect the breach development. One of the main is the hydraulic load, characterized by intensity and duration, i.e. by the flood event hydrograph. On the magnitude of the hydraulic load is based the levee design, generally without considering the fatigue failure due to the load duration. Moreover, many are the cases in which the levee breach are characterized by flood of magnitude lower than the design one. In order to implement the strategies of flood risk management, we built here a procedure based on a multivariate statistical analysis of flood peak and volume together with the analysis of the past levee failure events. Particularly, in order to define the probability of occurrence of the hydraulic load on a levee, a bivariate copula model is used to obtain the bivariate joint distribution of flood peak and volume. Flood peak is the expression of the load magnitude, while the volume is the expression of the stress over time. We consider the annual flood peak and the relative volume. The volume is given by the hydrograph area between the beginning and the end of event. The beginning of the event is identified as an abrupt rise of the discharge by more than 20%. The end is identified as the point from which the receding limb is characterized by the baseflow, using a nonlinear reservoir algorithm as baseflow separation technique. By this, with the aim to define warning thresholds we consider the past levee failure events and the relative bivariate return period (BTr) compared with the estimation of a traditional univariate model. The discharge data of 30 hydrometric stations of Arno River in Tuscany, Italy, in the period 1995-2016 are analysed. The database of levee failure events, considering for each event the location as well as the failure mode, is also created. The events were registered in the period 2000-2014 by EEA
GY SAMPLING THEORY IN ENVIRONMENTAL STUDIES 2: SUBSAMPLING ERROR MEASUREMENTS

Science.gov (United States)

Sampling can be a significant source of error in the measurement process. The characterization and cleanup of hazardous waste sites require data that meet site-specific levels of acceptable quality if scientifically supportable decisions are to be made. In support of this effort,...
ac driving amplitude dependent systematic error in scanning Kelvin probe microscope measurements: Detection and correction

International Nuclear Information System (INIS)

Wu Yan; Shannon, Mark A.

2006-01-01

The dependence of the contact potential difference (CPD) reading on the ac driving amplitude in scanning Kelvin probe microscope (SKPM) hinders researchers from quantifying true material properties. We show theoretically and demonstrate experimentally that an ac driving amplitude dependence in the SKPM measurement can come from a systematic error, and it is common for all tip sample systems as long as there is a nonzero tracking error in the feedback control loop of the instrument. We further propose a methodology to detect and to correct the ac driving amplitude dependent systematic error in SKPM measurements. The true contact potential difference can be found by applying a linear regression to the measured CPD versus one over ac driving amplitude data. Two scenarios are studied: (a) when the surface being scanned by SKPM is not semiconducting and there is an ac driving amplitude dependent systematic error; (b) when a semiconductor surface is probed and asymmetric band bending occurs when the systematic error is present. Experiments are conducted using a commercial SKPM and CPD measurement results of two systems: platinum-iridium/gap/gold and platinum-iridium/gap/thermal oxide/silicon are discussed
Development of a simple system for simultaneously measuring 6DOF geometric motion errors of a linear guide.

Science.gov (United States)

Qibo, Feng; Bin, Zhang; Cunxing, Cui; Cuifang, Kuang; Yusheng, Zhai; Fenglin, You

2013-11-04

A simple method for simultaneously measuring the 6DOF geometric motion errors of the linear guide was proposed. The mechanisms for measuring straightness and angular errors and for enhancing their resolution are described in detail. A common-path method for measuring the laser beam drift was proposed and it was used to compensate the errors produced by the laser beam drift in the 6DOF geometric error measurements. A compact 6DOF system was built. Calibration experiments with certain standard measurement meters showed that our system has a standard deviation of 0.5 µm in a range of ± 100 µm for the straightness measurements, and standard deviations of 0.5", 0.5", and 1.0" in the range of ± 100" for pitch, yaw, and roll measurements, respectively.
Error Analysis of Relative Calibration for RCS Measurement on Ground Plane Range

Directory of Open Access Journals (Sweden)

Wu Peng-fei

2012-03-01

Full Text Available Ground plane range is a kind of outdoor Radar Cross Section (RCS test range used for static measurement of full-size or scaled targets. Starting from the characteristics of ground plane range, the impact of environments on targets and calibrators is analyzed during calibration in the RCS measurements. The error of relative calibration produced by the different illumination of target and calibrator is studied. The relative calibration technique used in ground plane range is to place the calibrator on a fixed and auxiliary pylon somewhere between the radar and the target under test. By considering the effect of ground reflection and antenna pattern, the relationship between the magnitude of echoes and the position of calibrator is discussed. According to the different distances between the calibrator and target, the difference between free space and ground plane range is studied and the error of relative calibration is calculated. Numerical simulation results are presented with useful conclusions. The relative calibration error varies with the position of calibrator, frequency and antenna beam width. In most case, set calibrator close to the target may keep the error under control.
Characterization of positional errors and their influence on micro four-point probe measurements on a 100 nm Ru film

DEFF Research Database (Denmark)

Kjær, Daniel; Hansen, Ole; Østerberg, Frederik Westergaard

2015-01-01

Thin-film sheet resistance measurements at high spatial resolution and on small pads are important and can be realized with micrometer-scale four-point probes. As a result of the small scale the measurements are affected by electrode position errors. We have characterized the electrode position...... errors in measurements on Ru thin film using an Au-coated 12-point probe. We show that the standard deviation of the static electrode position error is on the order of 5 nm, which significantly affects the results of single configuration measurements. Position-error-corrected dual......-configuration measurements, however, are shown to eliminate the effect of position errors to a level limited either by electrical measurement noise or dynamic position errors. We show that the probe contact points remain almost static on the surface during the measurements (measured on an atomic scale) with a standard...
Chain Plot: A Tool for Exploiting Bivariate Temporal Structures

OpenAIRE

Taylor, CC; Zempeni, A

2004-01-01

In this paper we present a graphical tool useful for visualizing the cyclic behaviour of bivariate time series. We investigate its properties and link it to the asymmetry of the two variables concerned. We also suggest adding approximate confidence bounds to the points on the plot and investigate the effect of lagging to the chain plot. We conclude our paper by some standard Fourier analysis, relating and comparing this to the chain plot.
Positive phase error from parallel conductance in tetrapolar bio-impedance measurements and its compensation

Directory of Open Access Journals (Sweden)

Ivan M Roitt

2010-01-01

Full Text Available Bioimpedance measurements are of great use and can provide considerable insight into biological processes. However, there are a number of possible sources of measurement error that must be considered. The most dominant source of error is found in bipolar measurements where electrode polarisation effects are superimposed on the true impedance of the sample. Even with the tetrapolar approach that is commonly used to circumvent this issue, other errors can persist. Here we characterise the positive phase and rise in impedance magnitude with frequency that can result from the presence of any parallel conductive pathways in the measurement set-up. It is shown that fitting experimental data to an equivalent electrical circuit model allows for accurate determination of the true sample impedance as validated through finite element modelling (FEM of the measurement chamber. Finally, the model is used to extract dispersion information from cell cultures to characterise their growth.
Bivariate tensor product ( p , q $(p, q$ -analogue of Kantorovich-type Bernstein-Stancu-Schurer operators

Directory of Open Access Journals (Sweden)

Qing-Bo Cai

2017-11-01

Full Text Available Abstract In this paper, we construct a bivariate tensor product generalization of Kantorovich-type Bernstein-Stancu-Schurer operators based on the concept of ( p , q $(p, q$ -integers. We obtain moments and central moments of these operators, give the rate of convergence by using the complete modulus of continuity for the bivariate case and estimate a convergence theorem for the Lipschitz continuous functions. We also give some graphs and numerical examples to illustrate the convergence properties of these operators to certain functions.
The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model.

Science.gov (United States)

Fritz, Matthew S; Kenny, David A; MacKinnon, David P

2016-01-01

Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator-to-outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. To explore the combined effect of measurement error and omitted confounders in the same model, the effect of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect.
The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model

Science.gov (United States)

Fritz, Matthew S.; Kenny, David A.; MacKinnon, David P.

2016-01-01

Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator to outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. In order to explore the combined effect of measurement error and omitted confounders in the same model, the impact of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect. PMID:27739903
Optics measurement algorithms and error analysis for the proton energy frontier

Directory of Open Access Journals (Sweden)

A. Langner

2015-03-01

Full Text Available Optics measurement algorithms have been improved in preparation for the commissioning of the LHC at higher energy, i.e., with an increased damage potential. Due to machine protection considerations the higher energy sets tighter limits in the maximum excitation amplitude and the total beam charge, reducing the signal to noise ratio of optics measurements. Furthermore the precision in 2012 (4 TeV was insufficient to understand beam size measurements and determine interaction point (IP β-functions (β^{*}. A new, more sophisticated algorithm has been developed which takes into account both the statistical and systematic errors involved in this measurement. This makes it possible to combine more beam position monitor measurements for deriving the optical parameters and demonstrates to significantly improve the accuracy and precision. Measurements from the 2012 run have been reanalyzed which, due to the improved algorithms, result in a significantly higher precision of the derived optical parameters and decreased the average error bars by a factor of three to four. This allowed the calculation of β^{*} values and demonstrated to be fundamental in the understanding of emittance evolution during the energy ramp.
Optics measurement algorithms and error analysis for the proton energy frontier

Science.gov (United States)

Langner, A.; Tomás, R.

2015-03-01

Optics measurement algorithms have been improved in preparation for the commissioning of the LHC at higher energy, i.e., with an increased damage potential. Due to machine protection considerations the higher energy sets tighter limits in the maximum excitation amplitude and the total beam charge, reducing the signal to noise ratio of optics measurements. Furthermore the precision in 2012 (4 TeV) was insufficient to understand beam size measurements and determine interaction point (IP) β -functions (β*). A new, more sophisticated algorithm has been developed which takes into account both the statistical and systematic errors involved in this measurement. This makes it possible to combine more beam position monitor measurements for deriving the optical parameters and demonstrates to significantly improve the accuracy and precision. Measurements from the 2012 run have been reanalyzed which, due to the improved algorithms, result in a significantly higher precision of the derived optical parameters and decreased the average error bars by a factor of three to four. This allowed the calculation of β* values and demonstrated to be fundamental in the understanding of emittance evolution during the energy ramp.
Error reduction techniques for measuring long synchrotron mirrors

International Nuclear Information System (INIS)

Irick, S.

1998-07-01

Many instruments and techniques are used for measuring long mirror surfaces. A Fizeau interferometer may be used to measure mirrors much longer than the interferometer aperture size by using grazing incidence at the mirror surface and analyzing the light reflected from a flat end mirror. Advantages of this technique are data acquisition speed and use of a common instrument. Disadvantages are reduced sampling interval, uncertainty of tangential position, and sagittal/tangential aspect ratio other than unity. Also, deep aspheric surfaces cannot be measured on a Fizeau interferometer without a specially made fringe nulling holographic plate. Other scanning instruments have been developed for measuring height, slope, or curvature profiles of the surface, but lack accuracy for very long scans required for X-ray synchrotron mirrors. The Long Trace Profiler (LTP) was developed specifically for long x-ray mirror measurement, and still outperforms other instruments, especially for aspheres. Thus, this paper focuses on error reduction techniques for the LTP
Thin film thickness measurement error reduction by wavelength selection in spectrophotometry

International Nuclear Information System (INIS)

Tsepulin, Vladimir G; Perchik, Alexey V; Tolstoguzov, Victor L; Karasik, Valeriy E

2015-01-01

Fast and accurate volumetric profilometry of thin film structures is an important problem in the electronic visual display industry. We propose to use spectrophotometry with a limited number of working wavelengths to achieve high-speed control and an approach to selecting the optimal working wavelengths to reduce the thickness measurement error. A simple expression for error estimation is presented and tested using a Monte Carlo simulation. The experimental setup is designed to confirm the stability of film thickness determination using a limited number of wavelengths
A correction for emittance-measurement errors caused by finite slit and collector widths

International Nuclear Information System (INIS)

Connolly, R.C.

1992-01-01

One method of measuring the transverse phase-space distribution of a particle beam is to intercept the beam with a slit and measure the angular distribution of the beam passing through the slit using a parallel-strip collector. Together the finite widths of the slit and each collector strip form an acceptance window in phase space whose size and orientation are determined by the slit width, the strip width, and the slit-collector distance. If a beam is measured using a detector with a finite-size phase-space window, the measured distribution is different from the true distribution. The calculated emittance is larger than the true emittance, and the error depends both on the dimensions of the detector and on the Courant-Snyder parameters of the beam. Specifically, the error gets larger as the beam drifts farther from a waist. This can be important for measurements made on high-brightness beams, since power density considerations require that the beam be intercepted far from a waist. In this paper we calculate the measurement error and we show how the calculated emittance and Courant-Snyder parameters can be corrected for the effects of finite sizes of slit and collector. (Author) 5 figs., 3 refs
Research on Measurement Accuracy of Laser Tracking System Based on Spherical Mirror with Rotation Errors of Gimbal Mount Axes

Science.gov (United States)

Shi, Zhaoyao; Song, Huixu; Chen, Hongfang; Sun, Yanqiang

2018-02-01

This paper presents a novel experimental approach for confirming that spherical mirror of a laser tracking system can reduce the influences of rotation errors of gimbal mount axes on the measurement accuracy. By simplifying the optical system model of laser tracking system based on spherical mirror, we can easily extract the laser ranging measurement error caused by rotation errors of gimbal mount axes with the positions of spherical mirror, biconvex lens, cat's eye reflector, and measuring beam. The motions of polarization beam splitter and biconvex lens along the optical axis and vertical direction of optical axis are driven by error motions of gimbal mount axes. In order to simplify the experimental process, the motion of biconvex lens is substituted by the motion of spherical mirror according to the principle of relative motion. The laser ranging measurement error caused by the rotation errors of gimbal mount axes could be recorded in the readings of laser interferometer. The experimental results showed that the laser ranging measurement error caused by rotation errors was less than 0.1 μm if radial error motion and axial error motion were within ±10 μm. The experimental method simplified the experimental procedure and the spherical mirror could reduce the influences of rotation errors of gimbal mount axes on the measurement accuracy of the laser tracking system.

Cost-offsets of prescription drug expenditures: data analysis via a copula-based bivariate dynamic hurdle model.

Science.gov (United States)

Deb, Partha; Trivedi, Pravin K; Zimmer, David M

2014-10-01

In this paper, we estimate a copula-based bivariate dynamic hurdle model of prescription drug and nondrug expenditures to test the cost-offset hypothesis, which posits that increased expenditures on prescription drugs are offset by reductions in other nondrug expenditures. We apply the proposed methodology to data from the Medical Expenditure Panel Survey, which have the following features: (i) the observed bivariate outcomes are a mixture of zeros and continuously measured positives; (ii) both the zero and positive outcomes show state dependence and inter-temporal interdependence; and (iii) the zeros and the positives display contemporaneous association. The point mass at zero is accommodated using a hurdle or a two-part approach. The copula-based approach to generating joint distributions is appealing because the contemporaneous association involves asymmetric dependence. The paper studies samples categorized by four health conditions: arthritis, diabetes, heart disease, and mental illness. There is evidence of greater than dollar-for-dollar cost-offsets of expenditures on prescribed drugs for relatively low levels of spending on drugs and less than dollar-for-dollar cost-offsets at higher levels of drug expenditures. Copyright © 2013 John Wiley & Sons, Ltd.
Long-term continuous acoustical suspended-sediment measurements in rivers - Theory, application, bias, and error

Science.gov (United States)

Topping, David J.; Wright, Scott A.

2016-05-04

these sites. In addition, detailed, step-by-step procedures are presented for the general river application of the method.Quantification of errors in sediment-transport measurements made using this acoustical method is essential if the measurements are to be used effectively, for example, to evaluate uncertainty in long-term sediment loads and budgets. Several types of error analyses are presented to evaluate (1) the stability of acoustical calibrations over time, (2) the effect of neglecting backscatter from silt and clay, (3) the bias arising from changes in sand grain size, (4) the time-varying error in the method, and (5) the influence of nonrandom processes on error. Results indicate that (1) acoustical calibrations can be stable for long durations (multiple years), (2) neglecting backscatter from silt and clay can result in unacceptably high bias, (3) two frequencies are likely required to obtain sand-concentration measurements that are unbiased by changes in grain size, depending on site-specific conditions and acoustic frequency, (4) relative errors in silt-and-clay- and sand-concentration measurements decrease substantially as concentration increases, and (5) nonrandom errors may arise from slow changes in the spatial structure of suspended sediment that affect the relations between concentration in the acoustically ensonified part of the cross section and concentration in the entire river cross section. Taken together, the error analyses indicate that the two-frequency method produces unbiased measurements of suspended-silt-and-clay and sand concentration, with errors that are similar to, or larger than, those associated with conventional sampling methods.
The systematic error of temperature noise correlation measurement method and self-calibration

International Nuclear Information System (INIS)

Tian Hong; Tong Yunxian

1993-04-01

The turbulent transport behavior of fluid noise and the nature of noise affect on the velocity measurement system have been studied. The systematic error of velocity measurement system is analyzed. A theoretical calibration method is proposed, which makes the velocity measurement of time-correlation as an absolute measurement method. The theoretical results are in good agreement with experiments
Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems.

Science.gov (United States)

Bhadra, Anindya; Carroll, Raymond J

2016-07-01

In truncated polynomial spline or B-spline models where the covariates are measured with error, a fully Bayesian approach to model fitting requires the covariates and model parameters to be sampled at every Markov chain Monte Carlo iteration. Sampling the unobserved covariates poses a major computational problem and usually Gibbs sampling is not possible. This forces the practitioner to use a Metropolis-Hastings step which might suffer from unacceptable performance due to poor mixing and might require careful tuning. In this article we show for the cases of truncated polynomial spline or B-spline models of degree equal to one, the complete conditional distribution of the covariates measured with error is available explicitly as a mixture of double-truncated normals, thereby enabling a Gibbs sampling scheme. We demonstrate via a simulation study that our technique performs favorably in terms of computational efficiency and statistical performance. Our results indicate up to 62 and 54 % increase in mean integrated squared error efficiency when compared to existing alternatives while using truncated polynomial splines and B-splines respectively. Furthermore, there is evidence that the gain in efficiency increases with the measurement error variance, indicating the proposed method is a particularly valuable tool for challenging applications that present high measurement error. We conclude with a demonstration on a nutritional epidemiology data set from the NIH-AARP study and by pointing out some possible extensions of the current work.
General problems of metrology and indirect measuring in cardiology: error estimation criteria for indirect measurements of heart cycle phase durations

Directory of Open Access Journals (Sweden)

Konstantine K. Mamberger

2012-11-01

Full Text Available Aims This paper treats general problems of metrology and indirect measurement methods in cardiology. It is aimed at an identification of error estimation criteria for indirect measurements of heart cycle phase durations. Materials and methods A comparative analysis of an ECG of the ascending aorta recorded with the use of the Hemodynamic Analyzer Cardiocode (HDA lead versus conventional V3, V4, V5, V6 lead system ECGs is presented herein. Criteria for heart cycle phase boundaries are identified with graphic mathematical differentiation. Stroke volumes of blood SV calculated on the basis of the HDA phase duration measurements vs. echocardiography data are compared herein. Results The comparative data obtained in the study show an averaged difference at the level of 1%. An innovative noninvasive measuring technology originally developed by a Russian R & D team offers measuring stroke volume of blood SV with a high accuracy. Conclusion In practice, it is necessary to take into account some possible errors in measurements caused by hardware. Special attention should be paid to systematic errors.
Do Survey Data Estimate Earnings Inequality Correctly? Measurement Errors among Black and White Male Workers

Science.gov (United States)

Kim, ChangHwan; Tamborini, Christopher R.

2012-01-01

Few studies have considered how earnings inequality estimates may be affected by measurement error in self-reported earnings in surveys. Utilizing restricted-use data that links workers in the Survey of Income and Program Participation with their W-2 earnings records, we examine the effect of measurement error on estimates of racial earnings…
Model selection for marginal regression analysis of longitudinal data with missing observations and covariate measurement error.

Science.gov (United States)

Shen, Chung-Wei; Chen, Yi-Hau

2015-10-01

Missing observations and covariate measurement error commonly arise in longitudinal data. However, existing methods for model selection in marginal regression analysis of longitudinal data fail to address the potential bias resulting from these issues. To tackle this problem, we propose a new model selection criterion, the Generalized Longitudinal Information Criterion, which is based on an approximately unbiased estimator for the expected quadratic error of a considered marginal model accounting for both data missingness and covariate measurement error. The simulation results reveal that the proposed method performs quite well in the presence of missing data and covariate measurement error. On the contrary, the naive procedures without taking care of such complexity in data may perform quite poorly. The proposed method is applied to data from the Taiwan Longitudinal Study on Aging to assess the relationship of depression with health and social status in the elderly, accommodating measurement error in the covariate as well as missing observations. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Self-test web-based pure-tone audiometry: validity evaluation and measurement error analysis.

Science.gov (United States)

Masalski, Marcin; Kręcicki, Tomasz

2013-04-12

Potential methods of application of self-administered Web-based pure-tone audiometry conducted at home on a PC with a sound card and ordinary headphones depend on the value of measurement error in such tests. The aim of this research was to determine the measurement error of the hearing threshold determined in the way described above and to identify and analyze factors influencing its value. The evaluation of the hearing threshold was made in three series: (1) tests on a clinical audiometer, (2) self-tests done on a specially calibrated computer under the supervision of an audiologist, and (3) self-tests conducted at home. The research was carried out on the group of 51 participants selected from patients of an audiology outpatient clinic. From the group of 51 patients examined in the first two series, the third series was self-administered at home by 37 subjects (73%). The average difference between the value of the hearing threshold determined in series 1 and in series 2 was -1.54dB with standard deviation of 7.88dB and a Pearson correlation coefficient of .90. Between the first and third series, these values were -1.35dB±10.66dB and .84, respectively. In series 3, the standard deviation was most influenced by the error connected with the procedure of hearing threshold identification (6.64dB), calibration error (6.19dB), and additionally at the frequency of 250Hz by frequency nonlinearity error (7.28dB). The obtained results confirm the possibility of applying Web-based pure-tone audiometry in screening tests. In the future, modifications of the method leading to the decrease in measurement error can broaden the scope of Web-based pure-tone audiometry application.
Measurement Rounding Errors in an Assessment Model of Project Led Engineering Education

Directory of Open Access Journals (Sweden)

Francisco Moreira

2009-11-01

Full Text Available This paper analyzes the rounding errors that occur in the assessment of an interdisciplinary Project-Led Education (PLE process implemented in the Integrated Master degree on Industrial Management and Engineering (IME at University of Minho. PLE is an innovative educational methodology which makes use of active learning, promoting higher levels of motivation and students’ autonomy. The assessment model is based on multiple evaluation components with different weights. Each component can be evaluated by several teachers involved in different Project Supporting Courses (PSC. This model can be affected by different types of errors, namely: (1 rounding errors, and (2 non-uniform criteria of rounding the grades. A rigorous analysis of the assessment model was made and the rounding errors involved on each project component were characterized and measured. This resulted in a global maximum error of 0.308 on the individual student project grade, in a 0 to 100 scale. This analysis intended to improve not only the reliability of the assessment results, but also teachers’ awareness of this problem. Recommendations are also made in order to improve the assessment model and reduce the rounding errors as much as possible.
Unaccounted source of systematic errors in measurements of the Newtonian gravitational constant G

International Nuclear Information System (INIS)

DeSalvo, Riccardo

2015-01-01

Many precision measurements of G have produced a spread of results incompatible with measurement errors. Clearly an unknown source of systematic errors is at work. It is proposed here that most of the discrepancies derive from subtle deviations from Hooke's law, caused by avalanches of entangled dislocations. The idea is supported by deviations from linearity reported by experimenters measuring G, similarly to what is observed, on a larger scale, in low-frequency spring oscillators. Some mitigating experimental apparatus modifications are suggested. - Highlights: • Source of discrepancies on universal gravitational constant G measurements. • Collective motion of dislocations results in breakdown of Hook's law. • Self-organized criticality produce non-predictive shifts of equilibrium point. • New dissipation mechanism different from loss angle and viscous models is necessary. • Mitigation measures proposed may bring coherence to the measurements of G
Measurement error correction in the least absolute shrinkage and selection operator model when validation data are available.

Science.gov (United States)

Vasquez, Monica M; Hu, Chengcheng; Roe, Denise J; Halonen, Marilyn; Guerra, Stefano

2017-01-01

Measurement of serum biomarkers by multiplex assays may be more variable as compared to single biomarker assays. Measurement error in these data may bias parameter estimates in regression analysis, which could mask true associations of serum biomarkers with an outcome. The Least Absolute Shrinkage and Selection Operator (LASSO) can be used for variable selection in these high-dimensional data. Furthermore, when the distribution of measurement error is assumed to be known or estimated with replication data, a simple measurement error correction method can be applied to the LASSO method. However, in practice the distribution of the measurement error is unknown and is expensive to estimate through replication both in monetary cost and need for greater amount of sample which is often limited in quantity. We adapt an existing bias correction approach by estimating the measurement error using validation data in which a subset of serum biomarkers are re-measured on a random subset of the study sample. We evaluate this method using simulated data and data from the Tucson Epidemiological Study of Airway Obstructive Disease (TESAOD). We show that the bias in parameter estimation is reduced and variable selection is improved.
Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models.

Science.gov (United States)

De Haas, Y; Janss, L L G; Kadarmideen, H N

2007-10-01

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.
A simple approximation to the bivariate normal distribution with large correlation coefficient

NARCIS (Netherlands)

Albers, Willem/Wim; Kallenberg, W.C.M.

1994-01-01

The bivariate normal distribution function is approximated with emphasis on situations where the correlation coefficient is large. The high accuracy of the approximation is illustrated by numerical examples. Moreover, exact upper and lower bounds are presented as well as asymptotic results on the
Global assessment of predictability of water availability: A bivariate probabilistic Budyko analysis

Science.gov (United States)

Wang, Weiguang; Fu, Jianyu

2018-02-01

Estimating continental water availability is of great importance for water resources management, in terms of maintaining ecosystem integrity and sustaining society development. To more accurately quantify the predictability of water availability, on the basis of univariate probabilistic Budyko framework, a bivariate probabilistic Budyko approach was developed using copula-based joint distribution model for considering the dependence between parameter ω of Wang-Tang's equation and the Normalized Difference Vegetation Index (NDVI), and was applied globally. The results indicate the predictive performance in global water availability is conditional on the climatic condition. In comparison with simple univariate distribution, the bivariate one produces the lower interquartile range under the same global dataset, especially in the regions with higher NDVI values, highlighting the importance of developing the joint distribution by taking into account the dependence structure of parameter ω and NDVI, which can provide more accurate probabilistic evaluation of water availability.
Effects of Measurement Errors on Individual Tree Stem Volume Estimates for the Austrian National Forest Inventory

Science.gov (United States)

Ambros Berger; Thomas Gschwantner; Ronald E. McRoberts; Klemens. Schadauer

2014-01-01

National forest inventories typically estimate individual tree volumes using models that rely on measurements of predictor variables such as tree height and diameter, both of which are subject to measurement error. The aim of this study was to quantify the impacts of these measurement errors on the uncertainty of the model-based tree stem volume estimates. The impacts...
Test-Retest Reliability of the Adaptive Chemistry Assessment Survey for Teachers: Measurement Error and Alternatives to Correlation

Science.gov (United States)

Harshman, Jordan; Yezierski, Ellen

2016-01-01

Determining the error of measurement is a necessity for researchers engaged in bench chemistry, chemistry education research (CER), and a multitude of other fields. Discussions regarding what constructs measurement error entails and how to best measure them have occurred, but the critiques about traditional measures have yielded few alternatives.…
Influence of the statistical distribution of bioassay measurement errors on the intake estimation

International Nuclear Information System (INIS)

Lee, T. Y; Kim, J. K

2006-01-01

The purpose of this study is to provide the guidance necessary for making a selection of error distributions by analyzing influence of statistical distribution for a type of bioassay measurement error on the intake estimation. For this purpose, intakes were estimated using maximum likelihood method for cases that error distributions are normal and lognormal, and comparisons between two distributions for the estimated intakes were made. According to the results of this study, in case that measurement results for lung retention are somewhat greater than the limit of detection it appeared that distribution types have negligible influence on the results. Whereas in case of measurement results for the daily excretion rate, the results obtained from assumption of a lognormal distribution were 10% higher than those obtained from assumption of a normal distribution. In view of these facts, in case where uncertainty component is governed by counting statistics it is considered that distribution type have no influence on intake estimation. Whereas in case where the others are predominant, it is concluded that it is clearly desirable to estimate the intake assuming a lognormal distribution
Modifying Spearman's Attenuation Equation to Yield Partial Corrections for Measurement Error--With Application to Sample Size Calculations

Science.gov (United States)

Nicewander, W. Alan

2018-01-01

Spearman's correction for attenuation (measurement error) corrects a correlation coefficient for measurement errors in either-or-both of two variables, and follows from the assumptions of classical test theory. Spearman's equation removes all measurement error from a correlation coefficient which translates into "increasing the reliability of…
The Thirty Gigahertz Instrument Receiver for the QUIJOTE Experiment: Preliminary Polarization Measurements and Systematic-Error Analysis

Directory of Open Access Journals (Sweden)

Francisco J. Casas

2015-08-01

Full Text Available This paper presents preliminary polarization measurements and systematic-error characterization of the Thirty Gigahertz Instrument receiver developed for the QUIJOTE experiment. The instrument has been designed to measure the polarization of Cosmic Microwave Background radiation from the sky, obtaining the Q, U, and I Stokes parameters of the incoming signal simultaneously. Two kinds of linearly polarized input signals have been used as excitations in the polarimeter measurement tests in the laboratory; these show consistent results in terms of the Stokes parameters obtained. A measurement-based systematic-error characterization technique has been used in order to determine the possible sources of instrumental errors and to assist in the polarimeter calibration process.
On minimum divergence adaptation of discrete bivariate distributions to given marginals

Czech Academy of Sciences Publication Activity Database

Vajda, Igor; van der Meulen, E. C.

2005-01-01

Roč. 51, č. 1 (2005), s. 313-320 ISSN 0018-9448 R&D Projects: GA ČR GA201/02/1391; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : approximation of contingency tables * bivariate discrete distributions * minimization of divergences Subject RIV: BD - Theory of Information Impact factor: 2.183, year: 2005

Assessing thermally induced errors of machine tools by 3D length measurements

NARCIS (Netherlands)

Florussen, G.H.J.; Delbressine, F.L.M.; Schellekens, P.H.J.

2003-01-01

A new measurement technique is proposed for the assessment of thermally induced errors of machine tools. The basic idea is to measure changes of length by a telescopic double ball bar (TDEB) at multiple locations in the machine's workspace while the machine is thermally excited. In addition thermal
Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

Science.gov (United States)

Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2018-02-01

The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).
Proportion of medication error reporting and associated factors among nurses: a cross sectional study.

Science.gov (United States)

Jember, Abebaw; Hailu, Mignote; Messele, Anteneh; Demeke, Tesfaye; Hassen, Mohammed

2018-01-01

A medication error (ME) is any preventable event that may cause or lead to inappropriate medication use or patient harm. Voluntary reporting has a principal role in appreciating the extent and impact of medication errors. Thus, exploration of the proportion of medication error reporting and associated factors among nurses is important to inform service providers and program implementers so as to improve the quality of the healthcare services. Institution based quantitative cross-sectional study was conducted among 397 nurses from March 6 to May 10, 2015. Stratified sampling followed by simple random sampling technique was used to select the study participants. The data were collected using structured self-administered questionnaire which was adopted from studies conducted in Australia and Jordan. A pilot study was carried out to validate the questionnaire before data collection for this study. Bivariate and multivariate logistic regression models were fitted to identify factors associated with the proportion of medication error reporting among nurses. An adjusted odds ratio with 95% confidence interval was computed to determine the level of significance. The proportion of medication error reporting among nurses was found to be 57.4%. Regression analysis showed that sex, marital status, having made a medication error and medication error experience were significantly associated with medication error reporting. The proportion of medication error reporting among nurses in this study was found to be higher than other studies.
MEASUREMENT ERROR EFFECT ON THE POWER OF CONTROL CHART FOR ZERO-TRUNCATED POISSON DISTRIBUTION

Directory of Open Access Journals (Sweden)

Ashit Chakraborty

2013-09-01

Full Text Available Measurement error is the difference between the true value and the measured value of a quantity that exists in practice and may considerably affect the performance of control charts in some cases. Measurement error variability has uncertainty which can be from several sources. In this paper, we have studied the effect of these sources of variability on the power characteristics of control chart and obtained the values of average run length (ARL for zero-truncated Poisson distribution (ZTPD. Expression of the power of control chart for variable sample size under standardized normal variate for ZTPD is also derived.
Accounting for measurement error in log regression models with applications to accelerated testing.

Science.gov (United States)

Richardson, Robert; Tolley, H Dennis; Evenson, William E; Lunt, Barry M

2018-01-01

In regression settings, parameter estimates will be biased when the explanatory variables are measured with error. This bias can significantly affect modeling goals. In particular, accelerated lifetime testing involves an extrapolation of the fitted model, and a small amount of bias in parameter estimates may result in a significant increase in the bias of the extrapolated predictions. Additionally, bias may arise when the stochastic component of a log regression model is assumed to be multiplicative when the actual underlying stochastic component is additive. To account for these possible sources of bias, a log regression model with measurement error and additive error is approximated by a weighted regression model which can be estimated using Iteratively Re-weighted Least Squares. Using the reduced Eyring equation in an accelerated testing setting, the model is compared to previously accepted approaches to modeling accelerated testing data with both simulations and real data.
Accounting for measurement error in log regression models with applications to accelerated testing.

Directory of Open Access Journals (Sweden)

Robert Richardson

Full Text Available In regression settings, parameter estimates will be biased when the explanatory variables are measured with error. This bias can significantly affect modeling goals. In particular, accelerated lifetime testing involves an extrapolation of the fitted model, and a small amount of bias in parameter estimates may result in a significant increase in the bias of the extrapolated predictions. Additionally, bias may arise when the stochastic component of a log regression model is assumed to be multiplicative when the actual underlying stochastic component is additive. To account for these possible sources of bias, a log regression model with measurement error and additive error is approximated by a weighted regression model which can be estimated using Iteratively Re-weighted Least Squares. Using the reduced Eyring equation in an accelerated testing setting, the model is compared to previously accepted approaches to modeling accelerated testing data with both simulations and real data.
System for simultaneously measuring 6DOF geometric motion errors using a polarization maintaining fiber-coupled dual-frequency laser.

Science.gov (United States)

Cui, Cunxing; Feng, Qibo; Zhang, Bin; Zhao, Yuqiong

2016-03-21

A novel method for simultaneously measuring six degree-of-freedom (6DOF) geometric motion errors is proposed in this paper, and the corresponding measurement instrument is developed. Simultaneous measurement of 6DOF geometric motion errors using a polarization maintaining fiber-coupled dual-frequency laser is accomplished for the first time to the best of the authors' knowledge. Dual-frequency laser beams that are orthogonally linear polarized were adopted as the measuring datum. Positioning error measurement was achieved by heterodyne interferometry, and other 5DOF geometric motion errors were obtained by fiber collimation measurement. A series of experiments was performed to verify the effectiveness of the developed instrument. The experimental results showed that the stability and accuracy of the positioning error measurement are 31.1 nm and 0.5 μm, respectively. For the straightness error measurements, the stability and resolution are 60 and 40 nm, respectively, and the maximum deviation of repeatability is ± 0.15 μm in the x direction and ± 0.1 μm in the y direction. For pitch and yaw measurements, the stabilities are 0.03″ and 0.04″, the maximum deviations of repeatability are ± 0.18″ and ± 0.24″, and the accuracies are 0.4″ and 0.35″, respectively. The stability and resolution of roll measurement are 0.29″ and 0.2″, respectively, and the accuracy is 0.6″.
EFFECT OF MEASUREMENT ERRORS ON PREDICTED COSMOLOGICAL CONSTRAINTS FROM SHEAR PEAK STATISTICS WITH LARGE SYNOPTIC SURVEY TELESCOPE

Energy Technology Data Exchange (ETDEWEB)

Bard, D.; Chang, C.; Kahn, S. M.; Gilmore, K.; Marshall, S. [KIPAC, Stanford University, 452 Lomita Mall, Stanford, CA 94309 (United States); Kratochvil, J. M.; Huffenberger, K. M. [Department of Physics, University of Miami, Coral Gables, FL 33124 (United States); May, M. [Physics Department, Brookhaven National Laboratory, Upton, NY 11973 (United States); AlSayyad, Y.; Connolly, A.; Gibson, R. R.; Jones, L.; Krughoff, S. [Department of Astronomy, University of Washington, Seattle, WA 98195 (United States); Ahmad, Z.; Bankert, J.; Grace, E.; Hannel, M.; Lorenz, S. [Department of Physics, Purdue University, West Lafayette, IN 47907 (United States); Haiman, Z.; Jernigan, J. G., E-mail: djbard@slac.stanford.edu [Department of Astronomy and Astrophysics, Columbia University, New York, NY 10027 (United States); and others

2013-09-01

We study the effect of galaxy shape measurement errors on predicted cosmological constraints from the statistics of shear peak counts with the Large Synoptic Survey Telescope (LSST). We use the LSST Image Simulator in combination with cosmological N-body simulations to model realistic shear maps for different cosmological models. We include both galaxy shape noise and, for the first time, measurement errors on galaxy shapes. We find that the measurement errors considered have relatively little impact on the constraining power of shear peak counts for LSST.
Clinical measuring system for the form and position errors of circular workpieces using optical fiber sensors

Science.gov (United States)

Tan, Jiubin; Qiang, Xifu; Ding, Xuemei

1991-08-01

Optical sensors have two notable advantages in modern precision measurement. One is that they can be used in nondestructive measurement because the sensors need not touch the surfaces of workpieces in measuring. The other one is that they can strongly resist electromagnetic interferences, vibrations, and noises, so they are suitable to be used in machining sites. But the drift of light intensity and the changing of the reflection coefficient at different measuring positions of a workpiece may have great influence on measured results. To solve the problem, a spectroscopic differential characteristic compensating method is put forward. The method can be used effectively not only in compensating the measuring errors resulted from the drift of light intensity but also in eliminating the influence to measured results caused by the changing of the reflection coefficient. Also, the article analyzes the possibility of and the means of separating data errors of a clinical measuring system for form and position errors of circular workpieces.
A bivariate space-time downscaler under space and time misalignment.

Science.gov (United States)

Berrocal, Veronica J; Gelfand, Alan E; Holland, David M

2010-12-01

Ozone and particulate matter PM(2.5) are co-pollutants that have long been associated with increased public health risks. Information on concentration levels for both pollutants come from two sources: monitoring sites and output from complex numerical models that produce concentration surfaces over large spatial regions. In this paper, we offer a fully-model based approach for fusing these two sources of information for the pair of co-pollutants which is computationally feasible over large spatial regions and long periods of time. Due to the association between concentration levels of the two environmental contaminants, it is expected that information regarding one will help to improve prediction of the other. Misalignment is an obvious issue since the monitoring networks for the two contaminants only partly intersect and because the collection rate for PM(2.5) is typically less frequent than that for ozone.Extending previous work in Berrocal et al. (2009), we introduce a bivariate downscaler that provides a flexible class of bivariate space-time assimilation models. We discuss computational issues for model fitting and analyze a dataset for ozone and PM(2.5) for the ozone season during year 2002. We show a modest improvement in predictive performance, not surprising in a setting where we can anticipate only a small gain.
Characterization of the main error sources of chromatic confocal probes for dimensional measurement

International Nuclear Information System (INIS)

Nouira, H; El-Hayek, N; Yuan, X; Anwer, N

2014-01-01

Chromatic confocal probes are increasingly used in high-precision dimensional metrology applications such as roughness, form, thickness and surface profile measurements; however, their measurement behaviour is not well understood and must be characterized at a nanometre level. This paper provides a calibration bench for the characterization of two chromatic confocal probes of 20 and 350 µm travel ranges. The metrology loop that includes the chromatic confocal probe is stable and enables measurement repeatability at the nanometer level. With the proposed system, the major error sources, such as the relative axial and radial motions of the probe with respect to the sample, the material, colour and roughness of the measured sample, the relative deviation/tilt of the probe and the scanning speed are identified. Experimental test results show that the chromatic confocal probes are sensitive to these errors and that their measurement behaviour is highly dependent on them. (paper)
Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies

DEFF Research Database (Denmark)

Tybjærg-Hansen, Anne

2009-01-01

Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements...... of the risk factors are observed on a subsample. We extend the multivariate RC techniques to a meta-analysis framework where multiple studies provide independent repeat measurements and information on disease outcome. We consider the cases where some or all studies have repeat measurements, and compare study......-specific, averaged and empirical Bayes estimates of RC parameters. Additionally, we allow for binary covariates (e.g. smoking status) and for uncertainty and time trends in the measurement error corrections. Our methods are illustrated using a subset of individual participant data from prospective long-term studies...
Measurement of tokamak error fields using plasma response and its applicability to ITER

International Nuclear Information System (INIS)

Strait, E.J.; Buttery, R.J.; Chu, M.S.; Garofalo, A.M.; La Haye, R.J.; Schaffer, M.J.; Casper, T.A.; Gribov, Y.; Hanson, J.M.; Reimerdes, H.; Volpe, F.A.

2014-01-01

The nonlinear response of a low-beta tokamak plasma to non-axisymmetric fields offers an alternative to direct measurement of the non-axisymmetric part of the vacuum magnetic fields, often termed ‘error fields’. Possible approaches are discussed for determination of error fields and the required current in non-axisymmetric correction coils, with an emphasis on two relatively new methods: measurement of the torque balance on a saturated magnetic island, and measurement of the braking of plasma rotation in the absence of an island. The former is well suited to ohmically heated discharges, while the latter is more appropriate for discharges with a modest amount of neutral beam heating to drive rotation. Both can potentially provide continuous measurements during a discharge, subject to the limitation of a minimum averaging time. The applicability of these methods to ITER is discussed, and an estimate is made of their uncertainties in light of the specifications of ITER's diagnostic systems. The use of plasma response-based techniques in normal ITER operational scenarios may allow identification of the error field contributions by individual central solenoid coils, but identification of the individual contributions by the outer poloidal field coils or other sources is less likely to be feasible. (paper)
Potentiometric Measurement of Transition Ranges and Titration Errors for Acid/Base Indicators

Science.gov (United States)

Flowers, Paul A.

1997-07-01

Sophomore analytical chemistry courses typically devote a substantial amount of lecture time to acid/base equilibrium theory, and usually include at least one laboratory project employing potentiometric titrations. In an effort to provide students a laboratory experience that more directly supports their classroom discussions on this important topic, an experiment involving potentiometric measurement of transition ranges and titration errors for common acid/base indicators has been developed. The pH and visually-assessed color of a millimolar strong acid/base system are monitored as a function of added titrant volume, and the resultant data plotted to permit determination of the indicator's transition range and associated titration error. Student response is typically quite positive, and the measured quantities correlate reasonably well to literature values.
Evidence for bivariate linkage of obesity and HDL-C levels in the Framingham Heart Study.

Science.gov (United States)

Arya, Rector; Lehman, Donna; Hunt, Kelly J; Schneider, Jennifer; Almasy, Laura; Blangero, John; Stern, Michael P; Duggirala, Ravindranath

2003-12-31

Epidemiological studies have indicated that obesity and low high-density lipoprotein (HDL) levels are strong cardiovascular risk factors, and that these traits are inversely correlated. Despite the belief that these traits are correlated in part due to pleiotropy, knowledge on specific genes commonly affecting obesity and dyslipidemia is very limited. To address this issue, we first conducted univariate multipoint linkage analysis for body mass index (BMI) and HDL-C to identify loci influencing variation in these phenotypes using Framingham Heart Study data relating to 1702 subjects distributed across 330 pedigrees. Subsequently, we performed bivariate multipoint linkage analysis to detect common loci influencing covariation between these two traits. We scanned the genome and identified a major locus near marker D6S1009 influencing variation in BMI (LOD = 3.9) using the program SOLAR. We also identified a major locus for HDL-C near marker D2S1334 on chromosome 2 (LOD = 3.5) and another region near marker D6S1009 on chromosome 6 with suggestive evidence for linkage (LOD = 2.7). Since these two phenotypes have been independently mapped to the same region on chromosome 6q, we used the bivariate multipoint linkage approach using SOLAR. The bivariate linkage analysis of BMI and HDL-C implicated the genetic region near marker D6S1009 as harboring a major gene commonly influencing these phenotypes (bivariate LOD = 6.2; LODeq = 5.5) and appears to improve power to map the correlated traits to a region, precisely. We found substantial evidence for a quantitative trait locus with pleiotropic effects, which appears to influence both BMI and HDL-C phenotypes in the Framingham data.
The bivariate probit model of uncomplicated control of tumor: a heuristic exposition of the methodology

International Nuclear Information System (INIS)

Herbert, Donald

1997-01-01

Purpose: To describe the concept, models, and methods for the construction of estimates of joint probability of uncomplicated control of tumors in radiation oncology. Interpolations using this model can lead to the identification of more efficient treatment regimens for an individual patient. The requirement to find the treatment regimen that will maximize the joint probability of uncomplicated control of tumors suggests a new class of evolutionary experimental designs--Response Surface Methods--for clinical trials in radiation oncology. Methods and Materials: The software developed by Lesaffre and Molenberghs is used to construct bivariate probit models of the joint probability of uncomplicated control of cancer of the oropharynx from a set of 45 patients for each of whom the presence/absence of recurrent tumor (the binary event E-bar 1 /E 1 ) and the presence/absence of necrosis (the binary event E 2 /E-bar 2 ) of the normal tissues of the target volume is recorded, together with the treatment variables dose, time, and fractionation. Results: The bivariate probit model can be used to select a treatment regime that will give a specified probability, say P(S) = 0.60, of uncomplicated control of tumor by interpolation within a set of treatment regimes with known outcomes of recurrence and necrosis. The bivariate probit model can be used to guide a sequence of clinical trials to find the maximum probability of uncomplicated control of tumor for patients in a given prognostic stratum using Response Surface methods by extrapolation from an initial set of treatment regimens. Conclusions: The design of treatments for individual patients and the design of clinical trials might be improved by use of a bivariate probit model and Response Surface Methods
Robust estimation of partially linear models for longitudinal data with dropouts and measurement error.

Science.gov (United States)

Qin, Guoyou; Zhang, Jiajia; Zhu, Zhongyi; Fung, Wing

2016-12-20

Outliers, measurement error, and missing data are commonly seen in longitudinal data because of its data collection process. However, no method can address all three of these issues simultaneously. This paper focuses on the robust estimation of partially linear models for longitudinal data with dropouts and measurement error. A new robust estimating equation, simultaneously tackling outliers, measurement error, and missingness, is proposed. The asymptotic properties of the proposed estimator are established under some regularity conditions. The proposed method is easy to implement in practice by utilizing the existing standard generalized estimating equations algorithms. The comprehensive simulation studies show the strength of the proposed method in dealing with longitudinal data with all three features. Finally, the proposed method is applied to data from the Lifestyle Education for Activity and Nutrition study and confirms the effectiveness of the intervention in producing weight loss at month 9. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Experimental validation of error in temperature measurements in thin walled ductile iron castings

DEFF Research Database (Denmark)

Pedersen, Karl Martin; Tiedje, Niels Skat

2007-01-01

An experimental analysis has been performed to validate the measurement error of cooling curves measured in thin walled ductile cast iron. Specially designed thermocouples with Ø0.2 mm thermocouple wire in Ø1.6 mm ceramic tube was used for the experiments. Temperatures were measured in plates...
Nano-metrology: The art of measuring X-ray mirrors with slope errors <100 nrad

Energy Technology Data Exchange (ETDEWEB)

Alcock, Simon G., E-mail: simon.alcock@diamond.ac.uk; Nistea, Ioana; Sawhney, Kawal [Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot, Oxfordshire OX11 0DE (United Kingdom)

2016-05-15

We present a comprehensive investigation of the systematic and random errors of the nano-metrology instruments used to characterize synchrotron X-ray optics at Diamond Light Source. With experimental skill and careful analysis, we show that these instruments used in combination are capable of measuring state-of-the-art X-ray mirrors. Examples are provided of how Diamond metrology data have helped to achieve slope errors of <100 nrad for optical systems installed on synchrotron beamlines, including: iterative correction of substrates using ion beam figuring and optimal clamping of monochromator grating blanks in their holders. Simulations demonstrate how random noise from the Diamond-NOM’s autocollimator adds into the overall measured value of the mirror’s slope error, and thus predict how many averaged scans are required to accurately characterize different grades of mirror.
Nano-metrology: The art of measuring X-ray mirrors with slope errors <100 nrad

International Nuclear Information System (INIS)

Alcock, Simon G.; Nistea, Ioana; Sawhney, Kawal

2016-01-01

We present a comprehensive investigation of the systematic and random errors of the nano-metrology instruments used to characterize synchrotron X-ray optics at Diamond Light Source. With experimental skill and careful analysis, we show that these instruments used in combination are capable of measuring state-of-the-art X-ray mirrors. Examples are provided of how Diamond metrology data have helped to achieve slope errors of <100 nrad for optical systems installed on synchrotron beamlines, including: iterative correction of substrates using ion beam figuring and optimal clamping of monochromator grating blanks in their holders. Simulations demonstrate how random noise from the Diamond-NOM’s autocollimator adds into the overall measured value of the mirror’s slope error, and thus predict how many averaged scans are required to accurately characterize different grades of mirror.

Nano-metrology: The art of measuring X-ray mirrors with slope errors <100 nrad.

Science.gov (United States)

Alcock, Simon G; Nistea, Ioana; Sawhney, Kawal

2016-05-01

We present a comprehensive investigation of the systematic and random errors of the nano-metrology instruments used to characterize synchrotron X-ray optics at Diamond Light Source. With experimental skill and careful analysis, we show that these instruments used in combination are capable of measuring state-of-the-art X-ray mirrors. Examples are provided of how Diamond metrology data have helped to achieve slope errors of <100 nrad for optical systems installed on synchrotron beamlines, including: iterative correction of substrates using ion beam figuring and optimal clamping of monochromator grating blanks in their holders. Simulations demonstrate how random noise from the Diamond-NOM's autocollimator adds into the overall measured value of the mirror's slope error, and thus predict how many averaged scans are required to accurately characterize different grades of mirror.
Bayesian semiparametric mixture Tobit models with left censoring, skewness, and covariate measurement errors.

Science.gov (United States)

Dagne, Getachew A; Huang, Yangxin

2013-09-30

Common problems to many longitudinal HIV/AIDS, cancer, vaccine, and environmental exposure studies are the presence of a lower limit of quantification of an outcome with skewness and time-varying covariates with measurement errors. There has been relatively little work published simultaneously dealing with these features of longitudinal data. In particular, left-censored data falling below a limit of detection may sometimes have a proportion larger than expected under a usually assumed log-normal distribution. In such cases, alternative models, which can account for a high proportion of censored data, should be considered. In this article, we present an extension of the Tobit model that incorporates a mixture of true undetectable observations and those values from a skew-normal distribution for an outcome with possible left censoring and skewness, and covariates with substantial measurement error. To quantify the covariate process, we offer a flexible nonparametric mixed-effects model within the Tobit framework. A Bayesian modeling approach is used to assess the simultaneous impact of left censoring, skewness, and measurement error in covariates on inference. The proposed methods are illustrated using real data from an AIDS clinical study. . Copyright © 2013 John Wiley & Sons, Ltd.
Degradation data analysis based on a generalized Wiener process subject to measurement error

Science.gov (United States)

Li, Junxing; Wang, Zhihua; Zhang, Yongbo; Fu, Huimin; Liu, Chengrui; Krishnaswamy, Sridhar

2017-09-01

Wiener processes have received considerable attention in degradation modeling over the last two decades. In this paper, we propose a generalized Wiener process degradation model that takes unit-to-unit variation, time-correlated structure and measurement error into considerations simultaneously. The constructed methodology subsumes a series of models studied in the literature as limiting cases. A simple method is given to determine the transformed time scale forms of the Wiener process degradation model. Then model parameters can be estimated based on a maximum likelihood estimation (MLE) method. The cumulative distribution function (CDF) and the probability distribution function (PDF) of the Wiener process with measurement errors are given based on the concept of the first hitting time (FHT). The percentiles of performance degradation (PD) and failure time distribution (FTD) are also obtained. Finally, a comprehensive simulation study is accomplished to demonstrate the necessity of incorporating measurement errors in the degradation model and the efficiency of the proposed model. Two illustrative real applications involving the degradation of carbon-film resistors and the wear of sliding metal are given. The comparative results show that the constructed approach can derive a reasonable result and an enhanced inference precision.
Dynamic Modeling Accuracy Dependence on Errors in Sensor Measurements, Mass Properties, and Aircraft Geometry

Science.gov (United States)

Grauer, Jared A.; Morelli, Eugene A.

2013-01-01

A nonlinear simulation of the NASA Generic Transport Model was used to investigate the effects of errors in sensor measurements, mass properties, and aircraft geometry on the accuracy of dynamic models identified from flight data. Measurements from a typical system identification maneuver were systematically and progressively deteriorated and then used to estimate stability and control derivatives within a Monte Carlo analysis. Based on the results, recommendations were provided for maximum allowable errors in sensor measurements, mass properties, and aircraft geometry to achieve desired levels of dynamic modeling accuracy. Results using other flight conditions, parameter estimation methods, and a full-scale F-16 nonlinear aircraft simulation were compared with these recommendations.
Technical note: Towards a continuous classification of climate using bivariate colour mapping

NARCIS (Netherlands)

Teuling, A.J.

2011-01-01

Climate is often defined in terms of discrete classes. Here I use bivariate colour mapping to show that the global distribution of K¨oppen-Geiger climate classes can largely be reproduced by combining the simple means of two key states of the climate system 5 (i.e., air temperature and relative
DOI resolution measurement and error analysis with LYSO and APDs

International Nuclear Information System (INIS)

Lee, Chae-hun; Cho, Gyuseong

2008-01-01

Spatial resolution degradation in PET occurs at the edge of Field Of View (FOV) due to parallax error. To improve spatial resolution at the edge of FOV, Depth-Of-Interaction (DOI) PET has been investigated and several methods for DOI positioning were proposed. In this paper, a DOI-PET detector module using two 8x4 array avalanche photodiodes (APDs) (Hamamatsu, S8550) and a 2 cm long LYSO scintillation crystal was proposed and its DOI characteristics were investigated experimentally. In order to measure DOI positions, signals from two APDs were compared. Energy resolution was obtained from the sum of two APDs' signals and DOI positioning error was calculated. Finally, an optimum DOI step size in a 2 cm long LYSO were suggested to help to design a DOI-PET
Measurement error potential and control when quantifying volatile hydrocarbon concentrations in soils

International Nuclear Information System (INIS)

Siegrist, R.L.

1991-01-01

Due to their widespread use throughout commerce and industry, volatile hydrocarbons such as toluene, trichloroethene, and 1, 1,1-trichloroethane routinely appears as principal pollutants in contamination of soil system hydrocarbons is necessary to confirm the presence of contamination and its nature and extent; to assess site risks and the need for cleanup; to evaluate remedial technologies; and to verify the performance of a selected alternative. Decisions regarding these issues have far-reaching impacts and, ideally, should be based on accurate measurements of soil hydrocarbon concentrations. Unfortunately, quantification of volatile hydrocarbons in soils is extremely difficult and there is normally little understanding of the accuracy and precision of these measurements. Rather, the assumptions often implicitly made that the hydrocarbon data are sufficiently accurate for the intended purpose. This appear presents a discussion of measurement error potential when quantifying volatile hydrocarbons in soils, and outlines some methods for understanding the managing these errors
Part two: Error propagation

International Nuclear Information System (INIS)

Picard, R.R.

1989-01-01

Topics covered in this chapter include a discussion of exact results as related to nuclear materials management and accounting in nuclear facilities; propagation of error for a single measured value; propagation of error for several measured values; error propagation for materials balances; and an application of error propagation to an example of uranium hexafluoride conversion process
Circular Array of Magnetic Sensors for Current Measurement: Analysis for Error Caused by Position of Conductor.

Science.gov (United States)

Yu, Hao; Qian, Zheng; Liu, Huayi; Qu, Jiaqi

2018-02-14

This paper analyzes the measurement error, caused by the position of the current-carrying conductor, of a circular array of magnetic sensors for current measurement. The circular array of magnetic sensors is an effective approach for AC or DC non-contact measurement, as it is low-cost, light-weight, has a large linear range, wide bandwidth, and low noise. Especially, it has been claimed that such structure has excellent reduction ability for errors caused by the position of the current-carrying conductor, crosstalk current interference, shape of the conduction cross-section, and the Earth's magnetic field. However, the positions of the current-carrying conductor-including un-centeredness and un-perpendicularity-have not been analyzed in detail until now. In this paper, for the purpose of having minimum measurement error, a theoretical analysis has been proposed based on vector inner and exterior product. In the presented mathematical model of relative error, the un-center offset distance, the un-perpendicular angle, the radius of the circle, and the number of magnetic sensors are expressed in one equation. The comparison of the relative error caused by the position of the current-carrying conductor between four and eight sensors is conducted. Tunnel magnetoresistance (TMR) sensors are used in the experimental prototype to verify the mathematical model. The analysis results can be the reference to design the details of the circular array of magnetic sensors for current measurement in practical situations.
[Errors in medicine. Causes, impact and improvement measures to improve patient safety].

Science.gov (United States)

Waeschle, R M; Bauer, M; Schmidt, C E

2015-09-01

The guarantee of quality of care and patient safety is of major importance in hospitals even though increased economic pressure and work intensification are ubiquitously present. Nevertheless, adverse events still occur in 3-4 % of hospital stays and of these 25-50 % are estimated to be avoidable. The identification of possible causes of error and the development of measures for the prevention of medical errors are essential for patient safety. The implementation and continuous development of a constructive culture of error tolerance are fundamental.The origins of errors can be differentiated into systemic latent and individual active causes and components of both categories are typically involved when an error occurs. Systemic causes are, for example out of date structural environments, lack of clinical standards and low personnel density. These causes arise far away from the patient, e.g. management decisions and can remain unrecognized for a long time. Individual causes involve, e.g. confirmation bias, error of fixation and prospective memory failure. These causes have a direct impact on patient care and can result in immediate injury to patients. Stress, unclear information, complex systems and a lack of professional experience can promote individual causes. Awareness of possible causes of error is a fundamental precondition to establishing appropriate countermeasures.Error prevention should include actions directly affecting the causes of error and includes checklists and standard operating procedures (SOP) to avoid fixation and prospective memory failure and team resource management to improve communication and the generation of collective mental models. Critical incident reporting systems (CIRS) provide the opportunity to learn from previous incidents without resulting in injury to patients. Information technology (IT) support systems, such as the computerized physician order entry system, assist in the prevention of medication errors by providing
Estimation of perspective errors in 2D2C-PIV measurements for 3D concentrated vortices

Science.gov (United States)

Ma, Bao-Feng; Jiang, Hong-Gang

2018-06-01

Two-dimensional planar PIV (2D2C) is still extensively employed in flow measurement owing to its availability and reliability, although more advanced PIVs have been developed. It has long been recognized that there exist perspective errors in velocity fields when employing the 2D2C PIV to measure three-dimensional (3D) flows, the magnitude of which depends on out-of-plane velocity and geometric layouts of the PIV. For a variety of vortex flows, however, the results are commonly represented by vorticity fields, instead of velocity fields. The present study indicates that the perspective error in vorticity fields relies on gradients of the out-of-plane velocity along a measurement plane, instead of the out-of-plane velocity itself. More importantly, an estimation approach to the perspective error in 3D vortex measurements was proposed based on a theoretical vortex model and an analysis on physical characteristics of the vortices, in which the gradient of out-of-plane velocity is uniquely determined by the ratio of the maximum out-of-plane velocity to maximum swirling velocity of the vortex; meanwhile, the ratio has upper limits for naturally formed vortices. Therefore, if the ratio is imposed with the upper limits, the perspective error will only rely on the geometric layouts of PIV that are known in practical measurements. Using this approach, the upper limits of perspective errors of a concentrated vortex can be estimated for vorticity and other characteristic quantities of the vortex. In addition, the study indicates that the perspective errors in vortex location, vortex strength, and vortex radius can be all zero for axisymmetric vortices if they are calculated by proper methods. The dynamic mode decomposition on an oscillatory vortex indicates that the perspective errors of each DMD mode are also only dependent on the gradient of out-of-plane velocity if the modes are represented by vorticity.
A method of moments to estimate bivariate survival functions: the copula approach

Directory of Open Access Journals (Sweden)

Silvia Angela Osmetti

2013-05-01

Full Text Available In this paper we discuss the problem on parametric and non parametric estimation of the distributions generated by the Marshall-Olkin copula. This copula comes from the Marshall-Olkin bivariate exponential distribution used in reliability analysis. We generalize this model by the copula and different marginal distributions to construct several bivariate survival functions. The cumulative distribution functions are not absolutely continuous and they unknown parameters are often not be obtained in explicit form. In order to estimate the parameters we propose an easy procedure based on the moments. This method consist in two steps: in the first step we estimate only the parameters of marginal distributions and in the second step we estimate only the copula parameter. This procedure can be used to estimate the parameters of complex survival functions in which it is difficult to find an explicit expression of the mixed moments. Moreover it is preferred to the maximum likelihood one for its simplex mathematic form; in particular for distributions whose maximum likelihood parameters estimators can not be obtained in explicit form.
Errors of first-order probe correction for higher-order probes in spherical near-field antenna measurements

DEFF Research Database (Denmark)

Laitinen, Tommi; Nielsen, Jeppe Majlund; Pivnenko, Sergiy

2004-01-01

An investigation is performed to study the error of the far-field pattern determined from a spherical near-field antenna measurement in the case where a first-order (mu=+-1) probe correction scheme is applied to the near-field signal measured by a higher-order probe.......An investigation is performed to study the error of the far-field pattern determined from a spherical near-field antenna measurement in the case where a first-order (mu=+-1) probe correction scheme is applied to the near-field signal measured by a higher-order probe....
Mixtures of Berkson and classical covariate measurement error in the linear mixed model: Bias analysis and application to a study on ultrafine particles.

Science.gov (United States)

Deffner, Veronika; Küchenhoff, Helmut; Breitner, Susanne; Schneider, Alexandra; Cyrys, Josef; Peters, Annette

2018-03-13

The ultrafine particle measurements in the Augsburger Umweltstudie, a panel study conducted in Augsburg, Germany, exhibit measurement error from various sources. Measurements of mobile devices show classical possibly individual-specific measurement error; Berkson-type error, which may also vary individually, occurs, if measurements of fixed monitoring stations are used. The combination of fixed site and individual exposure measurements results in a mixture of the two error types. We extended existing bias analysis approaches to linear mixed models with a complex error structure including individual-specific error components, autocorrelated errors, and a mixture of classical and Berkson error. Theoretical considerations and simulation results show, that autocorrelation may severely change the attenuation of the effect estimations. Furthermore, unbalanced designs and the inclusion of confounding variables influence the degree of attenuation. Bias correction with the method of moments using data with mixture measurement error partially yielded better results compared to the usage of incomplete data with classical error. Confidence intervals (CIs) based on the delta method achieved better coverage probabilities than those based on Bootstrap samples. Moreover, we present the application of these new methods to heart rate measurements within the Augsburger Umweltstudie: the corrected effect estimates were slightly higher than their naive equivalents. The substantial measurement error of ultrafine particle measurements has little impact on the results. The developed methodology is generally applicable to longitudinal data with measurement error. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies.

NARCIS (Netherlands)

Kromhout, D.

2009-01-01

Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements of the
An integrated user-friendly ArcMAP tool for bivariate statistical modeling in geoscience applications

Science.gov (United States)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusof, Z.; Tehrany, M. S.

2014-10-01

Modeling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modeling. Bivariate statistical analysis (BSA) assists in hazard modeling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, BSM (bivariate statistical modeler), for BSA technique is proposed. Three popular BSA techniques such as frequency ratio, weights-of-evidence, and evidential belief function models are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and is created by a simple graphical user interface, which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.
An integrated user-friendly ArcMAP tool for bivariate statistical modelling in geoscience applications

Science.gov (United States)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusoff, Z. M.; Tehrany, M. S.

2015-03-01

Modelling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modelling. Bivariate statistical analysis (BSA) assists in hazard modelling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time-consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, bivariate statistical modeler (BSM), for BSA technique is proposed. Three popular BSA techniques, such as frequency ratio, weight-of-evidence (WoE), and evidential belief function (EBF) models, are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and created by a simple graphical user interface (GUI), which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve (AUC) is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.
Modeling gene expression measurement error: a quasi-likelihood approach

Directory of Open Access Journals (Sweden)

Strimmer Korbinian

2003-03-01

Full Text Available Abstract Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale. Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood. Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic variance structure of the data. As the quasi-likelihood behaves (almost like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also
Particle Filter with Novel Nonlinear Error Model for Miniature Gyroscope-Based Measurement While Drilling Navigation

Directory of Open Access Journals (Sweden)

Tao Li

2016-03-01

Full Text Available The derivation of a conventional error model for the miniature gyroscope-based measurement while drilling (MGWD system is based on the assumption that the errors of attitude are small enough so that the direction cosine matrix (DCM can be approximated or simplified by the errors of small-angle attitude. However, the simplification of the DCM would introduce errors to the navigation solutions of the MGWD system if the initial alignment cannot provide precise attitude, especially for the low-cost microelectromechanical system (MEMS sensors operated in harsh multilateral horizontal downhole drilling environments. This paper proposes a novel nonlinear error model (NNEM by the introduction of the error of DCM, and the NNEM can reduce the propagated errors under large-angle attitude error conditions. The zero velocity and zero position are the reference points and the innovations in the states estimation of particle filter (PF and Kalman filter (KF. The experimental results illustrate that the performance of PF is better than KF and the PF with NNEM can effectively restrain the errors of system states, especially for the azimuth, velocity, and height in the quasi-stationary condition.
Particle Filter with Novel Nonlinear Error Model for Miniature Gyroscope-Based Measurement While Drilling Navigation.

Science.gov (United States)

Li, Tao; Yuan, Gannan; Li, Wang

2016-03-15

The derivation of a conventional error model for the miniature gyroscope-based measurement while drilling (MGWD) system is based on the assumption that the errors of attitude are small enough so that the direction cosine matrix (DCM) can be approximated or simplified by the errors of small-angle attitude. However, the simplification of the DCM would introduce errors to the navigation solutions of the MGWD system if the initial alignment cannot provide precise attitude, especially for the low-cost microelectromechanical system (MEMS) sensors operated in harsh multilateral horizontal downhole drilling environments. This paper proposes a novel nonlinear error model (NNEM) by the introduction of the error of DCM, and the NNEM can reduce the propagated errors under large-angle attitude error conditions. The zero velocity and zero position are the reference points and the innovations in the states estimation of particle filter (PF) and Kalman filter (KF). The experimental results illustrate that the performance of PF is better than KF and the PF with NNEM can effectively restrain the errors of system states, especially for the azimuth, velocity, and height in the quasi-stationary condition.

Analysis of liquid medication dose errors made by patients and caregivers using alternative measuring devices.

Science.gov (United States)

Ryu, Gyeong Suk; Lee, Yu Jeung

2012-01-01

Patients use several types of devices to measure liquid medication. Using a criterion ranging from a 10% to 40% variation from a target 5 mL for a teaspoon dose, previous studies have found that a considerable proportion of patients or caregivers make errors when dosing liquid medication with measuring devices. To determine the rate and magnitude of liquid medication dose errors that occur with patient/caregiver use of various measuring devices in a community pharmacy. Liquid medication measurements by patients or caregivers were observed in a convenience sample of community pharmacy patrons in Korea during a 2-week period in March 2011. Participants included all patients or caregivers (N = 300) who came to the pharmacy to buy over-the-counter liquid medication or to have a liquid medication prescription filled during the study period. The participants were instructed by an investigator who was also a pharmacist to select their preferred measuring devices from 6 alternatives (etched-calibration dosing cup, printed-calibration dosing cup, dosing spoon, syringe, dispensing bottle, or spoon with a bottle adapter) and measure a 5 mL dose of Coben (chlorpheniramine maleate/phenylephrine HCl, Daewoo Pharm. Co., Ltd) syrup using the device of their choice. The investigator used an ISOLAB graduated cylinder (Germany, blue grad, 10 mL) to measure the amount of syrup dispensed by the study participants. Participant characteristics were recorded including gender, age, education level, and relationship to the person for whom the medication was intended. Of the 300 participants, 257 (85.7%) were female; 286 (95.3%) had at least a high school education; and 282 (94.0%) were caregivers (parent or grandparent) for the patient. The mean (SD) measured dose was 4.949 (0.378) mL for the 300 participants. In analysis of variance of the 6 measuring devices, the greatest difference from the 5 mL target was a mean 5.552 mL for 17 subjects who used the regular (etched) dosing cup and 4
Comparing Two Inferential Approaches to Handling Measurement Error in Mixed-Mode Surveys

Directory of Open Access Journals (Sweden)

Buelens Bart

2017-06-01

Full Text Available Nowadays sample survey data collection strategies combine web, telephone, face-to-face, or other modes of interviewing in a sequential fashion. Measurement bias of survey estimates of means and totals are composed of different mode-dependent measurement errors as each data collection mode has its own associated measurement error. This article contains an appraisal of two recently proposed methods of inference in this setting. The first is a calibration adjustment to the survey weights so as to balance the survey response to a prespecified distribution of the respondents over the modes. The second is a prediction method that seeks to correct measurements towards a benchmark mode. The two methods are motivated differently but at the same time coincide in some circumstances and agree in terms of required assumptions. The methods are applied to the Labour Force Survey in the Netherlands and are found to provide almost identical estimates of the number of unemployed. Each method has its own specific merits. Both can be applied easily in practice as they do not require additional data collection beyond the regular sequential mixed-mode survey, an attractive element for national statistical institutes and other survey organisations.
Bivariate Cointegration Analysis of Energy-Economy Interactions in Iran

Directory of Open Access Journals (Sweden)

Ismail Oladimeji Soile

2015-12-01

Full Text Available Fixing the prices of energy products below their opportunity cost for welfare and redistribution purposes is common with governments of many oil producing developing countries. This has often resulted in huge energy consumption in developing countries and the question that emerge is whether this increased energy consumption results in higher economic activities. Available statistics show that Iran’s economy growth shrunk for the first time in two decades from 2011 amidst the introduction of pricing reform in 2010 and 2014 suggesting a relationship between energy use and economic growth. Accordingly, the study examined the causality and the likelihood of a long term relationship between energy and economic growth in Iran. Unlike previous studies which have focused on the effects and effectiveness of the reform, the paper investigates the rationale for the reform. The study applied a bivariate cointegration time series econometric approach. The results reveals a one-way causality running from economic growth to energy with no feedback with evidence of long run connection. The implication of this is that energy conservation policy is not inimical to economic growth. This evidence lend further support for the ongoing subsidy reforms in Iran as a measure to check excessive and inefficient use of energy.
Analysis of interactive fixed effects dynamic linear panel regression with measurement error

OpenAIRE

Nayoung Lee; Hyungsik Roger Moon; Martin Weidner

2011-01-01

This paper studies a simple dynamic panel linear regression model with interactive fixed effects in which the variable of interest is measured with error. To estimate the dynamic coefficient, we consider the least-squares minimum distance (LS-MD) estimation method.
Two-dimensional errors

International Nuclear Information System (INIS)

Anon.

1991-01-01

This chapter addresses the extension of previous work in one-dimensional (linear) error theory to two-dimensional error analysis. The topics of the chapter include the definition of two-dimensional error, the probability ellipse, the probability circle, elliptical (circular) error evaluation, the application to position accuracy, and the use of control systems (points) in measurements
Assessment and Calibration of Ultrasonic Measurement Errors in Estimating Weathering Index of Stone Cultural Heritage

Science.gov (United States)

Lee, Y.; Keehm, Y.

2011-12-01

Estimating the degree of weathering in stone cultural heritage, such as pagodas and statues is very important to plan conservation and restoration. The ultrasonic measurement is one of commonly-used techniques to evaluate weathering index of stone cultual properties, since it is easy to use and non-destructive. Typically we use a portable ultrasonic device, PUNDIT with exponential sensors. However, there are many factors to cause errors in measurements such as operators, sensor layouts or measurement directions. In this study, we carried out variety of measurements with different operators (male and female), different sensor layouts (direct and indirect), and sensor directions (anisotropy). For operators bias, we found that there were not significant differences by the operator's sex, while the pressure an operator exerts can create larger error in measurements. Calibrating with a standard sample for each operator is very essential in this case. For the sensor layout, we found that the indirect measurement (commonly used for cultural properties, since the direct measurement is difficult in most cases) gives lower velocity than the real one. We found that the correction coefficient is slightly different for different types of rocks: 1.50 for granite and sandstone and 1.46 for marble. From the sensor directions, we found that many rocks have slight anisotropy in their ultrasonic velocity measurement, though they are considered isotropic in macroscopic scale. Thus averaging four different directional measurement (0°, 45°, 90°, 135°) gives much less errors in measurements (the variance is 2-3 times smaller). In conclusion, we reported the error in ultrasonic meaurement of stone cultural properties by various sources quantitatively and suggested the amount of correction and procedures to calibrate the measurements. Acknowledgement: This study, which forms a part of the project, has been achieved with the support of national R&D project, which has been hosted by
Trends and Correlation Estimation in Climate Sciences: Effects of Timescale Errors

Science.gov (United States)

Mudelsee, M.; Bermejo, M. A.; Bickert, T.; Chirila, D.; Fohlmeister, J.; Köhler, P.; Lohmann, G.; Olafsdottir, K.; Scholz, D.

2012-12-01

Trend describes time-dependence in the first moment of a stochastic process, and correlation measures the linear relation between two random variables. Accurately estimating the trend and correlation, including uncertainties, from climate time series data in the uni- and bivariate domain, respectively, allows first-order insights into the geophysical process that generated the data. Timescale errors, ubiquitious in paleoclimatology, where archives are sampled for proxy measurements and dated, poses a problem to the estimation. Statistical science and the various applied research fields, including geophysics, have almost completely ignored this problem due to its theoretical almost-intractability. However, computational adaptations or replacements of traditional error formulas have become technically feasible. This contribution gives a short overview of such an adaptation package, bootstrap resampling combined with parametric timescale simulation. We study linear regression, parametric change-point models and nonparametric smoothing for trend estimation. We introduce pairwise-moving block bootstrap resampling for correlation estimation. Both methods share robustness against autocorrelation and non-Gaussian distributional shape. We shortly touch computing-intensive calibration of bootstrap confidence intervals and consider options to parallelize the related computer code. Following examples serve not only to illustrate the methods but tell own climate stories: (1) the search for climate drivers of the Agulhas Current on recent timescales, (2) the comparison of three stalagmite-based proxy series of regional, western German climate over the later part of the Holocene, and (3) trends and transitions in benthic oxygen isotope time series from the Cenozoic. Financial support by Deutsche Forschungsgemeinschaft (FOR 668, FOR 1070, MU 1595/4-1) and the European Commission (MC ITN 238512, MC ITN 289447) is acknowledged.
Temperature and SAR measurement errors in the evaluation of metallic linear structures heating during MRI using fluoroptic (registered) probes

Energy Technology Data Exchange (ETDEWEB)

Mattei, E [Department of Technologies and Health, Italian National Institute of Health, Rome (Italy); Triventi, M [Department of Technologies and Health, Italian National Institute of Health, Rome (Italy); Calcagnini, G [Department of Technologies and Health, Italian National Institute of Health, Rome (Italy); Censi, F [Department of Technologies and Health, Italian National Institute of Health, Rome (Italy); Kainz, W [Center for Devices and Radiological Health, Food and Drug Administration, Rockville, MD (United States); Bassen, H I [Center for Devices and Radiological Health, Food and Drug Administration, Rockville, MD (United States); Bartolini, P [Department of Technologies and Health, Italian National Institute of Health, Rome (Italy)

2007-03-21

The purpose of this work is to evaluate the error associated with temperature and SAR measurements using fluoroptic (registered) temperature probes on pacemaker (PM) leads during magnetic resonance imaging (MRI). We performed temperature measurements on pacemaker leads, excited with a 25, 64, and 128 MHz current. The PM lead tip heating was measured with a fluoroptic (registered) thermometer (Luxtron, Model 3100, USA). Different contact configurations between the pigmented portion of the temperature probe and the PM lead tip were investigated to find the contact position minimizing the temperature and SAR underestimation. A computer model was used to estimate the error made by fluoroptic (registered) probes in temperature and SAR measurement. The transversal contact of the pigmented portion of the temperature probe and the PM lead tip minimizes the underestimation for temperature and SAR. This contact position also has the lowest temperature and SAR error. For other contact positions, the maximum temperature error can be as high as -45%, whereas the maximum SAR error can be as high as -54%. MRI heating evaluations with temperature probes should use a contact position minimizing the maximum error, need to be accompanied by a thorough uncertainty budget and the temperature and SAR errors should be specified.
Measurements on pointing error and field of view of Cimel-318 Sun photometers in the scope of AERONET

Directory of Open Access Journals (Sweden)

B. Torres

2013-08-01

Full Text Available Sensitivity studies indicate that among the diverse error sources of ground-based sky radiometer observations, the pointing error plays an important role in the correct retrieval of aerosol properties. The accurate pointing is specially critical for the characterization of desert dust aerosol. The present work relies on the analysis of two new measurement procedures (cross and matrix specifically designed for the evaluation of the pointing error in the standard instrument of the Aerosol Robotic Network (AERONET, the Cimel CE-318 Sun photometer. The first part of the analysis contains a preliminary study whose results conclude on the need of a Sun movement correction for an accurate evaluation of the pointing error from both new measurements. Once this correction is applied, both measurements show equivalent results with differences under 0.01° in the pointing error estimations. The second part of the analysis includes the incorporation of the cross procedure in the AERONET routine measurement protocol in order to monitor the pointing error in field instruments. The pointing error was evaluated using the data collected for more than a year, in 7 Sun photometers belonging to AERONET sites. The registered pointing error values were generally smaller than 0.1°, though in some instruments values up to 0.3° have been observed. Moreover, the pointing error analysis shows that this measurement can be useful to detect mechanical problems in the robots or dirtiness in the 4-quadrant detector used to track the Sun. Specifically, these mechanical faults can be detected due to the stable behavior of the values over time and vs. the solar zenith angle. Finally, the matrix procedure can be used to derive the value of the solid view angle of the instruments. The methodology has been implemented and applied for the characterization of 5 Sun photometers. To validate the method, a comparison with solid angles obtained from the vicarious calibration method was
Estimation of Dynamic Errors in Laser Optoelectronic Dimension Gauges for Geometric Measurement of Details

Directory of Open Access Journals (Sweden)

Khasanov Zimfir

2018-01-01

Full Text Available The article reviews the capabilities and particularities of the approach to the improvement of metrological characteristics of fiber-optic pressure sensors (FOPS based on estimation estimation of dynamic errors in laser optoelectronic dimension gauges for geometric measurement of details. It is shown that the proposed criteria render new methods for conjugation of optoelectronic converters in the dimension gauge for geometric measurements in order to reduce the speed and volume requirements for the Random Access Memory (RAM of the video controller which process the signal. It is found that the lower relative error, the higher the interrogetion speed of the CCD array. It is shown that thus, the maximum achievable dynamic accuracy characteristics of the optoelectronic gauge are determined by the following conditions: the parameter stability of the electronic circuits in the CCD array and the microprocessor calculator; linearity of characteristics; error dynamics and noise in all electronic circuits of the CCD array and microprocessor calculator.
Generalized Gaussian Error Calculus

CERN Document Server

Grabe, Michael

2010-01-01

For the first time in 200 years Generalized Gaussian Error Calculus addresses a rigorous, complete and self-consistent revision of the Gaussian error calculus. Since experimentalists realized that measurements in general are burdened by unknown systematic errors, the classical, widespread used evaluation procedures scrutinizing the consequences of random errors alone turned out to be obsolete. As a matter of course, the error calculus to-be, treating random and unknown systematic errors side by side, should ensure the consistency and traceability of physical units, physical constants and physical quantities at large. The generalized Gaussian error calculus considers unknown systematic errors to spawn biased estimators. Beyond, random errors are asked to conform to the idea of what the author calls well-defined measuring conditions. The approach features the properties of a building kit: any overall uncertainty turns out to be the sum of a contribution due to random errors, to be taken from a confidence inter...
Measurement error of a simplified protocol for quantitative sensory tests in chronic pain patients

DEFF Research Database (Denmark)

Müller, Monika; Biurrun Manresa, José; Limacher, Andreas

2017-01-01

BACKGROUND AND OBJECTIVES: Large-scale application of Quantitative Sensory Tests (QST) is impaired by lacking standardized testing protocols. One unclear methodological aspect is the number of records needed to minimize measurement error. Traditionally, measurements are repeated 3 to 5 times...
Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

DEFF Research Database (Denmark)

Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L

2017-01-01

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone...... as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total...
Multiobjective optimization framework for landmark measurement error correction in three-dimensional cephalometric tomography.

Science.gov (United States)

DeCesare, A; Secanell, M; Lagravère, M O; Carey, J

2013-01-01

The purpose of this study is to minimize errors that occur when using a four vs six landmark superimpositioning method in the cranial base to define the co-ordinate system. Cone beam CT volumetric data from ten patients were used for this study. Co-ordinate system transformations were performed. A co-ordinate system was constructed using two planes defined by four anatomical landmarks located by an orthodontist. A second co-ordinate system was constructed using four anatomical landmarks that are corrected using a numerical optimization algorithm for any landmark location operator error using information from six landmarks. The optimization algorithm minimizes the relative distance and angle between the known fixed points in the two images to find the correction. Measurement errors and co-ordinates in all axes were obtained for each co-ordinate system. Significant improvement is observed after using the landmark correction algorithm to position the final co-ordinate system. The errors found in a previous study are significantly reduced. Errors found were between 1 mm and 2 mm. When analysing real patient data, it was found that the 6-point correction algorithm reduced errors between images and increased intrapoint reliability. A novel method of optimizing the overlay of three-dimensional images using a 6-point correction algorithm was introduced and examined. This method demonstrated greater reliability and reproducibility than the previous 4-point correction algorithm.
Active and passive compensation of APPLE II-introduced multipole errors through beam-based measurement

Energy Technology Data Exchange (ETDEWEB)

Chung, Ting-Yi; Huang, Szu-Jung; Fu, Huang-Wen; Chang, Ho-Ping; Chang, Cheng-Hsiang [National Synchrotron Radiation Research Center, Hsinchu Science Park, Hsinchu 30076, Taiwan (China); Hwang, Ching-Shiang [National Synchrotron Radiation Research Center, Hsinchu Science Park, Hsinchu 30076, Taiwan (China); Department of Electrophysics, National Chiao Tung University, Hsinchu 30050, Taiwan (China)

2016-08-01

The effect of an APPLE II-type elliptically polarized undulator (EPU) on the beam dynamics were investigated using active and passive methods. To reduce the tune shift and improve the injection efficiency, dynamic multipole errors were compensated using L-shaped iron shims, which resulted in stable top-up operation for a minimum gap. The skew quadrupole error was compensated using a multipole corrector, which was located downstream of the EPU for minimizing betatron coupling, and it ensured the enhancement of the synchrotron radiation brightness. The investigation methods, a numerical simulation algorithm, a multipole error correction method, and the beam-based measurement results are discussed.
Estimation methods with ordered exposure subject to measurement error and missingness in semi-ecological design

Directory of Open Access Journals (Sweden)

Kim Hyang-Mi

2012-09-01

Full Text Available Abstract Background In epidemiological studies, it is often not possible to measure accurately exposures of participants even if their response variable can be measured without error. When there are several groups of subjects, occupational epidemiologists employ group-based strategy (GBS for exposure assessment to reduce bias due to measurement errors: individuals of a group/job within study sample are assigned commonly to the sample mean of exposure measurements from their group in evaluating the effect of exposure on the response. Therefore, exposure is estimated on an ecological level while health outcomes are ascertained for each subject. Such study design leads to negligible bias in risk estimates when group means are estimated from ‘large’ samples. However, in many cases, only a small number of observations are available to estimate the group means, and this causes bias in the observed exposure-disease association. Also, the analysis in a semi-ecological design may involve exposure data with the majority missing and the rest observed with measurement errors and complete response data collected with ascertainment. Methods In workplaces groups/jobs are naturally ordered and this could be incorporated in estimation procedure by constrained estimation methods together with the expectation and maximization (EM algorithms for regression models having measurement error and missing values. Four methods were compared by a simulation study: naive complete-case analysis, GBS, the constrained GBS (CGBS, and the constrained expectation and maximization (CEM. We illustrated the methods in the analysis of decline in lung function due to exposures to carbon black. Results Naive and GBS approaches were shown to be inadequate when the number of exposure measurements is too small to accurately estimate group means. The CEM method appears to be best among them when within each exposure group at least a ’moderate’ number of individuals have their
Self-reported medical, medication and laboratory error in eight countries: risk factors for chronically ill adults.

Science.gov (United States)

Scobie, Andrea

2011-04-01

To identify risk factors associated with self-reported medical, medication and laboratory error in eight countries. The Commonwealth Fund's 2008 International Health Policy Survey of chronically ill patients in eight countries. None. A multi-country telephone survey was conducted between 3 March and 30 May 2008 with patients in Australia, Canada, France, Germany, the Netherlands, New Zealand, the UK and the USA who self-reported being chronically ill. A bivariate analysis was performed to determine significant explanatory variables of medical, medication and laboratory error (P error: age 65 and under, education level of some college or less, presence of two or more chronic conditions, high prescription drug use (four+ drugs), four or more doctors seen within 2 years, a care coordination problem, poor doctor-patient communication and use of an emergency department. Risk factors with the greatest ability to predict experiencing an error encompassed issues with coordination of care and provider knowledge of a patient's medical history. The identification of these risk factors could help policymakers and organizations to proactively reduce the likelihood of error through greater examination of system- and organization-level practices.
Three-dimensional patient setup errors at different treatment sites measured by the Tomotherapy megavoltage CT

Energy Technology Data Exchange (ETDEWEB)

Hui, S.K.; Lusczek, E.; Dusenbery, K. [Univ. of Minnesota Medical School, Minneapolis, MN (United States). Dept. of Therapeutic Radiology - Radiation Oncology; DeFor, T. [Univ. of Minnesota Medical School, Minneapolis, MN (United States). Biostatistics and Informatics Core; Levitt, S. [Univ. of Minnesota Medical School, Minneapolis, MN (United States). Dept. of Therapeutic Radiology - Radiation Oncology; Karolinska Institutet, Stockholm (Sweden). Dept. of Onkol-Patol

2012-04-15

Reduction of interfraction setup uncertainty is vital for assuring the accuracy of conformal radiotherapy. We report a systematic study of setup error to assess patients' three-dimensional (3D) localization at various treatment sites. Tomotherapy megavoltage CT (MVCT) images were scanned daily in 259 patients from 2005-2008. We analyzed 6,465 MVCT images to measure setup error for head and neck (H and N), chest/thorax, abdomen, prostate, legs, and total marrow irradiation (TMI). Statistical comparisons of the absolute displacements across sites and time were performed in rotation (R), lateral (x), craniocaudal (y), and vertical (z) directions. The global systematic errors were measured to be less than 3 mm in each direction with increasing order of errors for different sites: H and N, prostate, chest, pelvis, spine, legs, and TMI. The differences in displacements in the x, y, and z directions, and 3D average displacement between treatment sites were significant (p < 0.01). Overall improvement in patient localization with time (after 3-4 treatment fractions) was observed. Large displacement (> 5 mm) was observed in the 75{sup th} percentile of the patient groups for chest, pelvis, legs, and spine in the x and y direction in the second week of the treatment. MVCT imaging is essential for determining 3D setup error and to reduce uncertainty in localization at all anatomical locations. Setup error evaluation should be performed daily for all treatment regions, preferably for all treatment fractions. (orig.)
Measurement errors for thermocouples attached to thin plates

International Nuclear Information System (INIS)

Sobolik, K.B.; Keltner, N.R.; Beck, J.V.

1989-01-01

This paper discusses Unsteady Surface Element (USE) methods which are applied to a model of a thermocouple wire attached to a thin disk. Green's functions are used to develop the integral equations for the wire and the disk. The model can be used to evaluate transient and steady state responses for many types of heat flux measurement devices including thin skin calorimeters and circular foil (Gardon) head flux gauges. The model can accommodate either surface or volumetric heating of the disk. The boundary condition at the outer radius of the disk can be either insulated or constant temperature. Effect on the errors of geometrical and thermal factors can be assessed. Examples are given
Transparency When Things Go Wrong: Physician Attitudes About Reporting Medical Errors to Patients, Peers, and Institutions.

Science.gov (United States)

Bell, Sigall K; White, Andrew A; Yi, Jean C; Yi-Frazier, Joyce P; Gallagher, Thomas H

2017-12-01

Transparent communication after medical error includes disclosing the mistake to the patient, discussing the event with colleagues, and reporting to the institution. Little is known about whether attitudes about these transparency practices are related. Understanding these relationships could inform educational and organizational strategies to promote transparency. We analyzed responses of 3038 US and Canadian physicians to a medical error communication survey. We used bivariate correlations, principal components analysis, and linear regression to determine whether and how physician attitudes about transparent communication with patients, peers, and the institution after error were related. Physician attitudes about disclosing errors to patients, peers, and institutions were correlated (all P's transparent communication with patients and peers/institution included female sex, US (vs Canadian) doctors, academic (vs private) practice, the belief that disclosure decreased likelihood of litigation, and the belief that system changes occur after error reporting. In addition, younger physicians, surgeons, and those with previous experience disclosing a serious error were more likely to agree with disclosure to patients. In comparison, doctors who believed that disclosure would decrease patient trust were less likely to agree with error disclosure to patients. Previous disclosure education was associated with attitudes supporting greater transparency with peers/institution. Physician attitudes about discussing errors with patients, colleagues, and institutions are related. Several predictors of transparency affect all 3 practices and are potentially modifiable by educational and institutional strategies.

Computational approach to Thornley's problem by bivariate operational calculus

Science.gov (United States)

Bazhlekova, E.; Dimovski, I.

2012-10-01

Thornley's problem is an initial-boundary value problem with a nonlocal boundary condition for linear onedimensional reaction-diffusion equation, used as a mathematical model of spiral phyllotaxis in botany. Applying a bivariate operational calculus we find explicit representation of the solution, containing two convolution products of special solutions and the arbitrary initial and boundary functions. We use a non-classical convolution with respect to the space variable, extending in this way the classical Duhamel principle. The special solutions involved are represented in the form of fast convergent series. Numerical examples are considered to show the application of the present technique and to analyze the character of the solution.
Aerogel Antennas Communications Study Using Error Vector Magnitude Measurements

Science.gov (United States)

Miranda, Felix A.; Mueller, Carl H.; Meador, Mary Ann B.

2014-01-01

This presentation discusses an aerogel antennas communication study using error vector magnitude (EVM) measurements. The study was performed using 2x4 element polyimide (PI) aerogel-based phased arrays designed for operation at 5 GHz as transmit (Tx) and receive (Rx) antennas separated by a line of sight (LOS) distance of 8.5 meters. The results of the EVM measurements demonstrate that polyimide aerogel antennas work appropriately to support digital communication links with typically used modulation schemes such as QPSK and 4 DQPSK. As such, PI aerogel antennas with higher gain, larger bandwidth and lower mass than typically used microwave laminates could be suitable to enable aerospace-to- ground communication links with enough channel capacity to support voice, data and video links from CubeSats, unmanned air vehicles (UAV), and commercial aircraft.
Aerogel Antennas Communications Study Using Error Vector Magnitude Measurements

Science.gov (United States)

Miranda, Felix A.; Mueller, Carl H.; Meador, Mary Ann B.

2014-01-01

This paper discusses an aerogel antennas communication study using error vector magnitude (EVM) measurements. The study was performed using 4x2 element polyimide (PI) aerogel-based phased arrays designed for operation at 5 GHz as transmit (Tx) and receive (Rx) antennas separated by a line of sight (LOS) distance of 8.5 meters. The results of the EVM measurements demonstrate that polyimide aerogel antennas work appropriately to support digital communication links with typically used modulation schemes such as QPSK and pi/4 DQPSK. As such, PI aerogel antennas with higher gain, larger bandwidth and lower mass than typically used microwave laminates could be suitable to enable aerospace-to-ground communication links with enough channel capacity to support voice, data and video links from cubesats, unmanned air vehicles (UAV), and commercial aircraft.
Semiparametric Bayesian Analysis of Nutritional Epidemiology Data in the Presence of Measurement Error

KAUST Repository

Sinha, Samiran; Mallick, Bani K.; Kipnis, Victor; Carroll, Raymond J.

2009-01-01

We propose a semiparametric Bayesian method for handling measurement error in nutritional epidemiological data. Our goal is to estimate nonparametrically the form of association between a disease and exposure variable while the true values
Carbon and oxygen isotopic ratio bi-variate distribution for marble artifacts quarry assignment

International Nuclear Information System (INIS)

Pentia, M.

1995-01-01

Statistical description, by a Gaussian bi-variate probability distribution of 13 C/ 12 C and 18 O/ 16 O isotopic ratios in the ancient marble quarries has been done and the new method for obtaining the confidence level quarry assignment for marble artifacts has been presented. (author) 8 figs., 3 tabs., 4 refs
PRECISION MEASUREMENTS OF THE CLUSTER RED SEQUENCE USING AN ERROR-CORRECTED GAUSSIAN MIXTURE MODEL

International Nuclear Information System (INIS)

Hao Jiangang; Annis, James; Koester, Benjamin P.; Mckay, Timothy A.; Evrard, August; Gerdes, David; Rykoff, Eli S.; Rozo, Eduardo; Becker, Matthew; Busha, Michael; Wechsler, Risa H.; Johnston, David E.; Sheldon, Erin

2009-01-01

The red sequence is an important feature of galaxy clusters and plays a crucial role in optical cluster detection. Measurement of the slope and scatter of the red sequence are affected both by selection of red sequence galaxies and measurement errors. In this paper, we describe a new error-corrected Gaussian Mixture Model for red sequence galaxy identification. Using this technique, we can remove the effects of measurement error and extract unbiased information about the intrinsic properties of the red sequence. We use this method to select red sequence galaxies in each of the 13,823 clusters in the maxBCG catalog, and measure the red sequence ridgeline location and scatter of each. These measurements provide precise constraints on the variation of the average red galaxy populations in the observed frame with redshift. We find that the scatter of the red sequence ridgeline increases mildly with redshift, and that the slope decreases with redshift. We also observe that the slope does not strongly depend on cluster richness. Using similar methods, we show that this behavior is mirrored in a spectroscopic sample of field galaxies, further emphasizing that ridgeline properties are independent of environment. These precise measurements serve as an important observational check on simulations and mock galaxy catalogs. The observed trends in the slope and scatter of the red sequence ridgeline with redshift are clues to possible intrinsic evolution of the cluster red sequence itself. Most importantly, the methods presented in this work lay the groundwork for further improvements in optically based cluster cosmology.
Precision Measurements of the Cluster Red Sequence using an Error Corrected Gaussian Mixture Model

Energy Technology Data Exchange (ETDEWEB)

Hao, Jiangang; /Fermilab /Michigan U.; Koester, Benjamin P.; /Chicago U.; Mckay, Timothy A.; /Michigan U.; Rykoff, Eli S.; /UC, Santa Barbara; Rozo, Eduardo; /Ohio State U.; Evrard, August; /Michigan U.; Annis, James; /Fermilab; Becker, Matthew; /Chicago U.; Busha, Michael; /KIPAC, Menlo Park /SLAC; Gerdes, David; /Michigan U.; Johnston, David E.; /Northwestern U. /Brookhaven

2009-07-01

The red sequence is an important feature of galaxy clusters and plays a crucial role in optical cluster detection. Measurement of the slope and scatter of the red sequence are affected both by selection of red sequence galaxies and measurement errors. In this paper, we describe a new error corrected Gaussian Mixture Model for red sequence galaxy identification. Using this technique, we can remove the effects of measurement error and extract unbiased information about the intrinsic properties of the red sequence. We use this method to select red sequence galaxies in each of the 13,823 clusters in the maxBCG catalog, and measure the red sequence ridgeline location and scatter of each. These measurements provide precise constraints on the variation of the average red galaxy populations in the observed frame with redshift. We find that the scatter of the red sequence ridgeline increases mildly with redshift, and that the slope decreases with redshift. We also observe that the slope does not strongly depend on cluster richness. Using similar methods, we show that this behavior is mirrored in a spectroscopic sample of field galaxies, further emphasizing that ridgeline properties are independent of environment. These precise measurements serve as an important observational check on simulations and mock galaxy catalogs. The observed trends in the slope and scatter of the red sequence ridgeline with redshift are clues to possible intrinsic evolution of the cluster red-sequence itself. Most importantly, the methods presented in this work lay the groundwork for further improvements in optically-based cluster cosmology.
Simulation study on heterogeneous variance adjustment for observations with different measurement error variance

DEFF Research Database (Denmark)

Pitkänen, Timo; Mäntysaari, Esa A; Nielsen, Ulrik Sander

2013-01-01

of variance correction is developed for the same observations. As automated milking systems are becoming more popular the current evaluation model needs to be enhanced to account for the different measurement error variances of observations from automated milking systems. In this simulation study different...... models and different approaches to account for heterogeneous variance when observations have different measurement error variances were investigated. Based on the results we propose to upgrade the currently applied models and to calibrate the heterogeneous variance adjustment method to yield same genetic......The Nordic Holstein yield evaluation model describes all available milk, protein and fat test-day yields from Denmark, Finland and Sweden. In its current form all variance components are estimated from observations recorded under conventional milking systems. Also the model for heterogeneity...
Effects of holding time and measurement error on culturing Legionella in environmental water samples.

Science.gov (United States)

Flanders, W Dana; Kirkland, Kimberly H; Shelton, Brian G

2014-10-01

Outbreaks of Legionnaires' disease require environmental testing of water samples from potentially implicated building water systems to identify the source of exposure. A previous study reports a large impact on Legionella sample results due to shipping and delays in sample processing. Specifically, this same study, without accounting for measurement error, reports more than half of shipped samples tested had Legionella levels that arbitrarily changed up or down by one or more logs, and the authors attribute this result to shipping time. Accordingly, we conducted a study to determine the effects of sample holding/shipping time on Legionella sample results while taking into account measurement error, which has previously not been addressed. We analyzed 159 samples, each split into 16 aliquots, of which one-half (8) were processed promptly after collection. The remaining half (8) were processed the following day to assess impact of holding/shipping time. A total of 2544 samples were analyzed including replicates. After accounting for inherent measurement error, we found that the effect of holding time on observed Legionella counts was small and should have no practical impact on interpretation of results. Holding samples increased the root mean squared error by only about 3-8%. Notably, for only one of 159 samples, did the average of the 8 replicate counts change by 1 log. Thus, our findings do not support the hypothesis of frequent, significant (≥= 1 log10 unit) Legionella colony count changes due to holding. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
Bias Correction and Random Error Characterization for the Assimilation of HRDI Line-of-Sight Wind Measurements

Science.gov (United States)

Tangborn, Andrew; Menard, Richard; Ortland, David; Einaudi, Franco (Technical Monitor)

2001-01-01

A new approach to the analysis of systematic and random observation errors is presented in which the error statistics are obtained using forecast data rather than observations from a different instrument type. The analysis is carried out at an intermediate retrieval level, instead of the more typical state variable space. This method is carried out on measurements made by the High Resolution Doppler Imager (HRDI) on board the Upper Atmosphere Research Satellite (UARS). HRDI, a limb sounder, is the only satellite instrument measuring winds in the stratosphere, and the only instrument of any kind making global wind measurements in the upper atmosphere. HRDI measures doppler shifts in the two different O2 absorption bands (alpha and B) and the retrieved products are tangent point Line-of-Sight wind component (level 2 retrieval) and UV winds (level 3 retrieval). This analysis is carried out on a level 1.9 retrieval, in which the contributions from different points along the line-of-sight have not been removed. Biases are calculated from O-F (observed minus forecast) LOS wind components and are separated into a measurement parameter space consisting of 16 different values. The bias dependence on these parameters (plus an altitude dependence) is used to create a bias correction scheme carried out on the level 1.9 retrieval. The random error component is analyzed by separating the gamma and B band observations and locating observation pairs where both bands are very nearly looking at the same location at the same time. It is shown that the two observation streams are uncorrelated and that this allows the forecast error variance to be estimated. The bias correction is found to cut the effective observation error variance in half.
A comparison of least squares linear regression and measurement error modeling of warm/cold multipole correlation in SSC prototype dipole magnets

International Nuclear Information System (INIS)

Pollock, D.; Kim, K.; Gunst, R.; Schucany, W.

1993-05-01

Linear estimation of cold magnetic field quality based on warm multipole measurements is being considered as a quality control method for SSC production magnet acceptance. To investigate prediction uncertainties associated with such an approach, axial-scan (Z-scan) magnetic measurements from SSC Prototype Collider Dipole Magnets (CDM's) have been studied. This paper presents a preliminary evaluation of the explanatory ability of warm measurement multipole variation on the prediction of cold magnet multipoles. Two linear estimation methods are presented: least-squares regression, which uses the assumption of fixed independent variable (xi) observations, and the measurement error model, which includes measurement error in the xi's. The influence of warm multipole measurement errors on predicted cold magnet multipole averages is considered. MSD QA is studying warm/cold correlation to answer several magnet quality control questions. How well do warm measurements predict cold (2kA) multipoles? Does sampling error significantly influence estimates of the linear coefficients (slope, intercept and residual standard error)? Is estimation error for the predicted cold magnet average small compared to typical variation along the Z-Axis? What fraction of the multipole RMS tolerance is accounted for by individual magnet prediction uncertainty?
Effects of Measurement Error on the Output Gap in Japan

OpenAIRE

Koichiro Kamada; Kazuto Masuda

2000-01-01

Potential output is the largest amount of products that can be produced by fully utilizing available labor and capital stock; the output gap is defined as the discrepancy between actual and potential output. If data on production factors contain measurement errors, total factor productivity (TFP) cannot be estimated accurately from the Solow residual(i.e., the portion of output that is not attributable to labor and capital inputs). This may give rise to distortions in the estimation of potent...
Implementation and verification of a four-probe motion error measurement system for a large-scale roll lathe used in hybrid manufacturing

International Nuclear Information System (INIS)

Chen, Yuan-Liu; Niu, Zengyuan; Matsuura, Daiki; Lee, Jung Chul; Shimizu, Yuki; Gao, Wei; Oh, Jeong Seok; Park, Chun Hong

2017-01-01

In this paper, a four-probe measurement system is implemented and verified for the carriage slide motion error measurement of a large-scale roll lathe used in hybrid manufacturing where a laser machining probe and a diamond cutting tool are placed on two sides of a roll workpiece for manufacturing. The motion error of the carriage slide of the roll lathe is composed of two straightness motion error components and two parallelism motion error components in the vertical and horizontal planes. Four displacement measurement probes, which are mounted on the carriage slide with respect to four opposing sides of the roll workpiece, are employed for the measurement. Firstly, based on the reversal technique, the four probes are moved by the carriage slide to scan the roll workpiece before and after a 180-degree rotation of the roll workpiece. Taking into consideration the fact that the machining accuracy of the lathe is influenced by not only the carriage slide motion error but also the gravity deformation of the large-scale roll workpiece due to its heavy weight, the vertical motion error is thus characterized relating to the deformed axis of the roll workpiece. The horizontal straightness motion error can also be synchronously obtained based on the reversal technique. In addition, based on an error separation algorithm, the vertical and horizontal parallelism motion error components are identified by scanning the rotating roll workpiece at the start and the end positions of the carriage slide, respectively. The feasibility and reliability of the proposed motion error measurement system are demonstrated by the experimental results and the measurement uncertainty analysis. (paper)
Implementation and verification of a four-probe motion error measurement system for a large-scale roll lathe used in hybrid manufacturing

Science.gov (United States)

Chen, Yuan-Liu; Niu, Zengyuan; Matsuura, Daiki; Lee, Jung Chul; Shimizu, Yuki; Gao, Wei; Oh, Jeong Seok; Park, Chun Hong

2017-10-01

In this paper, a four-probe measurement system is implemented and verified for the carriage slide motion error measurement of a large-scale roll lathe used in hybrid manufacturing where a laser machining probe and a diamond cutting tool are placed on two sides of a roll workpiece for manufacturing. The motion error of the carriage slide of the roll lathe is composed of two straightness motion error components and two parallelism motion error components in the vertical and horizontal planes. Four displacement measurement probes, which are mounted on the carriage slide with respect to four opposing sides of the roll workpiece, are employed for the measurement. Firstly, based on the reversal technique, the four probes are moved by the carriage slide to scan the roll workpiece before and after a 180-degree rotation of the roll workpiece. Taking into consideration the fact that the machining accuracy of the lathe is influenced by not only the carriage slide motion error but also the gravity deformation of the large-scale roll workpiece due to its heavy weight, the vertical motion error is thus characterized relating to the deformed axis of the roll workpiece. The horizontal straightness motion error can also be synchronously obtained based on the reversal technique. In addition, based on an error separation algorithm, the vertical and horizontal parallelism motion error components are identified by scanning the rotating roll workpiece at the start and the end positions of the carriage slide, respectively. The feasibility and reliability of the proposed motion error measurement system are demonstrated by the experimental results and the measurement uncertainty analysis.
Analysis of influence on back-EMF based sensorless control of PMSM due to parameter variations and measurement errors

DEFF Research Database (Denmark)

Wang, Z.; Lu, K.; Ye, Y.

2011-01-01

To achieve better performance of sensorless control of PMSM, a precise and stable estimation of rotor position and speed is required. Several parameter uncertainties and variable measurement errors may lead to estimation error, such as resistance and inductance variations due to temperature...... and flux saturation, current and voltage errors due to measurement uncertainties, and signal delay caused by hardwares. This paper reveals some inherent principles for the performance of the back-EMF based sensorless algorithm embedded in a surface mounted PMSM system adapting vector control strategy...
Some effects of random dose measurement errors on analysis of atomic bomb survivor data

International Nuclear Information System (INIS)

Gilbert, E.S.

1985-01-01

The effects of random dose measurement errors on analyses of atomic bomb survivor data are described and quantified for several procedures. It is found that the ways in which measurement error is most likely to mislead are through downward bias in the estimated regression coefficients and through distortion of the shape of the dose-response curve. The magnitude of the bias with simple linear regression is evaluated for several dose treatments including the use of grouped and ungrouped data, analyses with and without truncation at 600 rad, and analyses which exclude doses exceeding 200 rad. Limited calculations have also been made for maximum likelihood estimation based on Poisson regression. 16 refs., 6 tabs
Meta-analysis for diagnostic accuracy studies: a new statistical model using beta-binomial distributions and bivariate copulas.

Science.gov (United States)

Kuss, Oliver; Hoyer, Annika; Solms, Alexander

2014-01-15

There are still challenges when meta-analyzing data from studies on diagnostic accuracy. This is mainly due to the bivariate nature of the response where information on sensitivity and specificity must be summarized while accounting for their correlation within a single trial. In this paper, we propose a new statistical model for the meta-analysis for diagnostic accuracy studies. This model uses beta-binomial distributions for the marginal numbers of true positives and true negatives and links these margins by a bivariate copula distribution. The new model comes with all the features of the current standard model, a bivariate logistic regression model with random effects, but has the additional advantages of a closed likelihood function and a larger flexibility for the correlation structure of sensitivity and specificity. In a simulation study, which compares three copula models and two implementations of the standard model, the Plackett and the Gauss copula do rarely perform worse but frequently better than the standard model. We use an example from a meta-analysis to judge the diagnostic accuracy of telomerase (a urinary tumor marker) for the diagnosis of primary bladder cancer for illustration. Copyright © 2013 John Wiley & Sons, Ltd.
A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers.

Science.gov (United States)

Ji, Fei; Lee, Dayoung; Mendell, Nancy Role

2005-12-30

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait.
Probabilistic modeling using bivariate normal distributions for identification of flow and displacement intervals in longwall overburden

Energy Technology Data Exchange (ETDEWEB)

Karacan, C.O.; Goodman, G.V.R. [NIOSH, Pittsburgh, PA (United States). Off Mine Safety & Health Research

2011-01-15

Gob gas ventholes (GGV) are used to control methane emissions in longwall mines by capturing it within the overlying fractured strata before it enters the work environment. In order for GGVs to effectively capture more methane and less mine air, the length of the slotted sections and their proximity to top of the coal bed should be designed based on the potential gas sources and their locations, as well as the displacements in the overburden that will create potential flow paths for the gas. In this paper, an approach to determine the conditional probabilities of depth-displacement, depth-flow percentage, depth-formation and depth-gas content of the formations was developed using bivariate normal distributions. The flow percentage, displacement and formation data as a function of distance from coal bed used in this study were obtained from a series of borehole experiments contracted by the former US Bureau of Mines as part of a research project. Each of these parameters was tested for normality and was modeled using bivariate normal distributions to determine all tail probabilities. In addition, the probability of coal bed gas content as a function of depth was determined using the same techniques. The tail probabilities at various depths were used to calculate conditional probabilities for each of the parameters. The conditional probabilities predicted for various values of the critical parameters can be used with the measurements of flow and methane percentage at gob gas ventholes to optimize their performance.
A non-stationary cost-benefit based bivariate extreme flood estimation approach

Science.gov (United States)

Qi, Wei; Liu, Junguo

2018-02-01

Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.

Reduction of determinate errors in mass bias-corrected isotope ratios measured using a multi-collector plasma mass spectrometer

International Nuclear Information System (INIS)

Doherty, W.

2015-01-01

A nebulizer-centric instrument response function model of the plasma mass spectrometer was combined with a signal drift model, and the result was used to identify the causes of the non-spectroscopic determinate errors remaining in mass bias-corrected Pb isotope ratios (Tl as internal standard) measured using a multi-collector plasma mass spectrometer. Model calculations, confirmed by measurement, show that the detectable time-dependent errors are a result of the combined effect of signal drift and differences in the coordinates of the Pb and Tl response function maxima (horizontal offset effect). If there are no horizontal offsets, then the mass bias-corrected isotope ratios are approximately constant in time. In the absence of signal drift, the response surface curvature and horizontal offset effects are responsible for proportional errors in the mass bias-corrected isotope ratios. The proportional errors will be different for different analyte isotope ratios and different at every instrument operating point. Consequently, mass bias coefficients calculated using different isotope ratios are not necessarily equal. The error analysis based on the combined model provides strong justification for recommending a three step correction procedure (mass bias correction, drift correction and a proportional error correction, in that order) for isotope ratio measurements using a multi-collector plasma mass spectrometer
Total error vs. measurement uncertainty: revolution or evolution?

Science.gov (United States)

Oosterhuis, Wytze P; Theodorsson, Elvar

2016-02-01

The first strategic EFLM conference "Defining analytical performance goals, 15 years after the Stockholm Conference" was held in the autumn of 2014 in Milan. It maintained the Stockholm 1999 hierarchy of performance goals but rearranged them and established five task and finish groups to work on topics related to analytical performance goals including one on the "total error" theory. Jim Westgard recently wrote a comprehensive overview of performance goals and of the total error theory critical of the results and intentions of the Milan 2014 conference. The "total error" theory originated by Jim Westgard and co-workers has a dominating influence on the theory and practice of clinical chemistry but is not accepted in other fields of metrology. The generally accepted uncertainty theory, however, suffers from complex mathematics and conceived impracticability in clinical chemistry. The pros and cons of the total error theory need to be debated, making way for methods that can incorporate all relevant causes of uncertainty when making medical diagnoses and monitoring treatment effects. This development should preferably proceed not as a revolution but as an evolution.
Measurement-device-independent quantum key distribution with correlated source-light-intensity errors

Science.gov (United States)

Jiang, Cong; Yu, Zong-Wen; Wang, Xiang-Bin

2018-04-01

We present an analysis for measurement-device-independent quantum key distribution with correlated source-light-intensity errors. Numerical results show that the results here can greatly improve the key rate especially with large intensity fluctuations and channel attenuation compared with prior results if the intensity fluctuations of different sources are correlated.
Bivariate return periods of temperature and precipitation explain a large fraction of European crop yields

Science.gov (United States)

Zscheischler, Jakob; Orth, Rene; Seneviratne, Sonia I.

2017-07-01

Crops are vital for human society. Crop yields vary with climate and it is important to understand how climate and crop yields are linked to ensure future food security. Temperature and precipitation are among the key driving factors of crop yield variability. Previous studies have investigated mostly linear relationships between temperature and precipitation and crop yield variability. Other research has highlighted the adverse impacts of climate extremes, such as drought and heat waves, on crop yields. Impacts are, however, often non-linearly related to multivariate climate conditions. Here we derive bivariate return periods of climate conditions as indicators for climate variability along different temperature-precipitation gradients. We show that in Europe, linear models based on bivariate return periods of specific climate conditions explain on average significantly more crop yield variability (42 %) than models relying directly on temperature and precipitation as predictors (36 %). Our results demonstrate that most often crop yields increase along a gradient from hot and dry to cold and wet conditions, with lower yields associated with hot and dry periods. The majority of crops are most sensitive to climate conditions in summer and to maximum temperatures. The use of bivariate return periods allows the integration of non-linear impacts into climate-crop yield analysis. This offers new avenues to study the link between climate and crop yield variability and suggests that they are possibly more strongly related than what is inferred from conventional linear models.
Accounting for response misclassification and covariate measurement error improves power and reduces bias in epidemiologic studies.

Science.gov (United States)

Cheng, Dunlei; Branscum, Adam J; Stamey, James D

2010-07-01

To quantify the impact of ignoring misclassification of a response variable and measurement error in a covariate on statistical power, and to develop software for sample size and power analysis that accounts for these flaws in epidemiologic data. A Monte Carlo simulation-based procedure is developed to illustrate the differences in design requirements and inferences between analytic methods that properly account for misclassification and measurement error to those that do not in regression models for cross-sectional and cohort data. We found that failure to account for these flaws in epidemiologic data can lead to a substantial reduction in statistical power, over 25% in some cases. The proposed method substantially reduced bias by up to a ten-fold margin compared to naive estimates obtained by ignoring misclassification and mismeasurement. We recommend as routine practice that researchers account for errors in measurement of both response and covariate data when determining sample size, performing power calculations, or analyzing data from epidemiological studies. 2010 Elsevier Inc. All rights reserved.
A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models.

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Dionisio, Kathie L; Chang, Howard H; Baxter, Lisa K

2016-11-25

Exposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of air pollution and health. ZIP-code level estimates of exposure for six pollutants (CO, NO x , EC, PM 2.5 , SO 4 , O 3 ) from 1999 to 2002 in the Atlanta metropolitan area were used to calculate spatial, population (i.e. ambient versus personal), and total exposure measurement error. Empirically determined covariance of pollutant concentration pairs and the associated measurement errors were used to simulate true exposure (exposure without error) from observed exposure. Daily emergency department visits for respiratory diseases were simulated using a Poisson time-series model with a main pollutant RR = 1.05 per interquartile range, and a null association for the copollutant (RR = 1). Monte Carlo experiments were used to evaluate the impacts of correlated exposure errors of different copollutant pairs. Substantial attenuation of RRs due to exposure error was evident in nearly all copollutant pairs studied, ranging from 10 to 40% attenuation for spatial error, 3-85% for population error, and 31-85% for total error. When CO, NO x or EC is the main pollutant, we demonstrated the possibility of false positives, specifically identifying significant, positive associations for copollutants based on the estimated type I error rate. The impact of exposure error must be considered when interpreting results of copollutant epidemiologic models, due to the possibility of attenuation of main pollutant RRs and the increased probability of false positives when measurement error is present.
Random and Systematic Errors Share in Total Error of Probes for CNC Machine Tools

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Adam Wozniak

2018-03-01

Full Text Available Probes for CNC machine tools, as every measurement device, have accuracy limited by random errors and by systematic errors. Random errors of these probes are described by a parameter called unidirectional repeatability. Manufacturers of probes for CNC machine tools usually specify only this parameter, while parameters describing systematic errors of the probes, such as pre-travel variation or triggering radius variation, are used rarely. Systematic errors of the probes, linked to the differences in pre-travel values for different measurement directions, can be corrected or compensated, but it is not a widely used procedure. In this paper, the share of systematic errors and random errors in total error of exemplary probes are determined. In the case of simple, kinematic probes, systematic errors are much greater than random errors, so compensation would significantly reduce the probing error. Moreover, it shows that in the case of kinematic probes commonly specified unidirectional repeatability is significantly better than 2D performance. However, in the case of more precise strain-gauge probe systematic errors are of the same order as random errors, which means that errors correction or compensation, in this case, would not yield any significant benefits.
Measurement errors in multifrequency bioelectrical impedance analyzers with and without impedance electrode mismatch

International Nuclear Information System (INIS)

Bogónez-Franco, P; Nescolarde, L; Bragós, R; Rosell-Ferrer, J; Yandiola, I

2009-01-01

The purpose of this study is to compare measurement errors in two commercially available multi-frequency bioimpedance analyzers, a Xitron 4000B and an ImpediMed SFB7, including electrode impedance mismatch. The comparison was made using resistive electrical models and in ten human volunteers. We used three different electrical models simulating three different body segments: the right-side, leg and thorax. In the electrical models, we tested the effect of the capacitive coupling of the patient to ground and the skin–electrode impedance mismatch. Results showed that both sets of equipment are optimized for right-side measurements and for moderate skin–electrode impedance mismatch. In right-side measurements with mismatch electrode, 4000B is more accurate than SFB7. When an electrode impedance mismatch was simulated, errors increased in both bioimpedance analyzers and the effect of the mismatch in the voltage detection leads was greater than that in current injection leads. For segments with lower impedance as the leg and thorax, SFB7 is more accurate than 4000B and also shows less dependence on electrode mismatch. In both devices, impedance measurements were not significantly affected (p > 0.05) by the capacitive coupling to ground
Bias correction by use of errors-in-variables regression models in studies with K-X-ray fluorescence bone lead measurements.

Science.gov (United States)

Lamadrid-Figueroa, Héctor; Téllez-Rojo, Martha M; Angeles, Gustavo; Hernández-Ávila, Mauricio; Hu, Howard

2011-01-01

In-vivo measurement of bone lead by means of K-X-ray fluorescence (KXRF) is the preferred biological marker of chronic exposure to lead. Unfortunately, considerable measurement error associated with KXRF estimations can introduce bias in estimates of the effect of bone lead when this variable is included as the exposure in a regression model. Estimates of uncertainty reported by the KXRF instrument reflect the variance of the measurement error and, although they can be used to correct the measurement error bias, they are seldom used in epidemiological statistical analyzes. Errors-in-variables regression (EIV) allows for correction of bias caused by measurement error in predictor variables, based on the knowledge of the reliability of such variables. The authors propose a way to obtain reliability coefficients for bone lead measurements from uncertainty data reported by the KXRF instrument and compare, by the use of Monte Carlo simulations, results obtained using EIV regression models vs. those obtained by the standard procedures. Results of the simulations show that Ordinary Least Square (OLS) regression models provide severely biased estimates of effect, and that EIV provides nearly unbiased estimates. Although EIV effect estimates are more imprecise, their mean squared error is much smaller than that of OLS estimates. In conclusion, EIV is a better alternative than OLS to estimate the effect of bone lead when measured by KXRF. Copyright Â© 2010 Elsevier Inc. All rights reserved.
Semiparametric Bayesian Analysis of Nutritional Epidemiology Data in the Presence of Measurement Error

KAUST Repository

Sinha, Samiran

2009-08-10

We propose a semiparametric Bayesian method for handling measurement error in nutritional epidemiological data. Our goal is to estimate nonparametrically the form of association between a disease and exposure variable while the true values of the exposure are never observed. Motivated by nutritional epidemiological data, we consider the setting where a surrogate covariate is recorded in the primary data, and a calibration data set contains information on the surrogate variable and repeated measurements of an unbiased instrumental variable of the true exposure. We develop a flexible Bayesian method where not only is the relationship between the disease and exposure variable treated semiparametrically, but also the relationship between the surrogate and the true exposure is modeled semiparametrically. The two nonparametric functions are modeled simultaneously via B-splines. In addition, we model the distribution of the exposure variable as a Dirichlet process mixture of normal distributions, thus making its modeling essentially nonparametric and placing this work into the context of functional measurement error modeling. We apply our method to the NIH-AARP Diet and Health Study and examine its performance in a simulation study.
Optics measurement algorithms and error analysis for the proton energy frontier

CERN Document Server

Langner, A

2015-01-01

Optics measurement algorithms have been improved in preparation for the commissioning of the LHC at higher energy, i.e., with an increased damage potential. Due to machine protection considerations the higher energy sets tighter limits in the maximum excitation amplitude and the total beam charge, reducing the signal to noise ratio of optics measurements. Furthermore the precision in 2012 (4 TeV) was insufficient to understand beam size measurements and determine interaction point (IP) β-functions (β). A new, more sophisticated algorithm has been developed which takes into account both the statistical and systematic errors involved in this measurement. This makes it possible to combine more beam position monitor measurements for deriving the optical parameters and demonstrates to significantly improve the accuracy and precision. Measurements from the 2012 run have been reanalyzed which, due to the improved algorithms, result in a significantly higher precision of the derived optical parameters and decreased...
A study of the effect of measurement error in predictor variables in nondestructive assay

International Nuclear Information System (INIS)

Burr, Tom L.; Knepper, Paula L.

2000-01-01

It is not widely known that ordinary least squares estimates exhibit bias if there are errors in the predictor variables. For example, enrichment measurements are often fit to two predictors: Poisson-distributed count rates in the region of interest and in the background. Both count rates have at least random variation due to counting statistics. Therefore, the parameter estimates will be biased. In this case, the effect of bias is a minor issue because there is almost no interest in the parameters themselves. Instead, the parameters will be used to convert count rates into estimated enrichment. In other cases, this bias source is potentially more important. For example, in tomographic gamma scanning, there is an emission stage which depends on predictors (the 'system matrix') that are estimated with error during the transmission stage. In this paper, we provide background information for the impact and treatment of errors in predictors, present results of candidate methods of compensating for the effect, review some of the nondestructive assay situations where errors in predictors occurs, and provide guidance for when errors in predictors should be considered in nondestructive assay
Stochastic Frontier Models with Dependent Errors based on Normal and Exponential Margins || Modelos de frontera estocástica con errores dependientes basados en márgenes normal y exponencial

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Gómez-Déniz, Emilio

2017-06-01

Full Text Available Following the recent work of Gómez-Déniz and Pérez-Rodríguez (2014, this paper extends the results obtained there to the normal-exponential distribution with dependence. Accordingly, the main aim of the present paper is to enhance stochastic production frontier and stochastic cost frontier modelling by proposing a bivariate distribution for dependent errors which allows us to nest the classical models. Closed-form expressions for the error term and technical efficiency are provided. An illustration using real data from the econometric literature is provided to show the applicability of the model proposed. || Continuando el reciente trabajo de Gómez-Déniz y Pérez-Rodríguez (2014, el presente artículo extiende los resultados obtenidos a la distribución normal-exponencial con dependencia. En consecuencia, el principal propósito de este artículo es mejorar el modelado de la frontera estocástica tanto de producción como de coste proponiendo para ello una distribución bivariante para errores dependientes que nos permitan encajar los modelos clásicos. Se obtienen las expresiones en forma cerrada para el término de error y la eficiencia técnica. Se ilustra la aplicabilidad del modelo propouesto usando datos reales existentes en la literatura econométrica.
Measurement Error Affects Risk Estimates for Recruitment to the Hudson River Stock of Striped Bass

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Dennis J. Dunning

2002-01-01

Full Text Available We examined the consequences of ignoring the distinction between measurement error and natural variability in an assessment of risk to the Hudson River stock of striped bass posed by entrainment at the Bowline Point, Indian Point, and Roseton power plants. Risk was defined as the probability that recruitment of age-1+ striped bass would decline by 80% or more, relative to the equilibrium value, at least once during the time periods examined (1, 5, 10, and 15 years. Measurement error, estimated using two abundance indices from independent beach seine surveys conducted on the Hudson River, accounted for 50% of the variability in one index and 56% of the variability in the other. If a measurement error of 50% was ignored and all of the variability in abundance was attributed to natural causes, the risk that recruitment of age-1+ striped bass would decline by 80% or more after 15 years was 0.308 at the current level of entrainment mortality (11%. However, the risk decreased almost tenfold (0.032 if a measurement error of 50% was considered. The change in risk attributable to decreasing the entrainment mortality rate from 11 to 0% was very small (0.009 and similar in magnitude to the change in risk associated with an action proposed in Amendment #5 to the Interstate Fishery Management Plan for Atlantic striped bass (0.006— an increase in the instantaneous fishing mortality rate from 0.33 to 0.4. The proposed increase in fishing mortality was not considered an adverse environmental impact, which suggests that potentially costly efforts to reduce entrainment mortality on the Hudson River stock of striped bass are not warranted.
Regression analysis for bivariate gap time with missing first gap time data.

Science.gov (United States)

Huang, Chia-Hui; Chen, Yi-Hau

2017-01-01

We consider ordered bivariate gap time while data on the first gap time are unobservable. This study is motivated by the HIV infection and AIDS study, where the initial HIV contracting time is unavailable, but the diagnosis times for HIV and AIDS are available. We are interested in studying the risk factors for the gap time between initial HIV contraction and HIV diagnosis, and gap time between HIV and AIDS diagnoses. Besides, the association between the two gap times is also of interest. Accordingly, in the data analysis we are faced with two-fold complexity, namely data on the first gap time is completely missing, and the second gap time is subject to induced informative censoring due to dependence between the two gap times. We propose a modeling framework for regression analysis of bivariate gap time under the complexity of the data. The estimating equations for the covariate effects on, as well as the association between, the two gap times are derived through maximum likelihood and suitable counting processes. Large sample properties of the resulting estimators are developed by martingale theory. Simulations are performed to examine the performance of the proposed analysis procedure. An application of data from the HIV and AIDS study mentioned above is reported for illustration.
High-accuracy measurement and compensation of grating line-density error in a tiled-grating compressor

Science.gov (United States)

Zhao, Dan; Wang, Xiao; Mu, Jie; Li, Zhilin; Zuo, Yanlei; Zhou, Song; Zhou, Kainan; Zeng, Xiaoming; Su, Jingqin; Zhu, Qihua

2017-02-01

The grating tiling technology is one of the most effective means to increase the aperture of the gratings. The line-density error (LDE) between sub-gratings will degrade the performance of the tiling gratings, high accuracy measurement and compensation of the LDE are of significance to improve the output pulses characteristics of the tiled-grating compressor. In this paper, the influence of LDE on the output pulses of the tiled-grating compressor is quantitatively analyzed by means of numerical simulation, the output beams drift and output pulses broadening resulting from the LDE are presented. Based on the numerical results we propose a compensation method to reduce the degradations of the tiled grating compressor by applying angular tilt error and longitudinal piston error at the same time. Moreover, a monitoring system is setup to measure the LDE between sub-gratings accurately and the dispersion variation due to the LDE is also demonstrated based on spatial-spectral interference. In this way, we can realize high-accuracy measurement and compensation of the LDE, and this would provide an efficient way to guide the adjustment of the tiling gratings.
A COMPARISON OF SOME ROBUST BIVARIATE CONTROL CHARTS FOR INDIVIDUAL OBSERVATIONS

Directory of Open Access Journals (Sweden)

Moustafa Omar Ahmed Abu - Shawiesh

2014-06-01

Full Text Available This paper proposed and considered some bivariate control charts to monitor individual observations from a statistical process control. Usual control charts which use mean and variance-covariance estimators are sensitive to outliers. We consider the following robust alternatives to the classical Hoteling's T2: T2MedMAD, T2MCD, T2MVE a simulation study has been conducted to compare the performance of these control charts. Two real life data are analyzed to illustrate the application of these robust alternatives.
A comparison between multivariate and bivariate analysis used in marketing research

Directory of Open Access Journals (Sweden)

Constantin, C.

2012-01-01

Full Text Available This paper is about an instrumental research conducted in order to compare the information given by two multivariate data analysis in comparison with the usual bivariate analysis. The outcomes of the research reveal that sometimes the multivariate methods use more information from a certain variable, but sometimes they use only a part of the information considered the most important for certain associations. For this reason, a researcher should use both categories of data analysis in order to obtain entirely useful information.
Comparison between calorimeter and HLNC errors

International Nuclear Information System (INIS)

Goldman, A.S.; De Ridder, P.; Laszlo, G.

1991-01-01

This paper summarizes an error analysis that compares systematic and random errors of total plutonium mass estimated for high-level neutron coincidence counter (HLNC) and calorimeter measurements. This task was part of an International Atomic Energy Agency (IAEA) study on the comparison of the two instruments to determine if HLNC measurement errors met IAEA standards and if the calorimeter gave ''significantly'' better precision. Our analysis was based on propagation of error models that contained all known sources of errors including uncertainties associated with plutonium isotopic measurements. 5 refs., 2 tabs
Robustness of SOC Estimation Algorithms for EV Lithium-Ion Batteries against Modeling Errors and Measurement Noise

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Xue Li

2015-01-01

Full Text Available State of charge (SOC is one of the most important parameters in battery management system (BMS. There are numerous algorithms for SOC estimation, mostly of model-based observer/filter types such as Kalman filters, closed-loop observers, and robust observers. Modeling errors and measurement noises have critical impact on accuracy of SOC estimation in these algorithms. This paper is a comparative study of robustness of SOC estimation algorithms against modeling errors and measurement noises. By using a typical battery platform for vehicle applications with sensor noise and battery aging characterization, three popular and representative SOC estimation methods (extended Kalman filter, PI-controlled observer, and H∞ observer are compared on such robustness. The simulation and experimental results demonstrate that deterioration of SOC estimation accuracy under modeling errors resulted from aging and larger measurement noise, which is quantitatively characterized. The findings of this paper provide useful information on the following aspects: (1 how SOC estimation accuracy depends on modeling reliability and voltage measurement accuracy; (2 pros and cons of typical SOC estimators in their robustness and reliability; (3 guidelines for requirements on battery system identification and sensor selections.

Low relative error in consumer-grade GPS units make them ideal for measuring small-scale animal movement patterns

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Greg A. Breed

2015-08-01

Full Text Available Consumer-grade GPS units are a staple of modern field ecology, but the relatively large error radii reported by manufacturers (up to 10 m ostensibly precludes their utility in measuring fine-scale movement of small animals such as insects. Here we demonstrate that for data collected at fine spatio-temporal scales, these devices can produce exceptionally accurate data on step-length and movement patterns of small animals. With an understanding of the properties of GPS error and how it arises, it is possible, using a simple field protocol, to use consumer grade GPS units to collect step-length data for the movement of small animals that introduces a median error as small as 11 cm. These small error rates were measured in controlled observations of real butterfly movement. Similar conclusions were reached using a ground-truth test track prepared with a field tape and compass and subsequently measured 20 times using the same methodology as the butterfly tracking. Median error in the ground-truth track was slightly higher than the field data, mostly between 20 and 30 cm, but even for the smallest ground-truth step (70 cm, this is still a signal-to-noise ratio of 3:1, and for steps of 3 m or more, the ratio is greater than 10:1. Such small errors relative to the movements being measured make these inexpensive units useful for measuring insect and other small animal movements on small to intermediate scales with budgets orders of magnitude lower than survey-grade units used in past studies. As an additional advantage, these units are simpler to operate, and insect or other small animal trackways can be collected more quickly than either survey-grade units or more traditional ruler/gird approaches.
Reliability and measurement error of sagittal spinal motion parameters in 220 patients with chronic low back pain using a three-dimensional measurement device.

Science.gov (United States)

Mieritz, Rune M; Bronfort, Gert; Jakobsen, Markus D; Aagaard, Per; Hartvigsen, Jan

2014-09-01

A basic premise for any instrument measuring spinal motion is that reliable outcomes can be obtained on a relevant sample under standardized conditions. The purpose of this study was to assess the overall reliability and measurement error of regional spinal sagittal plane motion in patients with chronic low back pain (LBP), and then to evaluate the influence of body mass index, examiner, gender, stability of pain, and pain distribution on reliability and measurement error. This study comprises a test-retest design separated by 7 to 14 days. The patient cohort consisted of 220 individuals with chronic LBP. Kinematics of the lumbar spine were sampled during standardized spinal extension-flexion testing using a 6-df instrumented spatial linkage system. Test-retest reliability and measurement error were evaluated using interclass correlation coefficients (ICC(1,1)) and Bland-Altman limits of agreement (LOAs). The overall test-retest reliability (ICC(1,1)) for various motion parameters ranged from 0.51 to 0.70, and relatively wide LOAs were observed for all parameters. Reliability measures in patient subgroups (ICC(1,1)) ranged between 0.34 and 0.77. In general, greater (ICC(1,1)) coefficients and smaller LOAs were found in subgroups with patients examined by the same examiner, patients with a stable pain level, patients with a body mass index less than below 30 kg/m(2), patients who were men, and patients in the Quebec Task Force classifications Group 1. This study shows that sagittal plane kinematic data from patients with chronic LBP may be sufficiently reliable in measurements of groups of patients. However, because of the large LOAs, this test procedure appears unusable at the individual patient level. Furthermore, reliability and measurement error varies substantially among subgroups of patients. Copyright © 2014 Elsevier Inc. All rights reserved.
Accounting for optical errors in microtensiometry.

Science.gov (United States)

Hinton, Zachary R; Alvarez, Nicolas J

2018-09-15

Drop shape analysis (DSA) techniques measure interfacial tension subject to error in image analysis and the optical system. While considerable efforts have been made to minimize image analysis errors, very little work has treated optical errors. There are two main sources of error when considering the optical system: the angle of misalignment and the choice of focal plane. Due to the convoluted nature of these sources, small angles of misalignment can lead to large errors in measured curvature. We demonstrate using microtensiometry the contributions of these sources to measured errors in radius, and, more importantly, deconvolute the effects of misalignment and focal plane. Our findings are expected to have broad implications on all optical techniques measuring interfacial curvature. A geometric model is developed to analytically determine the contributions of misalignment angle and choice of focal plane on measurement error for spherical cap interfaces. This work utilizes a microtensiometer to validate the geometric model and to quantify the effect of both sources of error. For the case of a microtensiometer, an empirical calibration is demonstrated that corrects for optical errors and drastically simplifies implementation. The combination of geometric modeling and experimental results reveal a convoluted relationship between the true and measured interfacial radius as a function of the misalignment angle and choice of focal plane. The validated geometric model produces a full operating window that is strongly dependent on the capillary radius and spherical cap height. In all cases, the contribution of optical errors is minimized when the height of the spherical cap is equivalent to the capillary radius, i.e. a hemispherical interface. The understanding of these errors allow for correct measure of interfacial curvature and interfacial tension regardless of experimental setup. For the case of microtensiometry, this greatly decreases the time for experimental setup
Inference for the Bivariate and Multivariate Hidden Truncated Pareto(type II) and Pareto(type IV) Distribution and Some Measures of Divergence Related to Incompatibility of Probability Distribution

Science.gov (United States)

Ghosh, Indranil

2011-01-01

Consider a discrete bivariate random variable (X, Y) with possible values x[subscript 1], x[subscript 2],..., x[subscript I] for X and y[subscript 1], y[subscript 2],..., y[subscript J] for Y. Further suppose that the corresponding families of conditional distributions, for X given values of Y and of Y for given values of X are available. We…
Measurement-based analysis of error latency. [in computer operating system

Science.gov (United States)

Chillarege, Ram; Iyer, Ravishankar K.

1987-01-01

This paper demonstrates a practical methodology for the study of error latency under a real workload. The method is illustrated with sampled data on the physical memory activity, gathered by hardware instrumentation on a VAX 11/780 during the normal workload cycle of the installation. These data are used to simulate fault occurrence and to reconstruct the error discovery process in the system. The technique provides a means to study the system under different workloads and for multiple days. An approach to determine the percentage of undiscovered errors is also developed and a verification of the entire methodology is performed. This study finds that the mean error latency, in the memory containing the operating system, varies by a factor of 10 to 1 (in hours) between the low and high workloads. It is found that of all errors occurring within a day, 70 percent are detected in the same day, 82 percent within the following day, and 91 percent within the third day. The increase in failure rate due to latency is not so much a function of remaining errors but is dependent on whether or not there is a latent error.
A measurement error approach to assess the association between dietary diversity, nutrient intake, and mean probability of adequacy.

Science.gov (United States)

Joseph, Maria L; Carriquiry, Alicia

2010-11-01

Collection of dietary intake information requires time-consuming and expensive methods, making it inaccessible to many resource-poor countries. Quantifying the association between simple measures of usual dietary diversity and usual nutrient intake/adequacy would allow inferences to be made about the adequacy of micronutrient intake at the population level for a fraction of the cost. In this study, we used secondary data from a dietary intake study carried out in Bangladesh to assess the association between 3 food group diversity indicators (FGI) and calcium intake; and the association between these same 3 FGI and a composite measure of nutrient adequacy, mean probability of adequacy (MPA). By implementing Fuller's error-in-the-equation measurement error model (EEM) and simple linear regression (SLR) models, we assessed these associations while accounting for the error in the observed quantities. Significant associations were detected between usual FGI and usual calcium intakes, when the more complex EEM was used. The SLR model detected significant associations between FGI and MPA as well as for variations of these measures, including the best linear unbiased predictor. Through simulation, we support the use of the EEM. In contrast to the EEM, the SLR model does not account for the possible correlation between the measurement errors in the response and predictor. The EEM performs best when the model variables are not complex functions of other variables observed with error (e.g. MPA). When observation days are limited and poor estimates of the within-person variances are obtained, the SLR model tends to be more appropriate.
Recruitment into diabetes prevention programs: what is the impact of errors in self-reported measures of obesity?

Science.gov (United States)

Hernan, Andrea; Philpot, Benjamin; Janus, Edward D; Dunbar, James A

2012-07-08

Error in self-reported measures of obesity has been frequently described, but the effect of self-reported error on recruitment into diabetes prevention programs is not well established. The aim of this study was to examine the effect of using self-reported obesity data from the Finnish diabetes risk score (FINDRISC) on recruitment into the Greater Green Triangle Diabetes Prevention Project (GGT DPP). The GGT DPP was a structured group-based lifestyle modification program delivered in primary health care settings in South-Eastern Australia. Between 2004-05, 850 FINDRISC forms were collected during recruitment for the GGT DPP. Eligible individuals, at moderate to high risk of developing diabetes, were invited to undertake baseline tests, including anthropometric measurements performed by specially trained nurses. In addition to errors in calculating total risk scores, accuracy of self-reported data (height, weight, waist circumference (WC) and Body Mass Index (BMI)) from FINDRISCs was compared with baseline data, with impact on participation eligibility presented. Overall, calculation errors impacted on eligibility in 18 cases (2.1%). Of n = 279 GGT DPP participants with measured data, errors (total score calculation, BMI or WC) in self-report were found in n = 90 (32.3%). These errors were equally likely to result in under- or over-reported risk. Under-reporting was more common in those reporting lower risk scores (Spearman-rho = -0.226, p-value recruit participants at moderate to high risk of diabetes, accurately categorising levels of overweight and obesity using self-report data. The results could be generalisable to other diabetes prevention programs using screening tools which include self-reported levels of obesity.
Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics

Science.gov (United States)

Lundquist, J. K.; Churchfield, M. J.; Lee, S.; Clifton, A.

2015-02-01

Wind-profiling lidars are now regularly used in boundary-layer meteorology and in applications such as wind energy and air quality. Lidar wind profilers exploit the Doppler shift of laser light backscattered from particulates carried by the wind to measure a line-of-sight (LOS) velocity. The Doppler beam swinging (DBS) technique, used by many commercial systems, considers measurements of this LOS velocity in multiple radial directions in order to estimate horizontal and vertical winds. The method relies on the assumption of homogeneous flow across the region sampled by the beams. Using such a system in inhomogeneous flow, such as wind turbine wakes or complex terrain, will result in errors. To quantify the errors expected from such violation of the assumption of horizontal homogeneity, we simulate inhomogeneous flow in the atmospheric boundary layer, notably stably stratified flow past a wind turbine, with a mean wind speed of 6.5 m s-1 at the turbine hub-height of 80 m. This slightly stable case results in 15° of wind direction change across the turbine rotor disk. The resulting flow field is sampled in the same fashion that a lidar samples the atmosphere with the DBS approach, including the lidar range weighting function, enabling quantification of the error in the DBS observations. The observations from the instruments located upwind have small errors, which are ameliorated with time averaging. However, the downwind observations, particularly within the first two rotor diameters downwind from the wind turbine, suffer from errors due to the heterogeneity of the wind turbine wake. Errors in the stream-wise component of the flow approach 30% of the hub-height inflow wind speed close to the rotor disk. Errors in the cross-stream and vertical velocity components are also significant: cross-stream component errors are on the order of 15% of the hub-height inflow wind speed (1.0 m s-1) and errors in the vertical velocity measurement exceed the actual vertical velocity
Can i just check...? Effects of edit check questions on measurement error and survey estimates

NARCIS (Netherlands)

Lugtig, Peter; Jäckle, Annette

2014-01-01

Household income is difficult to measure, since it requires the collection of information about all potential income sources for each member of a household.Weassess the effects of two types of edit check questions on measurement error and survey estimates: within-wave edit checks use responses to
Error Analysis of High Frequency Core Loss Measurement for Low-Permeability Low-Loss Magnetic Cores

DEFF Research Database (Denmark)

Niroumand, Farideh Javidi; Nymand, Morten

2016-01-01

in magnetic cores is B-H loop measurement where two windings are placed on the core under test. However, this method is highly vulnerable to phase shift error, especially for low-permeability, low-loss cores. Due to soft saturation and very low core loss, low-permeability low-loss magnetic cores are favorable...... in many of the high-efficiency high power-density power converters. Magnetic powder cores, among the low-permeability low-loss cores, are very attractive since they possess lower magnetic losses in compared to gapped ferrites. This paper presents an analytical study of the phase shift error in the core...... loss measuring of low-permeability, low-loss magnetic cores. Furthermore, the susceptibility of this measurement approach has been analytically investigated under different excitations. It has been shown that this method, under square-wave excitation, is more accurate compared to sinusoidal excitation...
The relative size of measurement error and attrition error in a panel survey. Comparing them with a new multi-trait multi-method model

NARCIS (Netherlands)

Lugtig, Peter

2017-01-01

This paper proposes a method to simultaneously estimate both measurement and nonresponse errors for attitudinal and behavioural questions in a longitudinal survey. The method uses a Multi-Trait Multi-Method (MTMM) approach, which is commonly used to estimate the reliability and validity of survey
Bivariate return periods of temperature and precipitation explain a large fraction of European crop yields

Directory of Open Access Journals (Sweden)

J. Zscheischler

2017-07-01

Full Text Available Crops are vital for human society. Crop yields vary with climate and it is important to understand how climate and crop yields are linked to ensure future food security. Temperature and precipitation are among the key driving factors of crop yield variability. Previous studies have investigated mostly linear relationships between temperature and precipitation and crop yield variability. Other research has highlighted the adverse impacts of climate extremes, such as drought and heat waves, on crop yields. Impacts are, however, often non-linearly related to multivariate climate conditions. Here we derive bivariate return periods of climate conditions as indicators for climate variability along different temperature–precipitation gradients. We show that in Europe, linear models based on bivariate return periods of specific climate conditions explain on average significantly more crop yield variability (42 % than models relying directly on temperature and precipitation as predictors (36 %. Our results demonstrate that most often crop yields increase along a gradient from hot and dry to cold and wet conditions, with lower yields associated with hot and dry periods. The majority of crops are most sensitive to climate conditions in summer and to maximum temperatures. The use of bivariate return periods allows the integration of non-linear impacts into climate–crop yield analysis. This offers new avenues to study the link between climate and crop yield variability and suggests that they are possibly more strongly related than what is inferred from conventional linear models.
Measurements of Gun Tube Motion and Muzzle Pointing Error of Main Battle Tanks

Directory of Open Access Journals (Sweden)

Peter L. McCall

2001-01-01

Full Text Available Beginning in 1990, the US Army Aberdeen Test Center (ATC began testing a prototype cannon mounted in a non-armored turret fitted to an M1A1 Abrams tank chassis. The cannon design incorporated a longer gun tube as a means to increase projectile velocity. A significant increase in projectile impact dispersion was measured early in the test program. Through investigative efforts, the cause of the error was linked to the increased dynamic bending or flexure of the longer tube observed while the vehicle was moving. Research and investigative work was conducted through a collaborative effort with the US Army Research Laboratory, Benet Laboratory, Project Manager – Tank Main Armament Systems, US Army Research and Engineering Center, and Cadillac Gage Textron Inc. New test methods, instrumentation, data analysis procedures, and stabilization control design resulted through this series of investigations into the dynamic tube flexure error source. Through this joint research, improvements in tank fire control design have been developed to improve delivery accuracy. This paper discusses the instrumentation implemented, methods applied, and analysis procedures used to characterize the tube flexure during dynamic tests of a main battle tank and the relationship between gun pointing error and muzzle pointing error.
Simulation error propagation for a dynamic rod worth measurement technique

International Nuclear Information System (INIS)

Kastanya, D.F.; Turinsky, P.J.

1996-01-01

KRSKO nuclear station, subsequently adapted by Westinghouse, introduced the dynamic rod worth measurement (DRWM) technique for measuring pressurized water reactor rod worths. This technique has the potential for reduced test time and primary loop waste water versus alternatives. The measurement is performed starting from a slightly supercritical state with all rods out (ARO), driving a bank in at the maximum stepping rate, and recording the ex-core detectors responses and bank position as a function of time. The static bank worth is obtained by (1) using the ex-core detectors' responses to obtain the core average flux (2) using the core average flux in the inverse point-kinetics equations to obtain the dynamic bank worth (3) converting the dynamic bank worth to the static bank worth. In this data interpretation process, various calculated quantities obtained from a core simulator are utilized. This paper presents an analysis of the sensitivity to the impact of core simulator errors on the deduced static bank worth
Influence of Marker Movement Errors on Measuring 3 Dimentional Scapular Position and Orientation

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Afsoun Nodehi-Moghaddam

2003-12-01

Full Text Available Objective: Scapulothoracic muscles weakness or fatique can result in abnormal scapular positioning and compromising scapulo-humeral rhythm and shoulder dysfunction .The scapula moves in a -3 Dimentional fashion so the use of 2-Dimentional Techniques cannot fully capture scapular motion . One of approaches to positioining markers of kinematic systems is to mount each marker directly on the skin generally over a bony anatomical landmarks . Howerer skin movement and Motion of underlying bony structures are not Necessaritly identical and substantial errors may be introduced in the description of bone movement when using skin –mounted markers. evaluation of Influence of marker movement errors on 3-Dimentional scapular position and orientation. Materials & Methods: 10 Healthy subjects with a mean age 30.50 participated in the study . They were tested in three sessions A 3-dimentiional electro mechanical digitizer was used to measure scapular position and orientation measures were obtained while arm placed at the side of the body and elevated 45٫90٫120 and full Rang of motion in the scapular plane . At each test positions six bony landmarks were palpated and skin markers were mounted on them . This procedure repeated in the second test session in third session Removal of markers was not performed through obtaining entire Range of motion after mounting the markers . Results: The intraclass correlation coefficients (ICC for scapulor variables were higher (0.92-0.84 when markers were replaced and re-mounted on bony landmarks with Increasing the angle of elevation. Conclusion: our findings suggested significant markers movement error on measuring the upward Rotation and posterior tilt angle of scapula.
The Applicability of Standard Error of Measurement and Minimal Detectable Change to Motor Learning Research-A Behavioral Study.

Science.gov (United States)

Furlan, Leonardo; Sterr, Annette

2018-01-01

Motor learning studies face the challenge of differentiating between real changes in performance and random measurement error. While the traditional p -value-based analyses of difference (e.g., t -tests, ANOVAs) provide information on the statistical significance of a reported change in performance scores, they do not inform as to the likely cause or origin of that change, that is, the contribution of both real modifications in performance and random measurement error to the reported change. One way of differentiating between real change and random measurement error is through the utilization of the statistics of standard error of measurement (SEM) and minimal detectable change (MDC). SEM is estimated from the standard deviation of a sample of scores at baseline and a test-retest reliability index of the measurement instrument or test employed. MDC, in turn, is estimated from SEM and a degree of confidence, usually 95%. The MDC value might be regarded as the minimum amount of change that needs to be observed for it to be considered a real change, or a change to which the contribution of real modifications in performance is likely to be greater than that of random measurement error. A computer-based motor task was designed to illustrate the applicability of SEM and MDC to motor learning research. Two studies were conducted with healthy participants. Study 1 assessed the test-retest reliability of the task and Study 2 consisted in a typical motor learning study, where participants practiced the task for five consecutive days. In Study 2, the data were analyzed with a traditional p -value-based analysis of difference (ANOVA) and also with SEM and MDC. The findings showed good test-retest reliability for the task and that the p -value-based analysis alone identified statistically significant improvements in performance over time even when the observed changes could in fact have been smaller than the MDC and thereby caused mostly by random measurement error, as opposed
Soil pH Errors Propagation from Measurements to Spatial Predictions - Cost Benefit Analysis and Risk Assessment Implications for Practitioners and Modelers

Science.gov (United States)

Owens, P. R.; Libohova, Z.; Seybold, C. A.; Wills, S. A.; Peaslee, S.; Beaudette, D.; Lindbo, D. L.

2017-12-01

The measurement errors and spatial prediction uncertainties of soil properties in the modeling community are usually assessed against measured values when available. However, of equal importance is the assessment of errors and uncertainty impacts on cost benefit analysis and risk assessments. Soil pH was selected as one of the most commonly measured soil properties used for liming recommendations. The objective of this study was to assess the error size from different sources and their implications with respect to management decisions. Error sources include measurement methods, laboratory sources, pedotransfer functions, database transections, spatial aggregations, etc. Several databases of measured and predicted soil pH were used for this study including the United States National Cooperative Soil Survey Characterization Database (NCSS-SCDB), the US Soil Survey Geographic (SSURGO) Database. The distribution of errors among different sources from measurement methods to spatial aggregation showed a wide range of values. The greatest RMSE of 0.79 pH units was from spatial aggregation (SSURGO vs Kriging), while the measurement methods had the lowest RMSE of 0.06 pH units. Assuming the order of data acquisition based on the transaction distance i.e. from measurement method to spatial aggregation the RMSE increased from 0.06 to 0.8 pH units suggesting an "error propagation". This has major implications for practitioners and modeling community. Most soil liming rate recommendations are based on 0.1 pH unit increments, while the desired soil pH level increments are based on 0.4 to 0.5 pH units. Thus, even when the measured and desired target soil pH are the same most guidelines recommend 1 ton ha-1 lime, which translates in 111 ha-1 that the farmer has to factor in the cost-benefit analysis. However, this analysis need to be based on uncertainty predictions (0.5-1.0 pH units) rather than measurement errors (0.1 pH units) which would translate in 555-1,111 investment that
Field error lottery

Energy Technology Data Exchange (ETDEWEB)

Elliott, C.J.; McVey, B. (Los Alamos National Lab., NM (USA)); Quimby, D.C. (Spectra Technology, Inc., Bellevue, WA (USA))

1990-01-01

The level of field errors in an FEL is an important determinant of its performance. We have computed 3D performance of a large laser subsystem subjected to field errors of various types. These calculations have been guided by simple models such as SWOOP. The technique of choice is utilization of the FELEX free electron laser code that now possesses extensive engineering capabilities. Modeling includes the ability to establish tolerances of various types: fast and slow scale field bowing, field error level, beam position monitor error level, gap errors, defocusing errors, energy slew, displacement and pointing errors. Many effects of these errors on relative gain and relative power extraction are displayed and are the essential elements of determining an error budget. The random errors also depend on the particular random number seed used in the calculation. The simultaneous display of the performance versus error level of cases with multiple seeds illustrates the variations attributable to stochasticity of this model. All these errors are evaluated numerically for comprehensive engineering of the system. In particular, gap errors are found to place requirements beyond mechanical tolerances of {plus minus}25{mu}m, and amelioration of these may occur by a procedure utilizing direct measurement of the magnetic fields at assembly time. 4 refs., 12 figs.
Rate estimation in partially observed Markov jump processes with measurement errors

OpenAIRE

Amrein, Michael; Kuensch, Hans R.

2010-01-01

We present a simulation methodology for Bayesian estimation of rate parameters in Markov jump processes arising for example in stochastic kinetic models. To handle the problem of missing components and measurement errors in observed data, we embed the Markov jump process into the framework of a general state space model. We do not use diffusion approximations. Markov chain Monte Carlo and particle filter type algorithms are introduced, which allow sampling from the posterior distribution of t...
Abnormal error monitoring in math-anxious individuals: evidence from error-related brain potentials.

Directory of Open Access Journals (Sweden)

Macarena Suárez-Pellicioni

Full Text Available This study used event-related brain potentials to investigate whether math anxiety is related to abnormal error monitoring processing. Seventeen high math-anxious (HMA and seventeen low math-anxious (LMA individuals were presented with a numerical and a classical Stroop task. Groups did not differ in terms of trait or state anxiety. We found enhanced error-related negativity (ERN in the HMA group when subjects committed an error on the numerical Stroop task, but not on the classical Stroop task. Groups did not differ in terms of the correct-related negativity component (CRN, the error positivity component (Pe, classical behavioral measures or post-error measures. The amplitude of the ERN was negatively related to participants' math anxiety scores, showing a more negative amplitude as the score increased. Moreover, using standardized low resolution electromagnetic tomography (sLORETA we found greater activation of the insula in errors on a numerical task as compared to errors in a non-numerical task only for the HMA group. The results were interpreted according to the motivational significance theory of the ERN.

Errors of car wheels rotation rate measurement using roller follower on test benches

Science.gov (United States)

Potapov, A. S.; Svirbutovich, O. A.; Krivtsov, S. N.

2018-03-01

The article deals with rotation rate measurement errors, which depend on the motor vehicle rate, on the roller, test benches. Monitoring of the vehicle performance under operating conditions is performed on roller test benches. Roller test benches are not flawless. They have some drawbacks affecting the accuracy of vehicle performance monitoring. Increase in basic velocity of the vehicle requires increase in accuracy of wheel rotation rate monitoring. It determines the degree of accuracy of mode identification for a wheel of the tested vehicle. To ensure measurement accuracy for rotation velocity of rollers is not an issue. The problem arises when measuring rotation velocity of a car wheel. The higher the rotation velocity of the wheel is, the lower the accuracy of measurement is. At present, wheel rotation frequency monitoring on roller test benches is carried out by following-up systems. Their sensors are rollers following wheel rotation. The rollers of the system are not kinematically linked to supporting rollers of the test bench. The roller follower is forced against the wheels of the tested vehicle by means of a spring-lever mechanism. Experience of the test bench equipment operation has shown that measurement accuracy is satisfactory at small rates of vehicles diagnosed on roller test benches. With a rising diagnostics rate, rotation velocity measurement errors occur in both braking and pulling modes because a roller spins about a tire tread. The paper shows oscillograms of changes in wheel rotation velocity and rotation velocity measurement system’s signals when testing a vehicle on roller test benches at specified rates.
How Do Simulated Error Experiences Impact Attitudes Related to Error Prevention?

Science.gov (United States)

Breitkreuz, Karen R; Dougal, Renae L; Wright, Melanie C

2016-10-01

The objective of this project was to determine whether simulated exposure to error situations changes attitudes in a way that may have a positive impact on error prevention behaviors. Using a stratified quasi-randomized experiment design, we compared risk perception attitudes of a control group of nursing students who received standard error education (reviewed medication error content and watched movies about error experiences) to an experimental group of students who reviewed medication error content and participated in simulated error experiences. Dependent measures included perceived memorability of the educational experience, perceived frequency of errors, and perceived caution with respect to preventing errors. Experienced nursing students perceived the simulated error experiences to be more memorable than movies. Less experienced students perceived both simulated error experiences and movies to be highly memorable. After the intervention, compared with movie participants, simulation participants believed errors occurred more frequently. Both types of education increased the participants' intentions to be more cautious and reported caution remained higher than baseline for medication errors 6 months after the intervention. This study provides limited evidence of an advantage of simulation over watching movies describing actual errors with respect to manipulating attitudes related to error prevention. Both interventions resulted in long-term impacts on perceived caution in medication administration. Simulated error experiences made participants more aware of how easily errors can occur, and the movie education made participants more aware of the devastating consequences of errors.
Laboratory errors and patient safety.

Science.gov (United States)

Miligy, Dawlat A

2015-01-01

Laboratory data are extensively used in medical practice; consequently, laboratory errors have a tremendous impact on patient safety. Therefore, programs designed to identify and reduce laboratory errors, as well as, setting specific strategies are required to minimize these errors and improve patient safety. The purpose of this paper is to identify part of the commonly encountered laboratory errors throughout our practice in laboratory work, their hazards on patient health care and some measures and recommendations to minimize or to eliminate these errors. Recording the encountered laboratory errors during May 2008 and their statistical evaluation (using simple percent distribution) have been done in the department of laboratory of one of the private hospitals in Egypt. Errors have been classified according to the laboratory phases and according to their implication on patient health. Data obtained out of 1,600 testing procedure revealed that the total number of encountered errors is 14 tests (0.87 percent of total testing procedures). Most of the encountered errors lay in the pre- and post-analytic phases of testing cycle (representing 35.7 and 50 percent, respectively, of total errors). While the number of test errors encountered in the analytic phase represented only 14.3 percent of total errors. About 85.7 percent of total errors were of non-significant implication on patients health being detected before test reports have been submitted to the patients. On the other hand, the number of test errors that have been already submitted to patients and reach the physician represented 14.3 percent of total errors. Only 7.1 percent of the errors could have an impact on patient diagnosis. The findings of this study were concomitant with those published from the USA and other countries. This proves that laboratory problems are universal and need general standardization and bench marking measures. Original being the first data published from Arabic countries that
Continuous glucose monitoring in newborn infants: how do errors in calibration measurements affect detected hypoglycemia?

OpenAIRE

Thomas, Felicity Louise; Signal, Mathew; Harris, Deborah L.; Weston, Philip J.; Harding, Jane E.; Shaw, Geoffrey M.; Chase, J. Geoffrey

2014-01-01

Neonatal hypoglycemia is common and can cause serious brain injury. Continuous glucose monitoring (CGM) could improve hypoglycemia detection, while reducing blood glucose (BG) measurements. Calibration algorithms use BG measurements to convert sensor signals into CGM data. Thus, inaccuracies in calibration BG measurements directly affect CGM values and any metrics calculated from them. The aim was to quantify the effect of timing delays and calibration BG measurement errors on hypoglycemia me...
A statistical model for measurement error that incorporates variation over time in the target measure, with application to nutritional epidemiology.

Science.gov (United States)

Freedman, Laurence S; Midthune, Douglas; Dodd, Kevin W; Carroll, Raymond J; Kipnis, Victor

2015-11-30

Most statistical methods that adjust analyses for measurement error assume that the target exposure T is a fixed quantity for each individual. However, in many applications, the value of T for an individual varies with time. We develop a model that accounts for such variation, describing the model within the framework of a meta-analysis of validation studies of dietary self-report instruments, where the reference instruments are biomarkers. We demonstrate that in this application, the estimates of the attenuation factor and correlation with true intake, key parameters quantifying the accuracy of the self-report instrument, are sometimes substantially modified under the time-varying exposure model compared with estimates obtained under a traditional fixed-exposure model. We conclude that accounting for the time element in measurement error problems is potentially important. Copyright © 2015 John Wiley & Sons, Ltd.
Measurement error in epidemiologic studies of air pollution based on land-use regression models.

Science.gov (United States)

Basagaña, Xavier; Aguilera, Inmaculada; Rivera, Marcela; Agis, David; Foraster, Maria; Marrugat, Jaume; Elosua, Roberto; Künzli, Nino

2013-10-15

Land-use regression (LUR) models are increasingly used to estimate air pollution exposure in epidemiologic studies. These models use air pollution measurements taken at a small set of locations and modeling based on geographical covariates for which data are available at all study participant locations. The process of LUR model development commonly includes a variable selection procedure. When LUR model predictions are used as explanatory variables in a model for a health outcome, measurement error can lead to bias of the regression coefficients and to inflation of their variance. In previous studies dealing with spatial predictions of air pollution, bias was shown to be small while most of the effect of measurement error was on the variance. In this study, we show that in realistic cases where LUR models are applied to health data, bias in health-effect estimates can be substantial. This bias depends on the number of air pollution measurement sites, the number of available predictors for model selection, and the amount of explainable variability in the true exposure. These results should be taken into account when interpreting health effects from studies that used LUR models.
Development of an Abbe Error Free Micro Coordinate Measuring Machine

Directory of Open Access Journals (Sweden)

Qiangxian Huang

2016-04-01

Full Text Available A micro Coordinate Measuring Machine (CMM with the measurement volume of 50 mm × 50 mm × 50 mm and measuring accuracy of about 100 nm (2σ has been developed. In this new micro CMM, an XYZ stage, which is driven by three piezo-motors in X, Y and Z directions, can achieve the drive resolution of about 1 nm and the stroke of more than 50 mm. In order to reduce the crosstalk among X-, Y- and Z-stages, a special mechanical structure, which is called co-planar stage, is introduced. The movement of the stage in each direction is detected by a laser interferometer. A contact type of probe is adopted for measurement. The center of the probe ball coincides with the intersection point of the measuring axes of the three laser interferometers. Therefore, the metrological system of the CMM obeys the Abbe principle in three directions and is free from Abbe error. The CMM is placed in an anti-vibration and thermostatic chamber for avoiding the influence of vibration and temperature fluctuation. A series of experimental results show that the measurement uncertainty within 40 mm among X, Y and Z directions is about 100 nm (2σ. The flatness of measuring face of the gauge block is also measured and verified the performance of the developed micro CMM.
SPACE-BORNE LASER ALTIMETER GEOLOCATION ERROR ANALYSIS

Directory of Open Access Journals (Sweden)

Y. Wang

2018-05-01

Full Text Available This paper reviews the development of space-borne laser altimetry technology over the past 40 years. Taking the ICESAT satellite as an example, a rigorous space-borne laser altimeter geolocation model is studied, and an error propagation equation is derived. The influence of the main error sources, such as the platform positioning error, attitude measurement error, pointing angle measurement error and range measurement error, on the geolocation accuracy of the laser spot are analysed by simulated experiments. The reasons for the different influences on geolocation accuracy in different directions are discussed, and to satisfy the accuracy of the laser control point, a design index for each error source is put forward.
Recurrent major depression and right hippocampal volume: A bivariate linkage and association study.

Science.gov (United States)

Mathias, Samuel R; Knowles, Emma E M; Kent, Jack W; McKay, D Reese; Curran, Joanne E; de Almeida, Marcio A A; Dyer, Thomas D; Göring, Harald H H; Olvera, Rene L; Duggirala, Ravi; Fox, Peter T; Almasy, Laura; Blangero, John; Glahn, David C

2016-01-01

Previous work has shown that the hippocampus is smaller in the brains of individuals suffering from major depressive disorder (MDD) than those of healthy controls. Moreover, right hippocampal volume specifically has been found to predict the probability of subsequent depressive episodes. This study explored the utility of right hippocampal volume as an endophenotype of recurrent MDD (rMDD). We observed a significant genetic correlation between the two traits in a large sample of Mexican American individuals from extended pedigrees (ρg = -0.34, p = 0.013). A bivariate linkage scan revealed a significant pleiotropic quantitative trait locus on chromosome 18p11.31-32 (LOD = 3.61). Bivariate association analysis conducted under the linkage peak revealed a variant (rs574972) within an intron of the gene SMCHD1 meeting the corrected significance level (χ(2) = 19.0, p = 7.4 × 10(-5)). Univariate association analyses of each phenotype separately revealed that the same variant was significant for right hippocampal volume alone, and also revealed a suggestively significant variant (rs12455524) within the gene DLGAP1 for rMDD alone. The results implicate right-hemisphere hippocampal volume as a possible endophenotype of rMDD, and in so doing highlight a potential gene of interest for rMDD risk. © 2015 Wiley Periodicals, Inc.
Comparison of Six Methods for the Detection of Causality in a Bivariate Time Series

Czech Academy of Sciences Publication Activity Database

Krakovská, A.; Jakubík, J.; Chvosteková, M.; Coufal, David; Jajcay, Nikola; Paluš, Milan

2018-01-01

Roč. 97, č. 4 (2018), č. článku 042207. ISSN 2470-0045 R&D Projects: GA MZd(CZ) NV15-33250A Institutional support: RVO:67985807 Keywords : comparative study * causality detection * bivariate models * Granger causality * transfer entropy * convergent cross mappings Impact factor: 2.366, year: 2016 https://journals.aps.org/pre/abstract/10.1103/PhysRevE.97.042207
Bivariate- distribution for transition matrix elements in Breit-Wigner to Gaussian domains of interacting particle systems.

Science.gov (United States)

Kota, V K B; Chavda, N D; Sahu, R

2006-04-01

Interacting many-particle systems with a mean-field one-body part plus a chaos generating random two-body interaction having strength lambda exhibit Poisson to Gaussian orthogonal ensemble and Breit-Wigner (BW) to Gaussian transitions in level fluctuations and strength functions with transition points marked by lambda = lambda c and lambda = lambda F, respectively; lambda F > lambda c. For these systems a theory for the matrix elements of one-body transition operators is available, as valid in the Gaussian domain, with lambda > lambda F, in terms of orbital occupation numbers, level densities, and an integral involving a bivariate Gaussian in the initial and final energies. Here we show that, using a bivariate-t distribution, the theory extends below from the Gaussian regime to the BW regime up to lambda = lambda c. This is well tested in numerical calculations for 6 spinless fermions in 12 single-particle states.
Systematic Error Study for ALICE charged-jet v2 Measurement

Energy Technology Data Exchange (ETDEWEB)

Heinz, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Soltz, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-07-18

We study the treatment of systematic errors in the determination of v₂ for charged jets in √ sNN = 2:76 TeV Pb-Pb collisions by the ALICE Collaboration. Working with the reported values and errors for the 0-5% centrality data we evaluate the Χ² according to the formulas given for the statistical and systematic errors, where the latter are separated into correlated and shape contributions. We reproduce both the Χ² and p-values relative to a null (zero) result. We then re-cast the systematic errors into an equivalent co-variance matrix and obtain identical results, demonstrating that the two methods are equivalent.
Discrete time interval measurement system: fundamentals, resolution and errors in the measurement of angular vibrations

International Nuclear Information System (INIS)

Gómez de León, F C; Meroño Pérez, P A

2010-01-01

The traditional method for measuring the velocity and the angular vibration in the shaft of rotating machines using incremental encoders is based on counting the pulses at given time intervals. This method is generically called the time interval measurement system (TIMS). A variant of this method that we have developed in this work consists of measuring the corresponding time of each pulse from the encoder and sampling the signal by means of an A/D converter as if it were an analog signal, that is to say, in discrete time. For this reason, we have denominated this method as the discrete time interval measurement system (DTIMS). This measurement system provides a substantial improvement in the precision and frequency resolution compared with the traditional method of counting pulses. In addition, this method permits modification of the width of some pulses in order to obtain a mark-phase on every lap. This paper explains the theoretical fundamentals of the DTIMS and its application for measuring the angular vibrations of rotating machines. It also displays the required relationship between the sampling rate of the signal, the number of pulses of the encoder and the rotating velocity in order to obtain the required resolution and to delimit the methodological errors in the measurement
THE BIVARIATE SIZE-LUMINOSITY RELATIONS FOR LYMAN BREAK GALAXIES AT z {approx} 4-5

Energy Technology Data Exchange (ETDEWEB)

Huang, Kuang-Han; Su, Jian [Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Ferguson, Henry C. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Ravindranath, Swara, E-mail: kuanghan@pha.jhu.edu [The Inter-University Center for Astronomy and Astrophysics, Pune University Campus, Pune 411007, Maharashtra (India)

2013-03-01

We study the bivariate size-luminosity distribution of Lyman break galaxies (LBGs) selected at redshifts around 4 and 5 in GOODS and the HUDF fields. We model the size-luminosity distribution as a combination of log-normal distribution (in size) and Schechter function (in luminosity), therefore it enables a more detailed study of the selection effects. We perform extensive simulations to quantify the dropout-selection completenesses and measurement biases and uncertainties in two-dimensional size and magnitude bins, and transform the theoretical size-luminosity distribution to the expected distribution for the observed data. Using maximum-likelihood estimator, we find that the Schechter function parameters for B {sub 435}-dropouts and are consistent with the values in the literature, but the size distributions are wider than expected from the angular momentum distribution of the underlying dark matter halos. The slope of the size-luminosity (RL) relation is similar to those found for local disk galaxies, but considerably shallower than local early-type galaxies.
THE BIVARIATE SIZE-LUMINOSITY RELATIONS FOR LYMAN BREAK GALAXIES AT z ∼ 4-5

International Nuclear Information System (INIS)

Huang, Kuang-Han; Su, Jian; Ferguson, Henry C.; Ravindranath, Swara

2013-01-01

We study the bivariate size-luminosity distribution of Lyman break galaxies (LBGs) selected at redshifts around 4 and 5 in GOODS and the HUDF fields. We model the size-luminosity distribution as a combination of log-normal distribution (in size) and Schechter function (in luminosity), therefore it enables a more detailed study of the selection effects. We perform extensive simulations to quantify the dropout-selection completenesses and measurement biases and uncertainties in two-dimensional size and magnitude bins, and transform the theoretical size-luminosity distribution to the expected distribution for the observed data. Using maximum-likelihood estimator, we find that the Schechter function parameters for B 435 -dropouts and are consistent with the values in the literature, but the size distributions are wider than expected from the angular momentum distribution of the underlying dark matter halos. The slope of the size-luminosity (RL) relation is similar to those found for local disk galaxies, but considerably shallower than local early-type galaxies.
Effect of error in crack length measurement on maximum load fracture toughness of Zr-2.5Nb pressure tube material

International Nuclear Information System (INIS)

Bind, A.K.; Sunil, Saurav; Singh, R.N.; Chakravartty, J.K.

2016-03-01

Recently it was found that maximum load toughness (J max ) for Zr-2.5Nb pressure tube material was practically unaffected by error in Δ a . To check the sensitivity of the J max to error in Δ a measurement, the J max was calculated assuming no crack growth up to the maximum load (P max ) for as received and hydrogen charged Zr-2.5Nb pressure tube material. For load up to the P max , the J values calculated assuming no crack growth (J NC ) were slightly higher than that calculated based on Δ a measured using DCPD technique (JDCPD). In general, error in the J calculation found to be increased exponentially with Δ a . The error in J max calculation was increased with an increase in Δ a and a decrease in J max . Based on deformation theory of J, an analytic criterion was developed to check the insensitivity of the J max to error in Δ a . There was very good linear relation was found between the J max calculated based on Δ a measured using DCPD technique and the J max calculated assuming no crack growth. This relation will be very useful to calculate J max without measuring the crack growth during fracture test especially for irradiated material. (author)
On the construction of bivariate exponential distributions with an arbitrary correlation coefficient

DEFF Research Database (Denmark)

Bladt, Mogens; Nielsen, Bo Friis

In this paper we use a concept of multivariate phase-type distributions to define a class of bivariate exponential distributions. This class has the following three appealing properties. Firstly, we may construct a pair of exponentially distributed random variables with any feasible correlation...... coefficient (also negative). Secondly, the class satisfies that any linear combination (projection) of the marginal random variables is a phase {type distributions, The latter property is potentially important for the development hypothesis testing in linear models. Thirdly, it is very easy to simulate...
Study of principle error sources in gamma spectrometry. Application to cross sections measurement

International Nuclear Information System (INIS)

Majah, M. Ibn.

1985-01-01

The principle error sources in gamma spectrometry have been studied in purpose to measure cross sections with great precision. Three error sources have been studied: dead time and pile up which depend on counting rate, and coincidence effect that depends on the disintegration scheme of the radionuclide in question. A constant frequency pulse generator has been used to correct the counting loss due to dead time and pile up in cases of long and short disintegration periods. The loss due to coincidence effect can reach 25% and over, depending on the disintegration scheme and on the distance source-detector. After establishing the correction formula and verifying its validity for four examples: iron 56, scandium 48, antimony 120 and gold 196 m, an application has been done by measuring cross sections of nuclear reactions that lead to long disintegration periods which need short distance source-detector counting and thus correcting the loss due to dead time effect, pile up and coincidence effect. 16 refs., 45 figs., 25 tabs. (author)
Measuring systolic arterial blood pressure. Possible errors from extension tubes or disposable transducer domes.

Science.gov (United States)

Rothe, C F; Kim, K C

1980-11-01

The purpose of this study was to evaluate the magnitude of possible error in the measurement of systolic blood pressure if disposable, built-in diaphragm, transducer domes or long extension tubes between the patient and pressure transducer are used. Sinusoidal or arterial pressure patterns were generated with specially designed equipment. With a long extension tube or trapped air bubbles, the resonant frequency of the catheter system was reduced so that the arterial pulse was amplified as it acted on the transducer and, thus, gave an erroneously high systolic pressure measurement. The authors found this error to be as much as 20 mm Hg. Trapped air bubbles, not stopcocks or connections, per se, lead to poor fidelity. The utility of a continuous catheter flush system (Sorenson, Intraflow) to estimate the resonant frequency and degree of damping of a catheter-transducer system is described, as are possibly erroneous conclusions. Given a rough estimate of the resonant frequency of a catheter-transducer system and the magnitude of overshoot in response to a pulse, the authors present a table to predict the magnitude of probable error. These studies confirm the variability and unreliability of static calibration that may occur using some safety diaphragm domes and show that the system frequency response is decreased if air bubbles are trapped between the diaphragms. The authors conclude that regular procedures should be established to evaluate the accuracy of the pressure measuring systems in use, the transducer should be placed as close to the patient as possible, the air bubbles should be assiduously eliminated from the system.
Different grades MEMS accelerometers error characteristics

Science.gov (United States)

Pachwicewicz, M.; Weremczuk, J.

2017-08-01

The paper presents calibration effects of two different MEMS accelerometers of different price and quality grades and discusses different accelerometers errors types. The calibration for error determining is provided by reference centrifugal measurements. The design and measurement errors of the centrifuge are discussed as well. It is shown that error characteristics of the sensors are very different and it is not possible to use simple calibration methods presented in the literature in both cases.

Einstein's error

International Nuclear Information System (INIS)

Winterflood, A.H.

1980-01-01

In discussing Einstein's Special Relativity theory it is claimed that it violates the principle of relativity itself and that an anomalous sign in the mathematics is found in the factor which transforms one inertial observer's measurements into those of another inertial observer. The apparent source of this error is discussed. Having corrected the error a new theory, called Observational Kinematics, is introduced to replace Einstein's Special Relativity. (U.K.)
A first look at measurement error on FIA plots using blind plots in the Pacific Northwest

Science.gov (United States)

Susanna Melson; David Azuma; Jeremy S. Fried

2002-01-01

Measurement error in the Forest Inventory and Analysis work of the Pacific Northwest Station was estimated with a recently implemented blind plot measurement protocol. A small subset of plots was revisited by a crew having limited knowledge of the first crew's measurements. This preliminary analysis of the first 18 months' blind plot data indicates that...
A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League

NARCIS (Netherlands)

Koopman, S.J.; Lit, R.

2015-01-01

Summary: We develop a statistical model for the analysis and forecasting of football match results which assumes a bivariate Poisson distribution with intensity coefficients that change stochastically over time. The dynamic model is a novelty in the statistical time series analysis of match results
Reliability and Measurement Error of Tensiomyography to Assess Mechanical Muscle Function: A Systematic Review.

Science.gov (United States)

Martín-Rodríguez, Saúl; Loturco, Irineu; Hunter, Angus M; Rodríguez-Ruiz, David; Munguia-Izquierdo, Diego

2017-12-01

Martín-Rodríguez, S, Loturco, I, Hunter, AM, Rodríguez-Ruiz, D, and Munguia-Izquierdo, D. Reliability and measurement error of tensiomyography to assess mechanical muscle function: A systematic review. J Strength Cond Res 31(12): 3524-3536, 2017-Interest in studying mechanical skeletal muscle function through tensiomyography (TMG) has increased in recent years. This systematic review aimed to (a) report the reliability and measurement error of all TMG parameters (i.e., maximum radial displacement of the muscle belly [Dm], contraction time [Tc], delay time [Td], half-relaxation time [½ Tr], and sustained contraction time [Ts]) and (b) to provide critical reflection on how to perform accurate and appropriate measurements for informing clinicians, exercise professionals, and researchers. A comprehensive literature search was performed of the Pubmed, Scopus, Science Direct, and Cochrane databases up to July 2017. Eight studies were included in this systematic review. Meta-analysis could not be performed because of the low quality of the evidence of some studies evaluated. Overall, the review of the 9 studies involving 158 participants revealed high relative reliability (intraclass correlation coefficient [ICC]) for Dm (0.91-0.99); moderate-to-high ICC for Ts (0.80-0.96), Tc (0.70-0.98), and ½ Tr (0.77-0.93); and low-to-high ICC for Td (0.60-0.98), independently of the evaluated muscles. In addition, absolute reliability (coefficient of variation [CV]) was low for all TMG parameters except for ½ Tr (CV = >20%), whereas measurement error indexes were high for this parameter. In conclusion, this study indicates that 3 of the TMG parameters (Dm, Td, and Tc) are highly reliable, whereas ½ Tr demonstrate insufficient reliability, and thus should not be used in future studies.
A permutation test to analyse systematic bias and random measurement errors of medical devices via boosting location and scale models.

Science.gov (United States)

Mayr, Andreas; Schmid, Matthias; Pfahlberg, Annette; Uter, Wolfgang; Gefeller, Olaf

2017-06-01

Measurement errors of medico-technical devices can be separated into systematic bias and random error. We propose a new method to address both simultaneously via generalized additive models for location, scale and shape (GAMLSS) in combination with permutation tests. More precisely, we extend a recently proposed boosting algorithm for GAMLSS to provide a test procedure to analyse potential device effects on the measurements. We carried out a large-scale simulation study to provide empirical evidence that our method is able to identify possible sources of systematic bias as well as random error under different conditions. Finally, we apply our approach to compare measurements of skin pigmentation from two different devices in an epidemiological study.
Visual acuity measures do not reliably detect childhood refractive error--an epidemiological study.

Directory of Open Access Journals (Sweden)

Lisa O'Donoghue

Full Text Available PURPOSE: To investigate the utility of uncorrected visual acuity measures in screening for refractive error in white school children aged 6-7-years and 12-13-years. METHODS: The Northern Ireland Childhood Errors of Refraction (NICER study used a stratified random cluster design to recruit children from schools in Northern Ireland. Detailed eye examinations included assessment of logMAR visual acuity and cycloplegic autorefraction. Spherical equivalent refractive data from the right eye were used to classify significant refractive error as myopia of at least 1DS, hyperopia as greater than +3.50DS and astigmatism as greater than 1.50DC, whether it occurred in isolation or in association with myopia or hyperopia. RESULTS: Results are presented from 661 white 12-13-year-old and 392 white 6-7-year-old school-children. Using a cut-off of uncorrected visual acuity poorer than 0.20 logMAR to detect significant refractive error gave a sensitivity of 50% and specificity of 92% in 6-7-year-olds and 73% and 93% respectively in 12-13-year-olds. In 12-13-year-old children a cut-off of poorer than 0.20 logMAR had a sensitivity of 92% and a specificity of 91% in detecting myopia and a sensitivity of 41% and a specificity of 84% in detecting hyperopia. CONCLUSIONS: Vision screening using logMAR acuity can reliably detect myopia, but not hyperopia or astigmatism in school-age children. Providers of vision screening programs should be cognisant that where detection of uncorrected hyperopic and/or astigmatic refractive error is an aspiration, current UK protocols will not effectively deliver.
Climatologies from satellite measurements: the impact of orbital sampling on the standard error of the mean

Directory of Open Access Journals (Sweden)

M. Toohey

2013-04-01

Full Text Available Climatologies of atmospheric observations are often produced by binning measurements according to latitude and calculating zonal means. The uncertainty in these climatological means is characterised by the standard error of the mean (SEM. However, the usual estimator of the SEM, i.e., the sample standard deviation divided by the square root of the sample size, holds only for uncorrelated randomly sampled measurements. Measurements of the atmospheric state along a satellite orbit cannot always be considered as independent because (a the time-space interval between two nearest observations is often smaller than the typical scale of variations in the atmospheric state, and (b the regular time-space sampling pattern of a satellite instrument strongly deviates from random sampling. We have developed a numerical experiment where global chemical fields from a chemistry climate model are sampled according to real sampling patterns of satellite-borne instruments. As case studies, the model fields are sampled using sampling patterns of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS and Atmospheric Chemistry Experiment Fourier-Transform Spectrometer (ACE-FTS satellite instruments. Through an iterative subsampling technique, and by incorporating information on the random errors of the MIPAS and ACE-FTS measurements, we produce empirical estimates of the standard error of monthly mean zonal mean model O3 in 5° latitude bins. We find that generally the classic SEM estimator is a conservative estimate of the SEM, i.e., the empirical SEM is often less than or approximately equal to the classic estimate. Exceptions occur only when natural variability is larger than the random measurement error, and specifically in instances where the zonal sampling distribution shows non-uniformity with a similar zonal structure as variations in the sampled field, leading to maximum sensitivity to arbitrary phase shifts between the sample distribution and
Bivariate pointing movements on large touch screens: investigating the validity of a refined Fitts' Law.

Science.gov (United States)

Bützler, Jennifer; Vetter, Sebastian; Jochems, Nicole; Schlick, Christopher M

2012-01-01

On the basis of three empirical studies Fitts' Law was refined for bivariate pointing tasks on large touch screens. In the first study different target width parameters were investigated. The second study considered the effect of the motion angle. Based on the results of the two studies a refined model for movement time in human-computer interaction was formulated. A third study, which is described here in detail, concerns the validation of the refined model. For the validation study 20 subjects had to execute a bivariate pointing task on a large touch screen. In the experimental task 250 rectangular target objects were displayed at a randomly chosen position on the screen covering a broad range of ID values (ID= [1.01; 4.88]). Compared to existing refinements of Fitts' Law, the new model shows highest predictive validity. A promising field of application of the model is the ergonomic design and evaluation of project management software. By using the refined model, software designers can calculate a priori the appropriate angular position and the size of buttons, menus or icons.
Measurement errors in network load measurement: Effects on lead management and accounting. Messfehler bei der Netzlasterfassung: Einfluss auf Lastregelung und Leistungsverrechnung

Energy Technology Data Exchange (ETDEWEB)

Bunten, B. (Teilbereich Lastfuehrung, ABB Netzleittechnik GmbH, Ladenburg (Germany)); Dib, R.N. (Fachhochschule Giessen-Friedberg, Bereich Elektrische Energietechnik, Friedberg (Germany))

1994-05-16

In electric power supply systems continuous power measurement in the delivery points is necessary both for the purpose of load-management and for energy and power accounting. Electricity meters with pulse output points are commonly used for both applications today. The authors quantify the resulting errors in peak load measurement and load management as a function of the main influencing factors. (orig.)
The Effect of Error Correlation on Interfactor Correlation in Psychometric Measurement

Science.gov (United States)

Westfall, Peter H.; Henning, Kevin S. S.; Howell, Roy D.

2012-01-01

This article shows how interfactor correlation is affected by error correlations. Theoretical and practical justifications for error correlations are given, and a new equivalence class of models is presented to explain the relationship between interfactor correlation and error correlations. The class allows simple, parsimonious modeling of error…
Selection effects in the bivariate brightness distribution for spiral galaxies

International Nuclear Information System (INIS)

Phillipps, S.; Disney, M.

1986-01-01

The joint distribution of total luminosity and characteristic surface brightness (the bivariate brightness distribution) is investigated for a complete sample of spiral galaxies in the Virgo cluster. The influence of selection and physical limits of various kinds on the apparent distribution are detailed. While the distribution of surface brightness for bright galaxies may be genuinely fairly narrow, faint galaxies exist right across the (quite small) range of accessible surface brightnesses so no statement can be made about the true extent of the distribution. The lack of high surface brightness bright galaxies in the Virgo sample relative to an overall RC2 sample (mostly field galaxies) supports the contention that the star-formation rate is reduced in the inner region of the cluster for environmental reasons. (author)
Can the bivariate Hurst exponent be higher than an average of the separate Hurst exponents?

Czech Academy of Sciences Publication Activity Database

Krištoufek, Ladislav

2015-01-01

Roč. 431, č. 1 (2015), s. 124-127 ISSN 0378-4371 R&D Projects: GA ČR(CZ) GP14-11402P Institutional support: RVO:67985556 Keywords : Correlations * Power- law cross-correlations * Bivariate Hurst exponent * Spectrum coherence Subject RIV: AH - Economics Impact factor: 1.785, year: 2015 http://library.utia.cas.cz/separaty/2015/E/kristoufek-0452314.pdf
Mismeasurement and the resonance of strong confounders: correlated errors.

Science.gov (United States)

Marshall, J R; Hastrup, J L; Ross, J S

1999-07-01

Confounding in epidemiology, and the limits of standard methods of control for an imperfectly measured confounder, have been understood for some time. However, most treatments of this problem are based on the assumption that errors of measurement in confounding and confounded variables are independent. This paper considers the situation in which a strong risk factor (confounder) and an inconsequential but suspected risk factor (confounded) are each measured with errors that are correlated; the situation appears especially likely to occur in the field of nutritional epidemiology. Error correlation appears to add little to measurement error as a source of bias in estimating the impact of a strong risk factor: it can add to, diminish, or reverse the bias induced by measurement error in estimating the impact of the inconsequential risk factor. Correlation of measurement errors can add to the difficulty involved in evaluating structures in which confounding and measurement error are present. In its presence, observed correlations among risk factors can be greater than, less than, or even opposite to the true correlations. Interpretation of multivariate epidemiologic structures in which confounding is likely requires evaluation of measurement error structures, including correlations among measurement errors.
Parts of the Whole: Error Estimation for Science Students

Directory of Open Access Journals (Sweden)

Dorothy Wallace

2017-01-01

Full Text Available It is important for science students to understand not only how to estimate error sizes in measurement data, but also to see how these errors contribute to errors in conclusions they may make about the data. Relatively small errors in measurement, errors in assumptions, and roundoff errors in computation may result in large error bounds on computed quantities of interest. In this column, we look closely at a standard method for measuring the volume of cancer tumor xenografts to see how small errors in each of these three factors may contribute to relatively large observed errors in recorded tumor volumes.
A note on errors and signal to noise ratio of binary cross-correlation measurements of system impulse response

International Nuclear Information System (INIS)

Cummins, J.D.

1964-02-01

The sources of error in the measurement of system impulse response using test signals of a discrete interval binary nature are considered. Methods of correcting for the errors due to theoretical imperfections are given and the variance of the estimate of the system impulse response due to random noise is determined. Several topics related to the main topic are considered e.g. determination of a theoretical model from experimental results. General conclusions about the magnitude of the errors due to the theoretical imperfections are made. (author)
A note on errors and signal to noise ratio of binary cross-correlation measurements of system impulse response

Energy Technology Data Exchange (ETDEWEB)

Cummins, J D [Dynamics Group, Control and Instrumentation Division, Atomic Energy Establishment, Winfrith, Dorchester, Dorset (United Kingdom)

1964-02-15

The sources of error in the measurement of system impulse response using test signals of a discrete interval binary nature are considered. Methods of correcting for the errors due to theoretical imperfections are given and the variance of the estimate of the system impulse response due to random noise is determined. Several topics related to the main topic are considered e.g. determination of a theoretical model from experimental results. General conclusions about the magnitude of the errors due to the theoretical imperfections are made. (author)
Error Rates of M-PAM and M-QAM in Generalized Fading and Generalized Gaussian Noise Environments

KAUST Repository

Soury, Hamza

2013-07-01

This letter investigates the average symbol error probability (ASEP) of pulse amplitude modulation and quadrature amplitude modulation coherent signaling over flat fading channels subject to additive white generalized Gaussian noise. The new ASEP results are derived in a generic closed-form in terms of the Fox H function and the bivariate Fox H function for the extended generalized-K fading case. The utility of this new general closed-form is that it includes some special fading distributions, like the Generalized-K, Nakagami-m, and Rayleigh fading and special noise distributions such as Gaussian and Laplacian. Some of these special cases are also treated and are shown to yield simplified results.
A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests.

Science.gov (United States)

Simoneau, Gabrielle; Levis, Brooke; Cuijpers, Pim; Ioannidis, John P A; Patten, Scott B; Shrier, Ian; Bombardier, Charles H; de Lima Osório, Flavia; Fann, Jesse R; Gjerdingen, Dwenda; Lamers, Femke; Lotrakul, Manote; Löwe, Bernd; Shaaban, Juwita; Stafford, Lesley; van Weert, Henk C P M; Whooley, Mary A; Wittkampf, Karin A; Yeung, Albert S; Thombs, Brett D; Benedetti, Andrea

2017-11-01

Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models.

Science.gov (United States)

BackgroundExposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of a...
Errors and limits in the determination of plasma electron density by measuring the absolute values of the emitted continuum radiation intensity

International Nuclear Information System (INIS)

Bilbao, L.; Bruzzone, H.; Grondona, D.

1994-01-01

The reliable determination of a plasma electron structure requires a good knowledge of the errors affecting the employed technique. A technique based on the measurements of the absolute light intensity emitted by travelling plasma structures in plasma focus devices has been used, but it can be easily modified to other geometries and even to stationary plasma structures with time-varying plasma densities. The purpose of this work is to discuss in some detail the errors and limits of this technique. Three separate errors are shown: the minimum size of the density structure that can be resolved, an overall error in the measurements themselves, and an uncertainty in the shape of the density profile. (author)

Z-boson-exchange contributions to the luminosity measurements at LEP and c.m.s.-energy-dependent theoretical errors

International Nuclear Information System (INIS)

Beenakker, W.; Martinez, M.; Pietrzyk, B.

1995-02-01

The precision of the calculation of Z-boson-exchange contributions to the luminosity measurements at LEP is studied for both the first and second generation of LEP luminosity detectors. It is shown that the theoretical errors associated with these contributions are sufficiently small so that the high-precision measurements at LEP, based on the second generation of luminosity detectors, are not limited. The same is true for the c.m.s.-energy-dependent theoretical errors of the Z line-shape formulae. (author) 19 refs.; 3 figs.; 7 tabs
Characterization of model errors in the calculation of tangent heights for atmospheric infrared limb measurements

Directory of Open Access Journals (Sweden)

M. Ridolfi

2014-12-01

Full Text Available We review the main factors driving the calculation of the tangent height of spaceborne limb measurements: the ray-tracing method, the refractive index model and the assumed atmosphere. We find that commonly used ray tracing and refraction models are very accurate, at least in the mid-infrared. The factor with largest effect in the tangent height calculation is the assumed atmosphere. Using a climatological model in place of the real atmosphere may cause tangent height errors up to ± 200 m. Depending on the adopted retrieval scheme, these errors may have a significant impact on the derived profiles.
Relay-aided free-space optical communications using α - μ distribution over atmospheric turbulence channels with misalignment errors

Science.gov (United States)

Upadhya, Abhijeet; Dwivedi, Vivek K.; Singh, G.

2018-06-01

In this paper, we have analyzed the performance of dual hop radio frequency (RF)/free-space optical (FSO) fixed gain relay environment confined by atmospheric turbulence induced fading channel over FSO link and modeled using α - μ distribution. The RF hop of the amplify-and-forward scheme undergoes the Rayleigh fading and the proposed system model also considers the pointing error effect on the FSO link. A novel and accurate mathematical expression of the probability density function for a FSO link experiencing α - μ distributed atmospheric turbulence in the presence of pointing error is derived. Further, we have presented analytical expressions of outage probability and bit error rate in terms of Meijer-G function. In addition to this, a useful and mathematically tractable closed-form expression for the end-to-end ergodic capacity of the dual hop scheme in terms of bivariate Fox's H function is derived. The atmospheric turbulence, misalignment errors and various binary modulation schemes for intensity modulation on optical wireless link are considered to yield the results. Finally, we have analyzed each of the three performance metrics for high SNR in order to represent them in terms of elementary functions and the achieved analytical results are supported by computer-based simulations.
Uncertainty quantification and error analysis

Energy Technology Data Exchange (ETDEWEB)

Higdon, Dave M [Los Alamos National Laboratory; Anderson, Mark C [Los Alamos National Laboratory; Habib, Salman [Los Alamos National Laboratory; Klein, Richard [Los Alamos National Laboratory; Berliner, Mark [OHIO STATE UNIV.; Covey, Curt [LLNL; Ghattas, Omar [UNIV OF TEXAS; Graziani, Carlo [UNIV OF CHICAGO; Seager, Mark [LLNL; Sefcik, Joseph [LLNL; Stark, Philip [UC/BERKELEY; Stewart, James [SNL

2010-01-01

UQ studies all sources of error and uncertainty, including: systematic and stochastic measurement error; ignorance; limitations of theoretical models; limitations of numerical representations of those models; limitations on the accuracy and reliability of computations, approximations, and algorithms; and human error. A more precise definition for UQ is suggested below.
Methods for determining the effect of flatness deviations, eccentricity and pyramidal errors on angle measurements

CSIR Research Space (South Africa)

Kruger, OA

2000-01-01

Full Text Available on face-to-face angle measurements. The results show that flatness and eccentricity deviations have less effect on angle measurements than do pyramidal errors. 1. Introduction Polygons and angle blocks are the most important transfer standards in the field... of angle metrology. Polygons are used by national metrology institutes (NMIs) as transfer standards to industry, where they are used in conjunction with autocollimators to calibrate index tables, rotary tables and other forms of angle- measuring equipment...
Errors in clinical laboratories or errors in laboratory medicine?

Science.gov (United States)

Plebani, Mario

2006-01-01

Laboratory testing is a highly complex process and, although laboratory services are relatively safe, they are not as safe as they could or should be. Clinical laboratories have long focused their attention on quality control methods and quality assessment programs dealing with analytical aspects of testing. However, a growing body of evidence accumulated in recent decades demonstrates that quality in clinical laboratories cannot be assured by merely focusing on purely analytical aspects. The more recent surveys on errors in laboratory medicine conclude that in the delivery of laboratory testing, mistakes occur more frequently before (pre-analytical) and after (post-analytical) the test has been performed. Most errors are due to pre-analytical factors (46-68.2% of total errors), while a high error rate (18.5-47% of total errors) has also been found in the post-analytical phase. Errors due to analytical problems have been significantly reduced over time, but there is evidence that, particularly for immunoassays, interference may have a serious impact on patients. A description of the most frequent and risky pre-, intra- and post-analytical errors and advice on practical steps for measuring and reducing the risk of errors is therefore given in the present paper. Many mistakes in the Total Testing Process are called "laboratory errors", although these may be due to poor communication, action taken by others involved in the testing process (e.g., physicians, nurses and phlebotomists), or poorly designed processes, all of which are beyond the laboratory's control. Likewise, there is evidence that laboratory information is only partially utilized. A recent document from the International Organization for Standardization (ISO) recommends a new, broader definition of the term "laboratory error" and a classification of errors according to different criteria. In a modern approach to total quality, centered on patients' needs and satisfaction, the risk of errors and mistakes
Dual-Hop FSO Transmission Systems over Gamma-Gamma Turbulence with Pointing Errors

KAUST Repository

Zedini, Emna

2016-11-18

In this paper, we analyze the end-to-end performance of dual-hop free-space optical (FSO) fixed gain relaying systems under heterodyne detection and intensity modulation with direct detection techniques in the presence of atmospheric turbulence as well as pointing errors. In particular, we derive the cumulative distribution function (CDF) of the end-to-end signal-to-noise ratio (SNR) in exact closed-form in terms of the bivariate Fox’s H function. Capitalizing on this CDF expression, novel closed-form expressions for the outage probability, the average bit-error rate (BER) for different modulation schemes, and the ergodic capacity of dual-hop FSO transmission systems are presented. Moreover, we present very tight asymptotic results for the outage probability and the average BER at high SNR regime in terms of simple elementary functions and we derive the diversity order of the considered system. By using dual-hop FSO relaying, we demonstrate a better system performance as compared to the single FSO link. Numerical and Monte-Carlo simulation results are provided to verify the accuracy of the newly proposed results, and a perfect agreement is observed.
A Bivariate Mixture Model for Natural Antibody Levels to Human Papillomavirus Types 16 and 18: Baseline Estimates for Monitoring the Herd Effects of Immunization.

Directory of Open Access Journals (Sweden)

Margaretha A Vink

Full Text Available Post-vaccine monitoring programs for human papillomavirus (HPV have been introduced in many countries, but HPV serology is still an underutilized tool, partly owing to the weak antibody response to HPV infection. Changes in antibody levels among non-vaccinated individuals could be employed to monitor herd effects of immunization against HPV vaccine types 16 and 18, but inference requires an appropriate statistical model. The authors developed a four-component bivariate mixture model for jointly estimating vaccine-type seroprevalence from correlated antibody responses against HPV16 and -18 infections. This model takes account of the correlation between HPV16 and -18 antibody concentrations within subjects, caused e.g. by heterogeneity in exposure level and immune response. The model was fitted to HPV16 and -18 antibody concentrations as measured by a multiplex immunoassay in a large serological survey (3,875 females carried out in the Netherlands in 2006/2007, before the introduction of mass immunization. Parameters were estimated by Bayesian analysis. We used the deviance information criterion for model selection; performance of the preferred model was assessed through simulation. Our analysis uncovered elevated antibody concentrations in doubly as compared to singly seropositive individuals, and a strong clustering of HPV16 and -18 seropositivity, particularly around the age of sexual debut. The bivariate model resulted in a more reliable classification of singly and doubly seropositive individuals than achieved by a combination of two univariate models, and suggested a higher pre-vaccine HPV16 seroprevalence than previously estimated. The bivariate mixture model provides valuable baseline estimates of vaccine-type seroprevalence and may prove useful in seroepidemiologic assessment of the herd effects of HPV vaccination.
Comparing alternative approaches to measuring the geographical accessibility of urban health services: Distance types and aggregation-error issues

Directory of Open Access Journals (Sweden)

Riva Mylène

2008-02-01

Full Text Available Abstract Background Over the past two decades, geographical accessibility of urban resources for population living in residential areas has received an increased focus in urban health studies. Operationalising and computing geographical accessibility measures depend on a set of four parameters, namely definition of residential areas, a method of aggregation, a measure of accessibility, and a type of distance. Yet, the choice of these parameters may potentially generate different results leading to significant measurement errors. The aim of this paper is to compare discrepancies in results for geographical accessibility of selected health care services for residential areas (i.e. census tracts computed using different distance types and aggregation methods. Results First, the comparison of distance types demonstrates that Cartesian distances (Euclidean and Manhattan distances are strongly correlated with more accurate network distances (shortest network and shortest network time distances across the metropolitan area (Pearson correlation greater than 0.95. However, important local variations in correlation between Cartesian and network distances were observed notably in suburban areas where Cartesian distances were less precise. Second, the choice of the aggregation method is also important: in comparison to the most accurate aggregation method (population-weighted mean of the accessibility measure for census blocks within census tracts, accessibility measures computed from census tract centroids, though not inaccurate, yield important measurement errors for 5% to 10% of census tracts. Conclusion Although errors associated to the choice of distance types and aggregation method are only important for about 10% of census tracts located mainly in suburban areas, we should not avoid using the best estimation method possible for evaluating geographical accessibility. This is especially so if these measures are to be included as a dimension of the
Application of bivariate mapping for hydrological classification and analysis of temporal change and scale effects in Switzerland

NARCIS (Netherlands)

Speich, Matthias J.R.; Bernhard, Luzi; Teuling, Ryan; Zappa, Massimiliano

2015-01-01

Hydrological classification schemes are important tools for assessing the impacts of a changing climate on the hydrology of a region. In this paper, we present bivariate mapping as a simple means of classifying hydrological data for a quantitative and qualitative assessment of temporal change.
An Empirical State Error Covariance Matrix Orbit Determination Example

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Frisbee, Joseph H., Jr.

2015-01-01

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance
The error analysis of Lobular and segmental division of right liver by volume measurement.

Science.gov (United States)

Zhang, Jianfei; Lin, Weigang; Chi, Yanyan; Zheng, Nan; Xu, Qiang; Zhang, Guowei; Yu, Shengbo; Li, Chan; Wang, Bin; Sui, Hongjin

2017-07-01

The aim of this study is to explore the inconsistencies between right liver volume as measured by imaging and the actual anatomical appearance of the right lobe. Five healthy donated livers were studied. The liver slices were obtained with hepatic segments multicolor-infused through the portal vein. In the slices, the lobes were divided by two methods: radiological landmarks and real anatomical boundaries. The areas of the right anterior lobe (RAL) and right posterior lobe (RPL) on each slice were measured using Photoshop CS5 and AutoCAD, and the volumes of the two lobes were calculated. There was no statistically significant difference between the volumes of the RAL or RPL as measured by the radiological landmarks (RL) and anatomical boundaries (AB) methods. However, the curves of the square error value of the RAL and RPL measured using CT showed that the three lowest points were at the cranial, intermediate, and caudal levels. The U- or V-shaped curves of the square error rate of the RAL and RPL revealed that the lowest value is at the intermediate level and the highest at the cranial and caudal levels. On CT images, less accurate landmarks were used to divide the RAL and RPL at the cranial and caudal layers. The measured volumes of hepatic segments VIII and VI would be less than their true values, and the measured volumes of hepatic segments VII and V would be greater than their true values, according to radiological landmarks. Clin. Anat. 30:585-590, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Tail-weighted dependence measures with limit being the tail dependence coefficient

KAUST Repository

Lee, David

2017-12-02

For bivariate continuous data, measures of monotonic dependence are based on the rank transformations of the two variables. For bivariate extreme value copulas, there is a family of estimators (Formula presented.), for (Formula presented.), of the extremal coefficient, based on a transform of the absolute difference of the α power of the ranks. In the case of general bivariate copulas, we obtain the probability limit (Formula presented.) of (Formula presented.) as the sample size goes to infinity and show that (i) (Formula presented.) for (Formula presented.) is a measure of central dependence with properties similar to Kendall\\'s tau and Spearman\\'s rank correlation, (ii) (Formula presented.) is a tail-weighted dependence measure for large α, and (iii) the limit as (Formula presented.) is the upper tail dependence coefficient. We obtain asymptotic properties for the rank-based measure (Formula presented.) and estimate tail dependence coefficients through extrapolation on (Formula presented.). A data example illustrates the use of the new dependence measures for tail inference.
Tail-weighted dependence measures with limit being the tail dependence coefficient

KAUST Repository

Lee, David; Joe, Harry; Krupskii, Pavel

2017-01-01

For bivariate continuous data, measures of monotonic dependence are based on the rank transformations of the two variables. For bivariate extreme value copulas, there is a family of estimators (Formula presented.), for (Formula presented.), of the extremal coefficient, based on a transform of the absolute difference of the α power of the ranks. In the case of general bivariate copulas, we obtain the probability limit (Formula presented.) of (Formula presented.) as the sample size goes to infinity and show that (i) (Formula presented.) for (Formula presented.) is a measure of central dependence with properties similar to Kendall's tau and Spearman's rank correlation, (ii) (Formula presented.) is a tail-weighted dependence measure for large α, and (iii) the limit as (Formula presented.) is the upper tail dependence coefficient. We obtain asymptotic properties for the rank-based measure (Formula presented.) and estimate tail dependence coefficients through extrapolation on (Formula presented.). A data example illustrates the use of the new dependence measures for tail inference.
Testing and Estimating Shape-Constrained Nonparametric Density and Regression in the Presence of Measurement Error

KAUST Repository

Carroll, Raymond J.

2011-03-01

In many applications we can expect that, or are interested to know if, a density function or a regression curve satisfies some specific shape constraints. For example, when the explanatory variable, X, represents the value taken by a treatment or dosage, the conditional mean of the response, Y , is often anticipated to be a monotone function of X. Indeed, if this regression mean is not monotone (in the appropriate direction) then the medical or commercial value of the treatment is likely to be significantly curtailed, at least for values of X that lie beyond the point at which monotonicity fails. In the case of a density, common shape constraints include log-concavity and unimodality. If we can correctly guess the shape of a curve, then nonparametric estimators can be improved by taking this information into account. Addressing such problems requires a method for testing the hypothesis that the curve of interest satisfies a shape constraint, and, if the conclusion of the test is positive, a technique for estimating the curve subject to the constraint. Nonparametric methodology for solving these problems already exists, but only in cases where the covariates are observed precisely. However in many problems, data can only be observed with measurement errors, and the methods employed in the error-free case typically do not carry over to this error context. In this paper we develop a novel approach to hypothesis testing and function estimation under shape constraints, which is valid in the context of measurement errors. Our method is based on tilting an estimator of the density or the regression mean until it satisfies the shape constraint, and we take as our test statistic the distance through which it is tilted. Bootstrap methods are used to calibrate the test. The constrained curve estimators that we develop are also based on tilting, and in that context our work has points of contact with methodology in the error-free case.
Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine Learning for Modeling PM2.5 in the Northeastern USA

Directory of Open Access Journals (Sweden)

Allan C. Just

2018-05-01

Full Text Available Satellite-derived estimates of aerosol optical depth (AOD are key predictors in particulate air pollution models. The multi-step retrieval algorithms that estimate AOD also produce quality control variables but these have not been systematically used to address the measurement error in AOD. We compare three machine-learning methods: random forests, gradient boosting, and extreme gradient boosting (XGBoost to characterize and correct measurement error in the Multi-Angle Implementation of Atmospheric Correction (MAIAC 1 × 1 km AOD product for Aqua and Terra satellites across the Northeastern/Mid-Atlantic USA versus collocated measures from 79 ground-based AERONET stations over 14 years. Models included 52 quality control, land use, meteorology, and spatially-derived features. Variable importance measures suggest relative azimuth, AOD uncertainty, and the AOD difference in 30–210 km moving windows are among the most important features for predicting measurement error. XGBoost outperformed the other machine-learning approaches, decreasing the root mean squared error in withheld testing data by 43% and 44% for Aqua and Terra. After correction using XGBoost, the correlation of collocated AOD and daily PM2.5 monitors across the region increased by 10 and 9 percentage points for Aqua and Terra. We demonstrate how machine learning with quality control and spatial features substantially improves satellite-derived AOD products for air pollution modeling.
A national prediction model for PM2.5 component exposures and measurement error-corrected health effect inference.

Science.gov (United States)

Bergen, Silas; Sheppard, Lianne; Sampson, Paul D; Kim, Sun-Young; Richards, Mark; Vedal, Sverre; Kaufman, Joel D; Szpiro, Adam A

2013-09-01

Studies estimating health effects of long-term air pollution exposure often use a two-stage approach: building exposure models to assign individual-level exposures, which are then used in regression analyses. This requires accurate exposure modeling and careful treatment of exposure measurement error. To illustrate the importance of accounting for exposure model characteristics in two-stage air pollution studies, we considered a case study based on data from the Multi-Ethnic Study of Atherosclerosis (MESA). We built national spatial exposure models that used partial least squares and universal kriging to estimate annual average concentrations of four PM2.5 components: elemental carbon (EC), organic carbon (OC), silicon (Si), and sulfur (S). We predicted PM2.5 component exposures for the MESA cohort and estimated cross-sectional associations with carotid intima-media thickness (CIMT), adjusting for subject-specific covariates. We corrected for measurement error using recently developed methods that account for the spatial structure of predicted exposures. Our models performed well, with cross-validated R2 values ranging from 0.62 to 0.95. Naïve analyses that did not account for measurement error indicated statistically significant associations between CIMT and exposure to OC, Si, and S. EC and OC exhibited little spatial correlation, and the corrected inference was unchanged from the naïve analysis. The Si and S exposure surfaces displayed notable spatial correlation, resulting in corrected confidence intervals (CIs) that were 50% wider than the naïve CIs, but that were still statistically significant. The impact of correcting for measurement error on health effect inference is concordant with the degree of spatial correlation in the exposure surfaces. Exposure model characteristics must be considered when performing two-stage air pollution epidemiologic analyses because naïve health effect inference may be inappropriate.
Error threshold inference from Global Precipitation Measurement (GPM) satellite rainfall data and interpolated ground-based rainfall measurements in Metro Manila

Science.gov (United States)

Ampil, L. J. Y.; Yao, J. G.; Lagrosas, N.; Lorenzo, G. R. H.; Simpas, J.

2017-12-01

The Global Precipitation Measurement (GPM) mission is a group of satellites that provides global observations of precipitation. Satellite-based observations act as an alternative if ground-based measurements are inadequate or unavailable. Data provided by satellites however must be validated for this data to be reliable and used effectively. In this study, the Integrated Multisatellite Retrievals for GPM (IMERG) Final Run v3 half-hourly product is validated by comparing against interpolated ground measurements derived from sixteen ground stations in Metro Manila. The area considered in this study is the region 14.4° - 14.8° latitude and 120.9° - 121.2° longitude, subdivided into twelve 0.1° x 0.1° grid squares. Satellite data from June 1 - August 31, 2014 with the data aggregated to 1-day temporal resolution are used in this study. The satellite data is directly compared to measurements from individual ground stations to determine the effect of the interpolation by contrast against the comparison of satellite data and interpolated measurements. The comparisons are calculated by taking a fractional root-mean-square error (F-RMSE) between two datasets. The results show that interpolation improves errors compared to using raw station data except during days with very small amounts of rainfall. F-RMSE reaches extreme values of up to 654 without a rainfall threshold. A rainfall threshold is inferred to remove extreme error values and make the distribution of F-RMSE more consistent. Results show that the rainfall threshold varies slightly per month. The threshold for June is inferred to be 0.5 mm, reducing the maximum F-RMSE to 9.78, while the threshold for July and August is inferred to be 0.1 mm, reducing the maximum F-RMSE to 4.8 and 10.7, respectively. The maximum F-RMSE is reduced further as the threshold is increased. Maximum F-RMSE is reduced to 3.06 when a rainfall threshold of 10 mm is applied over the entire duration of JJA. These results indicate that
Accounting for baseline differences and measurement error in the analysis of change over time.

Science.gov (United States)

Braun, Julia; Held, Leonhard; Ledergerber, Bruno

2014-01-15

If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy. Copyright © 2013 John Wiley & Sons, Ltd.
Estimating the acute health effects of coarse particulate matter accounting for exposure measurement error.

Science.gov (United States)

Chang, Howard H; Peng, Roger D; Dominici, Francesca

2011-10-01

In air pollution epidemiology, there is a growing interest in estimating the health effects of coarse particulate matter (PM) with aerodynamic diameter between 2.5 and 10 μm. Coarse PM concentrations can exhibit considerable spatial heterogeneity because the particles travel shorter distances and do not remain suspended in the atmosphere for an extended period of time. In this paper, we develop a modeling approach for estimating the short-term effects of air pollution in time series analysis when the ambient concentrations vary spatially within the study region. Specifically, our approach quantifies the error in the exposure variable by characterizing, on any given day, the disagreement in ambient concentrations measured across monitoring stations. This is accomplished by viewing monitor-level measurements as error-prone repeated measurements of the unobserved population average exposure. Inference is carried out in a Bayesian framework to fully account for uncertainty in the estimation of model parameters. Finally, by using different exposure indicators, we investigate the sensitivity of the association between coarse PM and daily hospital admissions based on a recent national multisite time series analysis. Among Medicare enrollees from 59 US counties between the period 1999 and 2005, we find a consistent positive association between coarse PM and same-day admission for cardiovascular diseases.

On superactivation of one-shot quantum zero-error capacity and the related property of quantum measurements

DEFF Research Database (Denmark)

Shirokov, M. E.; Shulman, Tatiana

2014-01-01

We give a detailed description of a low-dimensional quantum channel (input dimension 4, Choi rank 3) demonstrating the symmetric form of superactivation of one-shot quantum zero-error capacity. This property means appearance of a noiseless (perfectly reversible) subchannel in the tensor square...... of a channel having no noiseless subchannels. Then we describe a quantum channel with an arbitrary given level of symmetric superactivation (including the infinite value). We also show that superactivation of one-shot quantum zero-error capacity of a channel can be reformulated in terms of quantum measurement...
ADC border effect and suppression of quantization error in the digital dynamic measurement

International Nuclear Information System (INIS)

Bai Li-Na; Liu Hai-Dong; Zhou Wei; Zhai Hong-Qi; Cui Zhen-Jian; Zhao Ming-Ying; Gu Xiao-Qian; Liu Bei-Ling; Huang Li-Bei; Zhang Yong

2017-01-01

The digital measurement and processing is an important direction in the measurement and control field. The quantization error widely existing in the digital processing is always the decisive factor that restricts the development and applications of the digital technology. In this paper, we find that the stability of the digital quantization system is obviously better than the quantization resolution. The application of a border effect in the digital quantization can greatly improve the accuracy of digital processing. Its effective precision has nothing to do with the number of quantization bits, which is only related to the stability of the quantization system. The high precision measurement results obtained in the low level quantization system with high sampling rate have an important application value for the progress in the digital measurement and processing field. (paper)
A NEW METHOD TO QUANTIFY AND REDUCE THE NET PROJECTION ERROR IN WHOLE-SOLAR-ACTIVE-REGION PARAMETERS MEASURED FROM VECTOR MAGNETOGRAMS

Energy Technology Data Exchange (ETDEWEB)

Falconer, David A.; Tiwari, Sanjiv K.; Moore, Ronald L. [NASA Marshall Space Flight Center, Huntsville, AL 35812 (United States); Khazanov, Igor, E-mail: David.a.Falconer@nasa.gov [Center for Space Plasma and Aeronomic Research, University of Alabama in Huntsville, Huntsville, AL 35899 (United States)

2016-12-20

Projection errors limit the use of vector magnetograms of active regions (ARs) far from the disk center. In this Letter, for ARs observed up to 60° from the disk center, we demonstrate a method for measuring and reducing the projection error in the magnitude of any whole-AR parameter that is derived from a vector magnetogram that has been deprojected to the disk center. The method assumes that the center-to-limb curve of the average of the parameter’s absolute values, measured from the disk passage of a large number of ARs and normalized to each AR’s absolute value of the parameter at central meridian, gives the average fractional projection error at each radial distance from the disk center. To demonstrate the method, we use a large set of large-flux ARs and apply the method to a whole-AR parameter that is among the simplest to measure: whole-AR magnetic flux. We measure 30,845 SDO /Helioseismic and Magnetic Imager vector magnetograms covering the disk passage of 272 large-flux ARs, each having whole-AR flux >10{sup 22} Mx. We obtain the center-to-limb radial-distance run of the average projection error in measured whole-AR flux from a Chebyshev fit to the radial-distance plot of the 30,845 normalized measured values. The average projection error in the measured whole-AR flux of an AR at a given radial distance is removed by multiplying the measured flux by the correction factor given by the fit. The correction is important for both the study of the evolution of ARs and for improving the accuracy of forecasts of an AR’s major flare/coronal mass ejection productivity.
Measurement of Systematic Error Effects for a Sensitive Storage Ring EDM Polarimeter

Science.gov (United States)

Imig, Astrid; Stephenson, Edward

2009-10-01

The Storage Ring EDM Collaboration was using the Cooler Synchrotron (COSY) and the EDDA detector at the Forschungszentrum J"ulich to explore systematic errors in very sensitive storage-ring polarization measurements. Polarized deuterons of 235 MeV were used. The analyzer target was a block of 17 mm thick carbon placed close to the beam so that white noise applied to upstream electrostatic plates increases the vertical phase space of the beam, allowing deuterons to strike the front face of the block. For a detector acceptance that covers laboratory angles larger than 9 ^o, the efficiency for particles to scatter into the polarimeter detectors was about 0.1% (all directions) and the vector analyzing power was about 0.2. Measurements were made of the sensitivity of the polarization measurement to beam position and angle. Both vector and tensor asymmetries were measured using beams with both vector and tensor polarization. Effects were seen that depend upon both the beam geometry and the data rate in the detectors.
High cortisol awakening response is associated with impaired error monitoring and decreased post-error adjustment.

Science.gov (United States)

Zhang, Liang; Duan, Hongxia; Qin, Shaozheng; Yuan, Yiran; Buchanan, Tony W; Zhang, Kan; Wu, Jianhui

2015-01-01

The cortisol awakening response (CAR), a rapid increase in cortisol levels following morning awakening, is an important aspect of hypothalamic-pituitary-adrenocortical axis activity. Alterations in the CAR have been linked to a variety of mental disorders and cognitive function. However, little is known regarding the relationship between the CAR and error processing, a phenomenon that is vital for cognitive control and behavioral adaptation. Using high-temporal resolution measures of event-related potentials (ERPs) combined with behavioral assessment of error processing, we investigated whether and how the CAR is associated with two key components of error processing: error detection and subsequent behavioral adjustment. Sixty university students performed a Go/No-go task while their ERPs were recorded. Saliva samples were collected at 0, 15, 30 and 60 min after awakening on the two consecutive days following ERP data collection. The results showed that a higher CAR was associated with slowed latency of the error-related negativity (ERN) and a higher post-error miss rate. The CAR was not associated with other behavioral measures such as the false alarm rate and the post-correct miss rate. These findings suggest that high CAR is a biological factor linked to impairments of multiple steps of error processing in healthy populations, specifically, the automatic detection of error and post-error behavioral adjustment. A common underlying neural mechanism of physiological and cognitive control may be crucial for engaging in both CAR and error processing.
Exploring Senior Residents' Intraoperative Error Management Strategies: A Potential Measure of Performance Improvement.

Science.gov (United States)

Law, Katherine E; Ray, Rebecca D; D'Angelo, Anne-Lise D; Cohen, Elaine R; DiMarco, Shannon M; Linsmeier, Elyse; Wiegmann, Douglas A; Pugh, Carla M

The study aim was to determine whether residents' error management strategies changed across 2 simulated laparoscopic ventral hernia (LVH) repair procedures after receiving feedback on their initial performance. We hypothesize that error detection and recovery strategies would improve during the second procedure without hands-on practice. Retrospective review of participant procedural performances of simulated laparoscopic ventral herniorrhaphy. A total of 3 investigators reviewed procedure videos to identify surgical errors. Errors were deconstructed. Error management events were noted, including error identification and recovery. Residents performed the simulated LVH procedures during a course on advanced laparoscopy. Participants had 30 minutes to complete a LVH procedure. After verbal and simulator feedback, residents returned 24 hours later to perform a different, more difficult simulated LVH repair. Senior (N = 7; postgraduate year 4-5) residents in attendance at the course participated in this study. In the first LVH procedure, residents committed 121 errors (M = 17.14, standard deviation = 4.38). Although the number of errors increased to 146 (M = 20.86, standard deviation = 6.15) during the second procedure, residents progressed further in the second procedure. There was no significant difference in the number of errors committed for both procedures, but errors shifted to the late stage of the second procedure. Residents changed the error types that they attempted to recover (χ 2 5 =24.96, perrors, but decreased for strategy errors. Residents also recovered the most errors in the late stage of the second procedure (p error management strategies changed between procedures following verbal feedback on their initial performance and feedback from the simulator. Errors and recovery attempts shifted to later steps during the second procedure. This may reflect residents' error management success in the earlier stages, which allowed further progression in the
Evaluation of measurement precision errors at different bone density values

International Nuclear Information System (INIS)

Wilson, M.; Wong, J.; Bartlett, M.; Lee, N.

2002-01-01

Full text: The precision error commonly used in serial monitoring of BMD values using Dual Energy X Ray Absorptometry (DEXA) is 0.01-0.015g/cm - for both the L2 L4 lumbar spine and total femur. However, this limit is based on normal individuals with bone densities similar to the population mean. The purpose of this study was to systematically evaluate precision errors over the range of bone density values encountered in clinical practice. In 96 patients a BMD scan of the spine and femur was immediately repeated by the same technologist with the patient taken off the bed and repositioned between scans. Nine technologists participated. Values were obtained for the total femur and spine. Each value was classified as low range (0.75-1.05 g/cm ) and medium range (1.05- 1.35g/cm ) for the spine, low range (0.55 0. 85 g/cm ) and medium range (0.85-1.15 g/cm ) for the total femur. Results show that the precision error was significantly lower in the medium range for total femur results with the medium range value at 0.015 g/cm - and the low range at 0.025 g/cm - (p<0.01). No significant difference was found for the spine results. We also analysed precision errors between three technologists and found a significant difference (p=0.05) occurred between only two technologists and this was seen in the spine data only. We conclude that there is some evidence that the precision error increases at the outer limits of the normal bone density range. Also, the results show that having multiple trained operators does not greatly increase the BMD precision error. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc
Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity

Science.gov (United States)

Spüler, Martin; Niethammer, Christian

2015-01-01

When a person recognizes an error during a task, an error-related potential (ErrP) can be measured as response. It has been shown that ErrPs can be automatically detected in tasks with time-discrete feedback, which is widely applied in the field of Brain-Computer Interfaces (BCIs) for error correction or adaptation. However, there are only a few studies that concentrate on ErrPs during continuous feedback. With this study, we wanted to answer three different questions: (i) Can ErrPs be measured in electroencephalography (EEG) recordings during a task with continuous cursor control? (ii) Can ErrPs be classified using machine learning methods and is it possible to discriminate errors of different origins? (iii) Can we use EEG to detect the severity of an error? To answer these questions, we recorded EEG data from 10 subjects during a video game task and investigated two different types of error (execution error, due to inaccurate feedback; outcome error, due to not achieving the goal of an action). We analyzed the recorded data to show that during the same task, different kinds of error produce different ErrP waveforms and have a different spectral response. This allows us to detect and discriminate errors of different origin in an event-locked manner. By utilizing the error-related spectral response, we show that also a continuous, asynchronous detection of errors is possible. Although the detection of error severity based on EEG was one goal of this study, we did not find any significant influence of the severity on the EEG. PMID:25859204
Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity

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Martin eSpüler

2015-03-01

Full Text Available When a person recognizes an error during a task, an error-related potential (ErrP can be measured as response. It has been shown that ErrPs can be automatically detected in tasks with time-discrete feedback, which is widely applied in the field of Brain-Computer Interfaces (BCIs for error correction or adaptation. However, there are only a few studies that concentrate on ErrPs during continuous feedback.With this study, we wanted to answer three different questions: (i Can ErrPs be measured in electroencephalography (EEG recordings during a task with continuous cursor control? (ii Can ErrPs be classified using machine learning methods and is it possible to discriminate errors of different origins? (iii Can we use EEG to detect the severity of an error? To answer these questions, we recorded EEG data from 10 subjects during a video game task and investigated two different types of error (execution error, due to inaccurate feedback; outcome error, due to not achieving the goal of an action. We analyzed the recorded data to show that during the same task, different kinds of error produce different ErrP waveforms and have a different spectral response. This allows us to detect and discriminate errors of different origin in an event-locked manner. By utilizing the error-related spectral response, we show that also a continuous, asynchronous detection of errors is possible.Although the detection of error severity based on EEG was one goal of this study, we did not find any significant influence of the severity on the EEG.
Powerful bivariate genome-wide association analyses suggest the SOX6 gene influencing both obesity and osteoporosis phenotypes in males.

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Yao-Zhong Liu

2009-08-01

Full Text Available Current genome-wide association studies (GWAS are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically.To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI, with the osteoporosis risk phenotype, hip bone mineral density (BMD, scanning approximately 380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6 gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82x10(-7 and 1.47x10(-6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the approximately 380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS cohort containing 3,355 Caucasians (1,370 males and 1,985 females from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat.Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis.
Powerful Bivariate Genome-Wide Association Analyses Suggest the SOX6 Gene Influencing Both Obesity and Osteoporosis Phenotypes in Males

Science.gov (United States)

Liu, Yao-Zhong; Pei, Yu-Fang; Liu, Jian-Feng; Yang, Fang; Guo, Yan; Zhang, Lei; Liu, Xiao-Gang; Yan, Han; Wang, Liang; Zhang, Yin-Ping; Levy, Shawn; Recker, Robert R.; Deng, Hong-Wen

2009-01-01

Background Current genome-wide association studies (GWAS) are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically. Principal Findings To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI), with the osteoporosis risk phenotype, hip bone mineral density (BMD), scanning ∼380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6) gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82×10−7 and 1.47×10−6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the ∼380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS) cohort containing 3,355 Caucasians (1,370 males and 1,985 females) from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat. Conclusions Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis. PMID:19714249
Evaluating EIV, OLS, and SEM Estimators of Group Slope Differences in the Presence of Measurement Error: The Single-Indicator Case

Science.gov (United States)

Culpepper, Steven Andrew

2012-01-01

Measurement error significantly biases interaction effects and distorts researchers' inferences regarding interactive hypotheses. This article focuses on the single-indicator case and shows how to accurately estimate group slope differences by disattenuating interaction effects with errors-in-variables (EIV) regression. New analytic findings were…
An improved estimator for the hydration of fat-free mass from in vivo measurements subject to additive technical errors

International Nuclear Information System (INIS)

Kinnamon, Daniel D; Ludwig, David A; Lipshultz, Steven E; Miller, Tracie L; Lipsitz, Stuart R

2010-01-01

The hydration of fat-free mass, or hydration fraction (HF), is often defined as a constant body composition parameter in a two-compartment model and then estimated from in vivo measurements. We showed that the widely used estimator for the HF parameter in this model, the mean of the ratios of measured total body water (TBW) to fat-free mass (FFM) in individual subjects, can be inaccurate in the presence of additive technical errors. We then proposed a new instrumental variables estimator that accurately estimates the HF parameter in the presence of such errors. In Monte Carlo simulations, the mean of the ratios of TBW to FFM was an inaccurate estimator of the HF parameter, and inferences based on it had actual type I error rates more than 13 times the nominal 0.05 level under certain conditions. The instrumental variables estimator was accurate and maintained an actual type I error rate close to the nominal level in all simulations. When estimating and performing inference on the HF parameter, the proposed instrumental variables estimator should yield accurate estimates and correct inferences in the presence of additive technical errors, but the mean of the ratios of TBW to FFM in individual subjects may not
Study of systematic errors in the luminosity measurement

International Nuclear Information System (INIS)

Arima, Tatsumi

1993-01-01

The experimental systematic error in the barrel region was estimated to be 0.44 %. This value is derived considering the systematic uncertainties from the dominant sources but does not include uncertainties which are being studied. In the end cap region, the study of shower behavior and clustering effect is under way in order to determine the angular resolution at the low angle edge of the Liquid Argon Calorimeter. We also expect that the systematic error in this region will be less than 1 %. The technical precision of theoretical uncertainty is better than 0.1 % comparing the Tobimatsu-Shimizu program and BABAMC modified by ALEPH. To estimate the physical uncertainty we will use the ALIBABA [9] which includes O(α 2 ) QED correction in leading-log approximation. (J.P.N.)
Study of systematic errors in the luminosity measurement

Energy Technology Data Exchange (ETDEWEB)

Arima, Tatsumi [Tsukuba Univ., Ibaraki (Japan). Inst. of Applied Physics

1993-04-01

The experimental systematic error in the barrel region was estimated to be 0.44 %. This value is derived considering the systematic uncertainties from the dominant sources but does not include uncertainties which are being studied. In the end cap region, the study of shower behavior and clustering effect is under way in order to determine the angular resolution at the low angle edge of the Liquid Argon Calorimeter. We also expect that the systematic error in this region will be less than 1 %. The technical precision of theoretical uncertainty is better than 0.1 % comparing the Tobimatsu-Shimizu program and BABAMC modified by ALEPH. To estimate the physical uncertainty we will use the ALIBABA [9] which includes O({alpha}{sup 2}) QED correction in leading-log approximation. (J.P.N.).
Research on the Factors Influencing the Measurement Errors of the Discrete Rogowski Coil.

Science.gov (United States)

Xu, Mengyuan; Yan, Jing; Geng, Yingsan; Zhang, Kun; Sun, Chao

2018-03-13

An innovative array of magnetic coils (the discrete Rogowski coil-RC) with the advantages of flexible structure, miniaturization and mass producibility is investigated. First, the mutual inductance between the discrete RC and circular and rectangular conductors are calculated using the magnetic vector potential (MVP) method. The results are found to be consistent with those calculated using the finite element method, but the MVP method is simpler and more practical. Then, the influence of conductor section parameters, inclination, and eccentricity on the accuracy of the discrete RC is calculated to provide a reference. Studying the influence of an external current on the discrete RC's interference error reveals optimal values for length, winding density, and position arrangement of the solenoids. It has also found that eccentricity and interference errors decreasing with increasing number of solenoids. Finally, a discrete RC prototype is devised and manufactured. The experimental results show consistent output characteristics, with the calculated sensitivity and mutual inductance of the discrete RC being very close to the experimental results. The influence of an external conductor on the measurement of the discrete RC is analyzed experimentally, and the results show that interference from an external current decreases with increasing distance between the external and measured conductors.
Research on the Factors Influencing the Measurement Errors of the Discrete Rogowski Coil

Directory of Open Access Journals (Sweden)

Mengyuan Xu

2018-03-01

Full Text Available An innovative array of magnetic coils (the discrete Rogowski coil—RC with the advantages of flexible structure, miniaturization and mass producibility is investigated. First, the mutual inductance between the discrete RC and circular and rectangular conductors are calculated using the magnetic vector potential (MVP method. The results are found to be consistent with those calculated using the finite element method, but the MVP method is simpler and more practical. Then, the influence of conductor section parameters, inclination, and eccentricity on the accuracy of the discrete RC is calculated to provide a reference. Studying the influence of an external current on the discrete RC’s interference error reveals optimal values for length, winding density, and position arrangement of the solenoids. It has also found that eccentricity and interference errors decreasing with increasing number of solenoids. Finally, a discrete RC prototype is devised and manufactured. The experimental results show consistent output characteristics, with the calculated sensitivity and mutual inductance of the discrete RC being very close to the experimental results. The influence of an external conductor on the measurement of the discrete RC is analyzed experimentally, and the results show that interference from an external current decreases with increasing distance between the external and measured conductors.
Calibration of a camera–projector measurement system and error impact analysis

International Nuclear Information System (INIS)

Huang, Junhui; Wang, Zhao; Xue, Qi; Gao, Jianmin

2012-01-01

In the camera–projector measurement system, calibration is a key to the measurement accuracy; especially, it is more difficult to obtain the same calibration accuracy for projector than camera due to the inaccurate corresponding relationship between its calibration points and imaging points. Thus, based on stereo vision measurement models of the camera and the projector, a calibration method with direct linear transformation (DLT) and bundle adjustment (BA) is introduced to adjust the corresponding relationships for better optimization purpose in this paper, which minimize the effect of inaccurate calibration points. And an integral method is presented to improve the precision of projection patterns to compensate the projector resolution limitation. Moreover impacts of system parameter and calibration points errors are evaluated when the calibration points positions change, which not only provides theoretical guidance for the rational layout of the calibration points, but also can be used for the optimization of system structure. Finally, the calibration of the system is carried out and the experiment results show that better precision can be achieved with those processes. (paper)
SNPMClust: Bivariate Gaussian Genotype Clustering and Calling for Illumina Microarrays

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Stephen W. Erickson

2016-07-01

Full Text Available SNPMClust is an R package for genotype clustering and calling with Illumina microarrays. It was originally developed for studies using the GoldenGate custom genotyping platform but can be used with other Illumina platforms, including Infinium BeadChip. The algorithm first rescales the fluorescent signal intensity data, adds empirically derived pseudo-data to minor allele genotype clusters, then uses the package mclust for bivariate Gaussian model fitting. We compared the accuracy and sensitivity of SNPMClust to that of GenCall, Illumina's proprietary algorithm, on a data set of 94 whole-genome amplified buccal (cheek swab DNA samples. These samples were genotyped on a custom panel which included 1064 SNPs for which the true genotype was known with high confidence. SNPMClust produced uniformly lower false call rates over a wide range of overall call rates.
Calibration, field-testing, and error analysis of a gamma-ray probe for in situ measurement of dry bulk density

International Nuclear Information System (INIS)

Bertuzzi, P.; Bruckler, L.; Gabilly, Y.; Gaudu, J.C.

1987-01-01

This paper describes a new gamma-ray probe for measuring dry bulk density in the field. This equipment can be used with three different tube spacings (15, 20 and 30 cm). Calibration procedures and local error analyses are proposed for two cases: (1) for the case where the access tubes are parallel, calibration equations are given for three tube spacings. The linear correlation coefficient obtained in the laboratory is satisfactory (0.999), and a local error analysis shows that the standard deviation in the measured dry bulk density is small (+/- 0.02 g/cm 3 ); (2) when the access tubes are not parallel, a new calibration procedure is presented that accounts for and corrects measurement bias due to the deviating probe spacing. The standard deviation associated with the measured dry bulk density is greater (+/- 0.05 g/cm 3 ), but the measurements themselves are regarded as unbiased. After comparisons of core samplings and gamma-ray probe measurements, a field validation of the gamma-ray measurements is presented. Field validation was carried out on a variety of soils (clay, clay loam, loam, and silty clay loam), using gravimetric water contents that varied from 0.11 0.27 and dry bulk densities ranging from 1.30-1.80 g°cm -3 . Finally, an example of dry bulk density field variability is shown, and the spatial variability is analyzed in regard to the measurement errors

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