An audit strategy for time-to-event outcomes measured with error: application to five randomized controlled trials in oncology.

Science.gov (United States)

Dodd, Lori E; Korn, Edward L; Freidlin, Boris; Gu, Wenjuan; Abrams, Jeffrey S; Bushnell, William D; Canetta, Renzo; Doroshow, James H; Gray, Robert J; Sridhara, Rajeshwari

2013-10-01

Measurement error in time-to-event end points complicates interpretation of treatment effects in clinical trials. Non-differential measurement error is unlikely to produce large bias [1]. When error depends on treatment arm, bias is of greater concern. Blinded-independent central review (BICR) of all images from a trial is commonly undertaken to mitigate differential measurement-error bias that may be present in hazard ratios (HRs) based on local evaluations. Similar BICR and local evaluation HRs may provide reassurance about the treatment effect, but BICR adds considerable time and expense to trials. We describe a BICR audit strategy [2] and apply it to five randomized controlled trials to evaluate its use and to provide practical guidelines. The strategy requires BICR on a subset of study subjects, rather than a complete-case BICR, and makes use of an auxiliary-variable estimator. When the effect size is relatively large, the method provides a substantial reduction in the size of the BICRs. In a trial with 722 participants and a HR of 0.48, an average audit of 28% of the data was needed and always confirmed the treatment effect as assessed by local evaluations. More moderate effect sizes and/or smaller trial sizes required larger proportions of audited images, ranging from 57% to 100% for HRs ranging from 0.55 to 0.77 and sample sizes between 209 and 737. The method is developed for a simple random sample of study subjects. In studies with low event rates, more efficient estimation may result from sampling individuals with events at a higher rate. The proposed strategy can greatly decrease the costs and time associated with BICR, by reducing the number of images undergoing review. The savings will depend on the underlying treatment effect and trial size, with larger treatment effects and larger trials requiring smaller proportions of audited data.

The influence of random and systematic errors on a general definition of minimum detectable amount (MDA) applicable to all radiobioassay measurements

International Nuclear Information System (INIS)

Brodsky, A.

1985-01-01

An approach to defining minimum detectable amount (MDA) of radioactivity in a sample will be discussed, with the aim of obtaining comments helpful in developing a formulation of MDA that will be broadly applicable to all kinds of radiobioassay measurements, and acceptable to the scientists who make these measurements. Also, the influence of random and systematic errors on the defined MDA are examined

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.

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.

Impacts of Random Attitude Measurement Errors on Airborne Laser Scanning Image%姿态角随机测量误差对机载激光扫描成像的影响

Institute of Scientific and Technical Information of China (English)

王建军; 徐立军; 李小路

2011-01-01

The impacts of random attitude measurement errors on the positioning accuracy of laser footprints and digital surface model (DSM) accuracy of airborne lidar are studied. The principle of airborne lidar is analyzed. The transformation formulas between the random attitude measurement errors and the positioning errors of laser footprints are derived. Three terrains are simulated and the impacts of the random attitude measurement errors on laser point clouds and the corresponding DSM of the three terrains are analyzed. A semi-physical simulation experiment is carried out. The impacts of the random attitude measurement errors on the positioning accuracy of laser footprints and the DSM accuracy are quantitatively evaluated. The simulation and experimental results show that the random attitude measurement errors decrease the accuracy of laser point cloud and DSM. With the parameters used in this research, the horizontal coordinate errors caused by the random attitude measurement errors are about 4～ 5 times higher of the vertical coordinate error. In addition, when the random attitude measurement errors increase 10 times, the coordinate errors of laser point cloud increase about 10 times, while the error of the DSM increases by about 40 times statistically.%研究了姿态角随机测量误差对机载激光雷达激光脚点定位精度和数字表面模型(DSM)精度的影响.分析了机载激光雷达的工作原理,推导了姿态角随机测量误差与激光脚点定位误差之间的传递关系.通过数值仿真,模拟了3种地形,研究了姿态角随机测量误差对点云及DSM的影响规律.通过半实物仿真实验,定最评价了姿态角随机测量误差对激光脚点定位精度和DSM精度的影响.仿真和实验结果表明,姿态角随机测量误差造成激光脚点定位精度和DSM精度降低.姿态角随机测量误差造成激光脚点平面坐标误差增加较大,是高程误差的4～5倍;当姿态角随机测量误差增大10�

Taylor-series and Monte-Carlo-method uncertainty estimation of the width of a probability distribution based on varying bias and random error

International Nuclear Information System (INIS)

Wilson, Brandon M; Smith, Barton L

2013-01-01

Uncertainties are typically assumed to be constant or a linear function of the measured value; however, this is generally not true. Particle image velocimetry (PIV) is one example of a measurement technique that has highly nonlinear, time varying local uncertainties. Traditional uncertainty methods are not adequate for the estimation of the uncertainty of measurement statistics (mean and variance) in the presence of nonlinear, time varying errors. Propagation of instantaneous uncertainty estimates into measured statistics is performed allowing accurate uncertainty quantification of time-mean and statistics of measurements such as PIV. It is shown that random errors will always elevate the measured variance, and thus turbulent statistics such as u'u'-bar. Within this paper, nonlinear, time varying errors are propagated from instantaneous measurements into the measured mean and variance using the Taylor-series method. With these results and knowledge of the systematic and random uncertainty of each measurement, the uncertainty of the time-mean, the variance and covariance can be found. Applicability of the Taylor-series uncertainty equations to time varying systematic and random errors and asymmetric error distributions are demonstrated with Monte-Carlo simulations. The Taylor-series uncertainty estimates are always accurate for uncertainties on the mean quantity. The Taylor-series variance uncertainty is similar to the Monte-Carlo results for cases in which asymmetric random errors exist or the magnitude of the instantaneous variations in the random and systematic errors is near the ‘true’ variance. However, the Taylor-series method overpredicts the uncertainty in the variance as the instantaneous variations of systematic errors are large or are on the same order of magnitude as the ‘true’ variance. (paper)

Evaluation of random errors in Williams’ series coefficients obtained with digital image correlation

International Nuclear Information System (INIS)

Lychak, Oleh V; Holyns’kiy, Ivan S

2016-01-01

The use of the Williams’ series parameters for fracture analysis requires valid information about their error values. The aim of this investigation is the development of the method for estimation of the standard deviation of random errors of the Williams’ series parameters, obtained from the measured components of the stress field. Also, the criteria for choosing the optimal number of terms in the truncated Williams’ series for derivation of their parameters with minimal errors is proposed. The method was used for the evaluation of the Williams’ parameters, obtained from the data, and measured by the digital image correlation technique for testing a three-point bending specimen. (paper)

Effects of Systematic and Random Errors on the Retrieval of Particle Microphysical Properties from Multiwavelength Lidar Measurements Using Inversion with Regularization

Science.gov (United States)

Ramirez, Daniel Perez; Whiteman, David N.; Veselovskii, Igor; Kolgotin, Alexei; Korenskiy, Michael; Alados-Arboledas, Lucas

2013-01-01

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.

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.

Consistent errors in first strand cDNA due to random hexamer mispriming.

Directory of Open Access Journals (Sweden)

Thomas P van Gurp

Full Text Available Priming of random hexamers in cDNA synthesis is known to show sequence bias, but in addition it has been suggested recently that mismatches in random hexamer priming could be a cause of mismatches between the original RNA fragment and observed sequence reads. To explore random hexamer mispriming as a potential source of these errors, we analyzed two independently generated RNA-seq datasets of synthetic ERCC spikes for which the reference is known. First strand cDNA synthesized by random hexamer priming on RNA showed consistent position and nucleotide-specific mismatch errors in the first seven nucleotides. The mismatch errors found in both datasets are consistent in distribution and thermodynamically stable mismatches are more common. This strongly indicates that RNA-DNA mispriming of specific random hexamers causes these errors. Due to their consistency and specificity, mispriming errors can have profound implications for downstream applications if not dealt with properly.

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...

Efficient decoding of random errors for quantum expander codes

OpenAIRE

Fawzi , Omar; Grospellier , Antoine; Leverrier , Anthony

2017-01-01

We show that quantum expander codes, a constant-rate family of quantum LDPC codes, with the quasi-linear time decoding algorithm of Leverrier, Tillich and Z\\'emor can correct a constant fraction of random errors with very high probability. This is the first construction of a constant-rate quantum LDPC code with an efficient decoding algorithm that can correct a linear number of random errors with a negligible failure probability. Finding codes with these properties is also motivated by Gottes...

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...

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

Random and systematic beam modulator errors in dynamic intensity modulated radiotherapy

International Nuclear Information System (INIS)

Parsai, Homayon; Cho, Paul S; Phillips, Mark H; Giansiracusa, Robert S; Axen, David

2003-01-01

This paper reports on the dosimetric effects of random and systematic modulator errors in delivery of dynamic intensity modulated beams. A sliding-widow type delivery that utilizes a combination of multileaf collimators (MLCs) and backup diaphragms was examined. Gaussian functions with standard deviations ranging from 0.5 to 1.5 mm were used to simulate random positioning errors. A clinical example involving a clival meningioma was chosen with optic chiasm and brain stem as limiting critical structures in the vicinity of the tumour. Dose calculations for different modulator fluctuations were performed, and a quantitative analysis was carried out based on cumulative and differential dose volume histograms for the gross target volume and surrounding critical structures. The study indicated that random modulator errors have a strong tendency to reduce minimum target dose and homogeneity. Furthermore, it was shown that random perturbation of both MLCs and backup diaphragms in the order of σ = 1 mm can lead to 5% errors in prescribed dose. In comparison, when MLCs or backup diaphragms alone was perturbed, the system was more robust and modulator errors of at least σ = 1.5 mm were required to cause dose discrepancies greater than 5%. For systematic perturbation, even errors in the order of ±0.5 mm were shown to result in significant dosimetric deviations

At least some errors are randomly generated (Freud was wrong)

Science.gov (United States)

Sellen, A. J.; Senders, J. W.

1986-01-01

An experiment was carried out to expose something about human error generating mechanisms. In the context of the experiment, an error was made when a subject pressed the wrong key on a computer keyboard or pressed no key at all in the time allotted. These might be considered, respectively, errors of substitution and errors of omission. Each of seven subjects saw a sequence of three digital numbers, made an easily learned binary judgement about each, and was to press the appropriate one of two keys. Each session consisted of 1,000 presentations of randomly permuted, fixed numbers broken into 10 blocks of 100. One of two keys should have been pressed within one second of the onset of each stimulus. These data were subjected to statistical analyses in order to probe the nature of the error generating mechanisms. Goodness of fit tests for a Poisson distribution for the number of errors per 50 trial interval and for an exponential distribution of the length of the intervals between errors were carried out. There is evidence for an endogenous mechanism that may best be described as a random error generator. Furthermore, an item analysis of the number of errors produced per stimulus suggests the existence of a second mechanism operating on task driven factors producing exogenous errors. Some errors, at least, are the result of constant probability generating mechanisms with error rate idiosyncratically determined for each subject.

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.

Random errors in the magnetic field coefficients of superconducting quadrupole magnets

International Nuclear Information System (INIS)

Herrera, J.; Hogue, R.; Prodell, A.; Thompson, P.; Wanderer, P.; Willen, E.

1987-01-01

The random multipole errors of superconducting quadrupoles are studied. For analyzing the multipoles which arise due to random variations in the size and locations of the current blocks, a model is outlined which gives the fractional field coefficients from the current distributions. With this approach, based on the symmetries of the quadrupole magnet, estimates are obtained of the random multipole errors for the arc quadrupoles envisioned for the Relativistic Heavy Ion Collider and for a single-layer quadrupole proposed for the Superconducting Super Collider

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.

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.

Quantifying spatial distribution of snow depth errors from LiDAR using Random Forests

Science.gov (United States)

Tinkham, W.; Smith, A. M.; Marshall, H.; Link, T. E.; Falkowski, M. J.; Winstral, A. H.

2013-12-01

There is increasing need to characterize the distribution of snow in complex terrain using remote sensing approaches, especially in isolated mountainous regions that are often water-limited, the principal source of terrestrial freshwater, and sensitive to climatic shifts and variations. We apply intensive topographic surveys, multi-temporal LiDAR, and Random Forest modeling to quantify snow volume and characterize associated errors across seven land cover types in a semi-arid mountainous catchment at a 1 and 4 m spatial resolution. The LiDAR-based estimates of both snow-off surface topology and snow depths were validated against ground-based measurements across the catchment. Comparison of LiDAR-derived snow depths to manual snow depth surveys revealed that LiDAR based estimates were more accurate in areas of low lying vegetation such as shrubs (RMSE = 0.14 m) as compared to areas consisting of tree cover (RMSE = 0.20-0.35 m). The highest errors were found along the edge of conifer forests (RMSE = 0.35 m), however a second conifer transect outside the catchment had much lower errors (RMSE = 0.21 m). This difference is attributed to the wind exposure of the first site that led to highly variable snow depths at short spatial distances. The Random Forest modeled errors deviated from the field measured errors with a RMSE of 0.09-0.34 m across the different cover types. Results show that snow drifts, which are important for maintaining spring and summer stream flows and establishing and sustaining water-limited plant species, contained 30 × 5-6% of the snow volume while only occupying 10% of the catchment area similar to findings by prior physically-based modeling approaches. This study demonstrates the potential utility of combining multi-temporal LiDAR with Random Forest modeling to quantify the distribution of snow depth with a reasonable degree of accuracy. Future work could explore the utility of Terrestrial LiDAR Scanners to produce validation of snow-on surface

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)

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.)

Effects of systematic phase errors on optimized quantum random-walk search algorithm

International Nuclear Information System (INIS)

Zhang Yu-Chao; Bao Wan-Su; Wang Xiang; Fu Xiang-Qun

2015-01-01

This study investigates the effects of systematic errors in phase inversions on the success rate and number of iterations in the optimized quantum random-walk search algorithm. Using the geometric description of this algorithm, a model of the algorithm with phase errors is established, and the relationship between the success rate of the algorithm, the database size, the number of iterations, and the phase error is determined. For a given database size, we obtain both the maximum success rate of the algorithm and the required number of iterations when phase errors are present in the algorithm. Analyses and numerical simulations show that the optimized quantum random-walk search algorithm is more robust against phase errors than Grover’s algorithm. (paper)

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.

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.

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.

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.

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...

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.

Range walk error correction and modeling on Pseudo-random photon counting system

Science.gov (United States)

Shen, Shanshan; Chen, Qian; He, Weiji

2017-08-01

Signal to noise ratio and depth accuracy are modeled for the pseudo-random ranging system with two random processes. The theoretical results, developed herein, capture the effects of code length and signal energy fluctuation are shown to agree with Monte Carlo simulation measurements. First, the SNR is developed as a function of the code length. Using Geiger-mode avalanche photodiodes (GMAPDs), longer code length is proven to reduce the noise effect and improve SNR. Second, the Cramer-Rao lower bound on range accuracy is derived to justify that longer code length can bring better range accuracy. Combined with the SNR model and CRLB model, it is manifested that the range accuracy can be improved by increasing the code length to reduce the noise-induced error. Third, the Cramer-Rao lower bound on range accuracy is shown to converge to the previously published theories and introduce the Gauss range walk model to range accuracy. Experimental tests also converge to the presented boundary model in this paper. It has been proven that depth error caused by the fluctuation of the number of detected photon counts in the laser echo pulse leads to the depth drift of Time Point Spread Function (TPSF). Finally, numerical fitting function is used to determine the relationship between the depth error and the photon counting ratio. Depth error due to different echo energy is calibrated so that the corrected depth accuracy is improved to 1cm.

Calculating radiotherapy margins based on Bayesian modelling of patient specific random errors

International Nuclear Information System (INIS)

Herschtal, A; Te Marvelde, L; Mengersen, K; Foroudi, F; Ball, D; Devereux, T; Pham, D; Greer, P B; Pichler, P; Eade, T; Kneebone, A; Bell, L; Caine, H; Hindson, B; Kron, T; Hosseinifard, Z

2015-01-01

Collected real-life clinical target volume (CTV) displacement data show that some patients undergoing external beam radiotherapy (EBRT) demonstrate significantly more fraction-to-fraction variability in their displacement (‘random error’) than others. This contrasts with the common assumption made by historical recipes for margin estimation for EBRT, that the random error is constant across patients. In this work we present statistical models of CTV displacements in which random errors are characterised by an inverse gamma (IG) distribution in order to assess the impact of random error variability on CTV-to-PTV margin widths, for eight real world patient cohorts from four institutions, and for different sites of malignancy. We considered a variety of clinical treatment requirements and penumbral widths. The eight cohorts consisted of a total of 874 patients and 27 391 treatment sessions. Compared to a traditional margin recipe that assumes constant random errors across patients, for a typical 4 mm penumbral width, the IG based margin model mandates that in order to satisfy the common clinical requirement that 90% of patients receive at least 95% of prescribed RT dose to the entire CTV, margins be increased by a median of 10% (range over the eight cohorts −19% to +35%). This substantially reduces the proportion of patients for whom margins are too small to satisfy clinical requirements. (paper)

The systematic and random errors determination using realtime 3D surface tracking system in breast cancer

International Nuclear Information System (INIS)

Kanphet, J; Suriyapee, S; Sanghangthum, T; Kumkhwao, J; Wisetrintong, M; Dumrongkijudom, N

2016-01-01

The purpose of this study to determine the patient setup uncertainties in deep inspiration breath-hold (DIBH) radiation therapy for left breast cancer patients using real-time 3D surface tracking system. The six breast cancer patients treated by 6 MV photon beams from TrueBeam linear accelerator were selected. The patient setup errors and motion during treatment were observed and calculated for interfraction and intrafraction motions. The systematic and random errors were calculated in vertical, longitudinal and lateral directions. From 180 images tracking before and during treatment, the maximum systematic error of interfraction and intrafraction motions were 0.56 mm and 0.23 mm, the maximum random error of interfraction and intrafraction motions were 1.18 mm and 0.53 mm, respectively. The interfraction was more pronounce than the intrafraction, while the systematic error was less impact than random error. In conclusion the intrafraction motion error from patient setup uncertainty is about half of interfraction motion error, which is less impact due to the stability in organ movement from DIBH. The systematic reproducibility is also half of random error because of the high efficiency of modern linac machine that can reduce the systematic uncertainty effectively, while the random errors is uncontrollable. (paper)

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

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.

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,

Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

Science.gov (United States)

Zhou, Tony; Dickson, Jennifer L; Geoffrey Chase, J

2018-01-01

Continuous glucose monitoring (CGM) devices have been effective in managing diabetes and offer potential benefits for use in the intensive care unit (ICU). Use of CGM devices in the ICU has been limited, primarily due to the higher point accuracy errors over currently used traditional intermittent blood glucose (BG) measures. General models of CGM errors, including drift and random errors, are lacking, but would enable better design of protocols to utilize these devices. This article presents an autoregressive (AR) based modeling method that separately characterizes the drift and random noise of the GlySure CGM sensor (GlySure Limited, Oxfordshire, UK). Clinical sensor data (n = 33) and reference measurements were used to generate 2 AR models to describe sensor drift and noise. These models were used to generate 100 Monte Carlo simulations based on reference blood glucose measurements. These were then compared to the original CGM clinical data using mean absolute relative difference (MARD) and a Trend Compass. The point accuracy MARD was very similar between simulated and clinical data (9.6% vs 9.9%). A Trend Compass was used to assess trend accuracy, and found simulated and clinical sensor profiles were similar (simulated trend index 11.4° vs clinical trend index 10.9°). The model and method accurately represents cohort sensor behavior over patients, providing a general modeling approach to any such sensor by separately characterizing each type of error that can arise in the data. Overall, it enables better protocol design based on accurate expected CGM sensor behavior, as well as enabling the analysis of what level of each type of sensor error would be necessary to obtain desired glycemic control safety and performance with a given protocol.

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.

Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans

International Nuclear Information System (INIS)

Stapleton, S; Zavgorodni, S; Popescu, I A; Beckham, W A

2005-01-01

The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot

Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans

Science.gov (United States)

Stapleton, S.; Zavgorodni, S.; Popescu, I. A.; Beckham, W. A.

2005-02-01

The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot.

Blind Measurement Selection: A Random Matrix Theory Approach

KAUST Repository

Elkhalil, Khalil

2016-12-14

This paper considers the problem of selecting a set of $k$ measurements from $n$ available sensor observations. The selected measurements should minimize a certain error function assessing the error in estimating a certain $m$ dimensional parameter vector. The exhaustive search inspecting each of the $n\\\\choose k$ possible choices would require a very high computational complexity and as such is not practical for large $n$ and $k$. Alternative methods with low complexity have recently been investigated but their main drawbacks are that 1) they require perfect knowledge of the measurement matrix and 2) they need to be applied at the pace of change of the measurement matrix. To overcome these issues, we consider the asymptotic regime in which $k$, $n$ and $m$ grow large at the same pace. Tools from random matrix theory are then used to approximate in closed-form the most important error measures that are commonly used. The asymptotic approximations are then leveraged to select properly $k$ measurements exhibiting low values for the asymptotic error measures. Two heuristic algorithms are proposed: the first one merely consists in applying the convex optimization artifice to the asymptotic error measure. The second algorithm is a low-complexity greedy algorithm that attempts to look for a sufficiently good solution for the original minimization problem. The greedy algorithm can be applied to both the exact and the asymptotic error measures and can be thus implemented in blind and channel-aware fashions. We present two potential applications where the proposed algorithms can be used, namely antenna selection for uplink transmissions in large scale multi-user systems and sensor selection for wireless sensor networks. Numerical results are also presented and sustain the efficiency of the proposed blind methods in reaching the performances of channel-aware algorithms.

A comparison between the original and Tablet-based Symbol Digit Modalities Test in patients with schizophrenia: Test-retest agreement, random measurement error, practice effect, and ecological validity.

Science.gov (United States)

Tang, Shih-Fen; Chen, I-Hui; Chiang, Hsin-Yu; Wu, Chien-Te; Hsueh, I-Ping; Yu, Wan-Hui; Hsieh, Ching-Lin

2017-11-27

We aimed to compare the test-retest agreement, random measurement error, practice effect, and ecological validity of the original and Tablet-based Symbol Digit Modalities Test (T-SDMT) over five serial assessments, and to examine the concurrent validity of the T-SDMT in patients with schizophrenia. Sixty patients with chronic schizophrenia completed five serial assessments (one week apart) of the SDMT and T-SDMT and one assessment of the Activities of Daily Living Rating Scale III at the first time point. Both measures showed high test-retest agreement, similar levels of random measurement error over five serial assessments. Moreover, the practice effects of the two measures did not reach a plateau phase after five serial assessments in young and middle-aged participants. Nevertheless, only the practice effect of the T-SDMT became trivial after the first assessment. Like the SDMT, the T-SDMT had good ecological validity. The T-SDMT also had good concurrent validity with the SDMT. In addition, only the T-SDMT had discriminative validity to discriminate processing speed in young and middle-aged participants. Compared to the SDMT, the T-SDMT had overall slightly better psychometric properties, so it can be an alternative measure to the SDMT for assessing processing speed in patients with schizophrenia. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-isocenter stereotactic radiotherapy: implications for target dose distributions of systematic and random localization errors

International Nuclear Information System (INIS)

Ebert, M.A.; Zavgorodni, S.F.; Kendrick, L.A.; Weston, S.; Harper, C.S.

2001-01-01

Purpose: This investigation examined the effect of alignment and localization errors on dose distributions in stereotactic radiotherapy (SRT) with arced circular fields. In particular, it was desired to determine the effect of systematic and random localization errors on multi-isocenter treatments. Methods and Materials: A research version of the FastPlan system from Surgical Navigation Technologies was used to generate a series of SRT plans of varying complexity. These plans were used to examine the influence of random setup errors by recalculating dose distributions with successive setup errors convolved into the off-axis ratio data tables used in the dose calculation. The influence of systematic errors was investigated by displacing isocenters from their planned positions. Results: For single-isocenter plans, it is found that the influences of setup error are strongly dependent on the size of the target volume, with minimum doses decreasing most significantly with increasing random and systematic alignment error. For multi-isocenter plans, similar variations in target dose are encountered, with this result benefiting from the conventional method of prescribing to a lower isodose value for multi-isocenter treatments relative to single-isocenter treatments. Conclusions: It is recommended that the systematic errors associated with target localization in SRT be tracked via a thorough quality assurance program, and that random setup errors be minimized by use of a sufficiently robust relocation system. These errors should also be accounted for by incorporating corrections into the treatment planning algorithm or, alternatively, by inclusion of sufficient margins in target definition

ERROR DISTRIBUTION EVALUATION OF THE THIRD VANISHING POINT BASED ON RANDOM STATISTICAL SIMULATION

Directory of Open Access Journals (Sweden)

C. Li

2012-07-01

Full Text Available POS, integrated by GPS / INS (Inertial Navigation Systems, has allowed rapid and accurate determination of position and attitude of remote sensing equipment for MMS (Mobile Mapping Systems. However, not only does INS have system error, but also it is very expensive. Therefore, in this paper error distributions of vanishing points are studied and tested in order to substitute INS for MMS in some special land-based scene, such as ground façade where usually only two vanishing points can be detected. Thus, the traditional calibration approach based on three orthogonal vanishing points is being challenged. In this article, firstly, the line clusters, which parallel to each others in object space and correspond to the vanishing points, are detected based on RANSAC (Random Sample Consensus and parallelism geometric constraint. Secondly, condition adjustment with parameters is utilized to estimate nonlinear error equations of two vanishing points (VX, VY. How to set initial weights for the adjustment solution of single image vanishing points is presented. Solving vanishing points and estimating their error distributions base on iteration method with variable weights, co-factor matrix and error ellipse theory. Thirdly, under the condition of known error ellipses of two vanishing points (VX, VY and on the basis of the triangle geometric relationship of three vanishing points, the error distribution of the third vanishing point (VZ is calculated and evaluated by random statistical simulation with ignoring camera distortion. Moreover, Monte Carlo methods utilized for random statistical estimation are presented. Finally, experimental results of vanishing points coordinate and their error distributions are shown and analyzed.

Error Distribution Evaluation of the Third Vanishing Point Based on Random Statistical Simulation

Science.gov (United States)

Li, C.

2012-07-01

POS, integrated by GPS / INS (Inertial Navigation Systems), has allowed rapid and accurate determination of position and attitude of remote sensing equipment for MMS (Mobile Mapping Systems). However, not only does INS have system error, but also it is very expensive. Therefore, in this paper error distributions of vanishing points are studied and tested in order to substitute INS for MMS in some special land-based scene, such as ground façade where usually only two vanishing points can be detected. Thus, the traditional calibration approach based on three orthogonal vanishing points is being challenged. In this article, firstly, the line clusters, which parallel to each others in object space and correspond to the vanishing points, are detected based on RANSAC (Random Sample Consensus) and parallelism geometric constraint. Secondly, condition adjustment with parameters is utilized to estimate nonlinear error equations of two vanishing points (VX, VY). How to set initial weights for the adjustment solution of single image vanishing points is presented. Solving vanishing points and estimating their error distributions base on iteration method with variable weights, co-factor matrix and error ellipse theory. Thirdly, under the condition of known error ellipses of two vanishing points (VX, VY) and on the basis of the triangle geometric relationship of three vanishing points, the error distribution of the third vanishing point (VZ) is calculated and evaluated by random statistical simulation with ignoring camera distortion. Moreover, Monte Carlo methods utilized for random statistical estimation are presented. Finally, experimental results of vanishing points coordinate and their error distributions are shown and analyzed.

Random access to mobile networks with advanced error correction

Science.gov (United States)

Dippold, Michael

1990-01-01

A random access scheme for unreliable data channels is investigated in conjunction with an adaptive Hybrid-II Automatic Repeat Request (ARQ) scheme using Rate Compatible Punctured Codes (RCPC) Forward Error Correction (FEC). A simple scheme with fixed frame length and equal slot sizes is chosen and reservation is implicit by the first packet transmitted randomly in a free slot, similar to Reservation Aloha. This allows the further transmission of redundancy if the last decoding attempt failed. Results show that a high channel utilization and superior throughput can be achieved with this scheme that shows a quite low implementation complexity. For the example of an interleaved Rayleigh channel and soft decision utilization and mean delay are calculated. A utilization of 40 percent may be achieved for a frame with the number of slots being equal to half the station number under high traffic load. The effects of feedback channel errors and some countermeasures are discussed.

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.

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.

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

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

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.

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

Systematic errors due to linear congruential random-number generators with the Swendsen-Wang algorithm: a warning.

Science.gov (United States)

Ossola, Giovanni; Sokal, Alan D

2004-08-01

We show that linear congruential pseudo-random-number generators can cause systematic errors in Monte Carlo simulations using the Swendsen-Wang algorithm, if the lattice size is a multiple of a very large power of 2 and one random number is used per bond. These systematic errors arise from correlations within a single bond-update half-sweep. The errors can be eliminated (or at least radically reduced) by updating the bonds in a random order or in an aperiodic manner. It also helps to use a generator of large modulus (e.g., 60 or more bits).

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

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.

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

Science.gov (United States)

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

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.

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

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.

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.

Random synaptic feedback weights support error backpropagation for deep learning

Science.gov (United States)

Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

2016-01-01

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning. PMID:27824044

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...

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

Science.gov (United States)

Duda, David P.; Minnis, Patrick

2009-01-01

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

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

SOERP, Statistics and 2. Order Error Propagation for Function of Random Variables

International Nuclear Information System (INIS)

Cox, N. D.; Miller, C. F.

1985-01-01

1 - Description of problem or function: SOERP computes second-order error propagation equations for the first four moments of a function of independently distributed random variables. SOERP was written for a rigorous second-order error propagation of any function which may be expanded in a multivariable Taylor series, the input variables being independently distributed. The required input consists of numbers directly related to the partial derivatives of the function, evaluated at the nominal values of the input variables and the central moments of the input variables from the second through the eighth. 2 - Method of solution: The development of equations for computing the propagation of errors begins by expressing the function of random variables in a multivariable Taylor series expansion. The Taylor series expansion is then truncated, and statistical operations are applied to the series in order to obtain equations for the moments (about the origin) of the distribution of the computed value. If the Taylor series is truncated after powers of two, the procedure produces second-order error propagation equations. 3 - Restrictions on the complexity of the problem: The maximum number of component variables allowed is 30. The IBM version will only process one set of input data per run

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

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

Determination of fission products and actinides by inductively coupled plasma-mass spectrometry using isotope dilution analysis. A study of random and systematic errors

International Nuclear Information System (INIS)

Ignacio Garcia Alonso, Jose

1995-01-01

The theory of the propagation of errors (random and systematic) for isotope dilution analysis (IDA) has been applied to the analysis of fission products and actinide elements by inductively coupled plasma-mass spectrometry (ICP-MS). Systematic errors in ID-ICP-MS arising from mass-discrimination (mass bias), detector non-linearity and isobaric interferences in the measured isotopes have to be corrected for in order to achieve accurate results. The mass bias factor and the detector dead-time can be determined by using natural elements with well-defined isotope abundances. A combined method for the simultaneous determination of both factors is proposed. On the other hand, isobaric interferences for some fission products and actinides cannot be eliminated using mathematical corrections (due to the unknown isotope abundances in the sample) and a chemical separation is necessary. The theory for random error propagation in IDA has been applied to the determination of non-natural elements by ICP-MS taking into account all possible sources of uncertainty with pulse counting detection. For the analysis of fission products, the selection of the right spike isotope composition and spike to sample ratio can be performed by applying conventional random propagation theory. However, it has been observed that, in the experimental determination of the isotope abundances of the fission product elements to be determined, the correction for mass-discrimination and the correction for detector dead-time losses contribute to the total random uncertainty. For the instrument used in the experimental part of this study, it was found that the random uncertainty on the measured isotope ratios followed Poisson statistics for low counting rates whereas, for high counting rates, source instability was the main source of error

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.

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

possible reducing of the digital stream. Discrete cosine transformation is most widely used among possible orthogonal transformation. Errors of television measuring systems and data compression protocols analyzed In this paper. The main characteristics of measuring systems and detected sources of their error detected. The most effective methods of video compression are determined. The influence of video compression error on television measuring systems was researched. Obtained results will increase the accuracy of the measuring systems. In television image quality measuring system reduces distortion identical distortion in analog systems and specific distortions resulting from the process of coding / decoding digital video signal and errors in the transmission channel. By the distortions associated with encoding / decoding signal include quantization noise, reducing resolution, mosaic effect, "mosquito" effect edging on sharp drops brightness, blur colors, false patterns, the effect of "dirty window" and other defects. The size of video compression algorithms used in television measuring systems based on the image encoding with intra- and inter prediction individual fragments. The process of encoding / decoding image is non-linear in space and in time, because the quality of the playback of a movie at the reception depends on the pre- and post-history of a random, from the preceding and succeeding tracks, which can lead to distortion of the inadequacy of the sub-picture and a corresponding measuring signal.

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

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

have shown a tendency for inverse regression to have lower error variance than classical regression followed by inversion. This paper supports that tendency both with and without error in predictors. Also, the paper shows that calibration parameter estimates using error in predictor methods perform worse than without using error in predictor methods in the case of inverse regression, but perform better than without using error in predictor methods in the case of classical regression followed by inversion. Both inverse and classical regression involve the ratio of dependent random variables; therefore, the assumed error distribution(s) will matter in parameter estimation and in uncertainty calculations. Mainly for that reason, calibration using a single predictor is distinct from simple regression, and it has not been thoroughly treated in the literature, nor in the ISO Guide to the Expression of Uncertainty in Measurements (GUM). Our refined approach is based on simulation, because we illustrate that analytical approximations are not adequate when there are, for example, 10 or fewer calibration measurements, which is common in calibration applications, each consisting of measured responses from known quantities. - Highlights: • Simulations confirmed a tendency to favour inverse regression for calibration. • Inverse regression has lower error variance than classical regression followed by inversion. • Our study extended previous studies in include the case with non-negligible errors in predictors. • Analytical approximations used to estimate variances are not sufficiently accurate for our application.

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.

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)

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

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.

Do People With Severe Traumatic Brain Injury Benefit From Making Errors? A Randomized Controlled Trial of Error-Based and Errorless Learning.

Science.gov (United States)

Ownsworth, Tamara; Fleming, Jennifer; Tate, Robyn; Beadle, Elizabeth; Griffin, Janelle; Kendall, Melissa; Schmidt, Julia; Lane-Brown, Amanda; Chevignard, Mathilde; Shum, David H K

2017-12-01

Errorless learning (ELL) and error-based learning (EBL) are commonly used approaches to rehabilitation for people with traumatic brain injury (TBI). However, it is unknown whether making errors is beneficial in the learning process to promote skills generalization after severe TBI. To compare the efficacy of ELL and EBL for improving skills generalization, self-awareness, behavioral competency, and psychosocial functioning after severe TBI. A total of 54 adults (79% male; mean age = 38.0 years, SD = 13.4) with severe TBI were randomly allocated to ELL or EBL and received 8 × 1.5-hour therapy sessions that involved meal preparation and other goal-directed activities. The primary outcome was total errors on the Cooking Task (near-transfer). Secondary outcome measures included the Zoo Map Test (far-transfer), Awareness Questionnaire, Patient Competency Rating Scale, Sydney Psychosocial Reintegration Scale, and Care and Needs Scale. Controlling for baseline performance and years of education, participants in the EBL group made significantly fewer errors at postintervention (mean = 36.25; 95% CI = 32.5-40.0) than ELL participants (mean = 42.57; 95% CI = 38.8-46.3). EBL participants also demonstrated greater self-awareness and behavioral competency at postintervention than ELL participants ( P .05), or at the 6-month follow-up assessment. EBL was found to be more effective than ELL for enhancing skills generalization on a task related to training and improving self-awareness and behavioral competency.

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

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.

HyDEn: A Hybrid Steganocryptographic Approach for Data Encryption Using Randomized Error-Correcting DNA Codes

Directory of Open Access Journals (Sweden)

Dan Tulpan

2013-01-01

Full Text Available This paper presents a novel hybrid DNA encryption (HyDEn approach that uses randomized assignments of unique error-correcting DNA Hamming code words for single characters in the extended ASCII set. HyDEn relies on custom-built quaternary codes and a private key used in the randomized assignment of code words and the cyclic permutations applied on the encoded message. Along with its ability to detect and correct errors, HyDEn equals or outperforms existing cryptographic methods and represents a promising in silico DNA steganographic approach.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

Science.gov (United States)

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

ELLIPTICAL WEIGHTED HOLICs FOR WEAK LENSING SHEAR MEASUREMENT. III. THE EFFECT OF RANDOM COUNT NOISE ON IMAGE MOMENTS IN WEAK LENSING ANALYSIS

International Nuclear Information System (INIS)

Okura, Yuki; Futamase, Toshifumi

2013-01-01

This is the third paper on the improvement of systematic errors in weak lensing analysis using an elliptical weight function, referred to as E-HOLICs. In previous papers, we succeeded in avoiding errors that depend on the ellipticity of the background image. In this paper, we investigate the systematic error that depends on the signal-to-noise ratio of the background image. We find that the origin of this error is the random count noise that comes from the Poisson noise of sky counts. The random count noise makes additional moments and centroid shift error, and those first-order effects are canceled in averaging, but the second-order effects are not canceled. We derive the formulae that correct this systematic error due to the random count noise in measuring the moments and ellipticity of the background image. The correction formulae obtained are expressed as combinations of complex moments of the image, and thus can correct the systematic errors caused by each object. We test their validity using a simulated image and find that the systematic error becomes less than 1% in the measured ellipticity for objects with an IMCAT significance threshold of ν ∼ 11.7.

A Logistic Regression Model with a Hierarchical Random Error Term for Analyzing the Utilization of Public Transport

Directory of Open Access Journals (Sweden)

Chong Wei

2015-01-01

Full Text Available Logistic regression models have been widely used in previous studies to analyze public transport utilization. These studies have shown travel time to be an indispensable variable for such analysis and usually consider it to be a deterministic variable. This formulation does not allow us to capture travelers’ perception error regarding travel time, and recent studies have indicated that this error can have a significant effect on modal choice behavior. In this study, we propose a logistic regression model with a hierarchical random error term. The proposed model adds a new random error term for the travel time variable. This term structure enables us to investigate travelers’ perception error regarding travel time from a given choice behavior dataset. We also propose an extended model that allows constraining the sign of this error in the model. We develop two Gibbs samplers to estimate the basic hierarchical model and the extended model. The performance of the proposed models is examined using a well-known dataset.

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

Science.gov (United States)

Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

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

Electronic laboratory system reduces errors in National Tuberculosis Program: a cluster randomized controlled trial.

Science.gov (United States)

Blaya, J A; Shin, S S; Yale, G; Suarez, C; Asencios, L; Contreras, C; Rodriguez, P; Kim, J; Cegielski, P; Fraser, H S F

2010-08-01

To evaluate the impact of the e-Chasqui laboratory information system in reducing reporting errors compared to the current paper system. Cluster randomized controlled trial in 76 health centers (HCs) between 2004 and 2008. Baseline data were collected every 4 months for 12 months. HCs were then randomly assigned to intervention (e-Chasqui) or control (paper). Further data were collected for the same months the following year. Comparisons were made between intervention and control HCs, and before and after the intervention. Intervention HCs had respectively 82% and 87% fewer errors in reporting results for drug susceptibility tests (2.1% vs. 11.9%, P = 0.001, OR 0.17, 95%CI 0.09-0.31) and cultures (2.0% vs. 15.1%, P Chasqui users sent on average three electronic error reports per week to the laboratories. e-Chasqui reduced the number of missing laboratory results at point-of-care health centers. Clinical users confirmed viewing electronic results not available on paper. Reporting errors to the laboratory using e-Chasqui promoted continuous quality improvement. The e-Chasqui laboratory information system is an important part of laboratory infrastructure improvements to support multidrug-resistant tuberculosis care in Peru.

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.

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

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

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.

Modeling of random geometric errors in superconducting magnets with applications to the CERN Large Hadron Collider

Directory of Open Access Journals (Sweden)

P. Ferracin

2000-12-01

Full Text Available Estimates of random field-shape errors induced by cable mispositioning in superconducting magnets are presented and specific applications to the Large Hadron Collider (LHC main dipoles and quadrupoles are extensively discussed. Numerical simulations obtained with Monte Carlo methods are compared to analytic estimates and are used to interpret the experimental data for the LHC dipole and quadrupole prototypes. The proposed approach can predict the effect of magnet tolerances on geometric components of random field-shape errors, and it is a useful tool to monitor the obtained tolerances during magnet production.

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.

Scattering quantum random-walk search with errors

International Nuclear Information System (INIS)

Gabris, A.; Kiss, T.; Jex, I.

2007-01-01

We analyze the realization of a quantum-walk search algorithm in a passive, linear optical network. The specific model enables us to consider the effect of realistic sources of noise and losses on the search efficiency. Photon loss uniform in all directions is shown to lead to the rescaling of search time. Deviation from directional uniformity leads to the enhancement of the search efficiency compared to uniform loss with the same average. In certain cases even increasing loss in some of the directions can improve search efficiency. We show that while we approach the classical limit of the general search algorithm by introducing random phase fluctuations, its utility for searching is lost. Using numerical methods, we found that for static phase errors the averaged search efficiency displays a damped oscillatory behavior that asymptotically tends to a nonzero value

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

Comparison of error-based and errorless learning for people with severe traumatic brain injury: study protocol for a randomized control trial.

Science.gov (United States)

Ownsworth, Tamara; Fleming, Jennifer; Tate, Robyn; Shum, David H K; Griffin, Janelle; Schmidt, Julia; Lane-Brown, Amanda; Kendall, Melissa; Chevignard, Mathilde

2013-11-05

Poor skills generalization poses a major barrier to successful outcomes of rehabilitation after traumatic brain injury (TBI). Error-based learning (EBL) is a relatively new intervention approach that aims to promote skills generalization by teaching people internal self-regulation skills, or how to anticipate, monitor and correct their own errors. This paper describes the protocol of a study that aims to compare the efficacy of EBL and errorless learning (ELL) for improving error self-regulation, behavioral competency, awareness of deficits and long-term outcomes after TBI. This randomized, controlled trial (RCT) has two arms (EBL and ELL); each arm entails 8 × 2 h training sessions conducted within the participants' homes. The first four sessions involve a meal preparation activity, and the final four sessions incorporate a multitasking errand activity. Based on a sample size estimate, 135 participants with severe TBI will be randomized into either the EBL or ELL condition. The primary outcome measure assesses error self-regulation skills on a task related to but distinct from training. Secondary outcomes include measures of self-monitoring and self-regulation, behavioral competency, awareness of deficits, role participation and supportive care needs. Assessments will be conducted at pre-intervention, post-intervention, and at 6-months post-intervention. This study seeks to determine the efficacy and long-term impact of EBL for training internal self-regulation strategies following severe TBI. In doing so, the study will advance theoretical understanding of the role of errors in task learning and skills generalization. EBL has the potential to reduce the length and costs of rehabilitation and lifestyle support because the techniques could enhance generalization success and lifelong application of strategies after TBI. ACTRN12613000585729.

Correcting the Standard Errors of 2-Stage Residual Inclusion Estimators for Mendelian Randomization Studies.

Science.gov (United States)

Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A

2017-11-01

Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

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)

Development of a simulation program to study error propagation in the reprocessing input accountancy measurements

International Nuclear Information System (INIS)

Sanfilippo, L.

1987-01-01

A physical model and a computer program have been developed to simulate all the measurement operations involved with the Isotopic Dilution Analysis technique currently applied in the Volume - Concentration method for the Reprocessing Input Accountancy, together with their errors or uncertainties. The simulator is apt to easily solve a number of problems related to the measurement sctivities of the plant operator and the inspector. The program, written in Fortran 77, is based on a particular Montecarlo technique named ''Random Sampling''; a full description of the code is reported

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.

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

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.

Neutron detection using soft errors in dynamic Random Access Memories

International Nuclear Information System (INIS)

Darambara, D.G.; Spyrou, N.M.

1994-01-01

The purpose of this paper is to present results from experiments that have been performed to show the memory cycle time dependence of the soft errors produced by the interaction of alpha particles with dynamic random access memory devices, with a view to using these as position sensitive detectors. Furthermore, a preliminary feasibility study being carried out indicates the use of dynamic RAMs as neutron detectors by the utilization of (n, α) capture reactions in a Li converter placed on the top of the active area of the memory chip. ((orig.))

Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

Science.gov (United States)

Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

2016-01-01

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

Space-borne remote sensing of CO2 by IPDA lidar with heterodyne detection: random error estimation

Science.gov (United States)

Matvienko, G. G.; Sukhanov, A. Y.

2015-11-01

Possibilities of measuring the CO2 column concentration by spaceborne integrated path differential lidar (IPDA) signals in the near IR absorption bands are investigated. It is shown that coherent detection principles applied in the nearinfrared spectral region promise a high sensitivity for the measurement of the integrated dry air column mixing ratio of the CO2. The simulations indicate that for CO2 the target observational requirements (0.2%) for the relative random error can be met with telescope aperture 0.5 m, detector bandwidth 10 MHz, laser energy per impulse 0.3 mJ and averaging 7500 impulses. It should also be noted that heterodyne technique allows to significantly reduce laser power and receiver overall dimensions compared to direct detection.

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.

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

It is commonly recognized that suspended-sediment concentrations in rivers can change rapidly in time and independently of water discharge during important sediment‑transporting events (for example, during floods); thus, suspended-sediment measurements at closely spaced time intervals are necessary to characterize suspended‑sediment loads. Because the manual collection of sufficient numbers of suspended-sediment samples required to characterize this variability is often time and cost prohibitive, several “surrogate” techniques have been developed for in situ measurements of properties related to suspended-sediment characteristics (for example, turbidity, laser-diffraction, acoustics). Herein, we present a new physically based method for the simultaneous measurement of suspended-silt-and-clay concentration, suspended-sand concentration, and suspended‑sand median grain size in rivers, using multi‑frequency arrays of single-frequency side‑looking acoustic-Doppler profilers. The method is strongly grounded in the extensive scientific literature on the incoherent scattering of sound by random suspensions of small particles. In particular, the method takes advantage of theory that relates acoustic frequency, acoustic attenuation, acoustic backscatter, suspended-sediment concentration, and suspended-sediment grain-size distribution. We develop the theory and methods, and demonstrate the application of the method at six study sites on the Colorado River and Rio Grande, where large numbers of suspended-sediment samples have been collected concurrently with acoustic attenuation and backscatter measurements over many years. The method produces acoustical measurements of suspended-silt-and-clay and suspended-sand concentration (in units of mg/L), and acoustical measurements of suspended-sand median grain size (in units of mm) that are generally in good to excellent agreement with concurrent physical measurements of these quantities in the river cross sections at

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

Error Analysis of Indirect Broadband Monitoring of Multilayer Optical Coatings using Computer Simulations

Science.gov (United States)

Semenov, Z. V.; Labusov, V. A.

2017-11-01

Results of studying the errors of indirect monitoring by means of computer simulations are reported. The monitoring method is based on measuring spectra of reflection from additional monitoring substrates in a wide spectral range. Special software (Deposition Control Simulator) is developed, which allows one to estimate the influence of the monitoring system parameters (noise of the photodetector array, operating spectral range of the spectrometer and errors of its calibration in terms of wavelengths, drift of the radiation source intensity, and errors in the refractive index of deposited materials) on the random and systematic errors of deposited layer thickness measurements. The direct and inverse problems of multilayer coatings are solved using the OptiReOpt library. Curves of the random and systematic errors of measurements of the deposited layer thickness as functions of the layer thickness are presented for various values of the system parameters. Recommendations are given on using the indirect monitoring method for the purpose of reducing the layer thickness measurement error.

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...

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.

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.

On modeling animal movements using Brownian motion with measurement error.

Science.gov (United States)

Pozdnyakov, Vladimir; Meyer, Thomas; Wang, Yu-Bo; Yan, Jun

2014-02-01

Modeling animal movements with Brownian motion (or more generally by a Gaussian process) has a long tradition in ecological studies. The recent Brownian bridge movement model (BBMM), which incorporates measurement errors, has been quickly adopted by ecologists because of its simplicity and tractability. We discuss some nontrivial properties of the discrete-time stochastic process that results from observing a Brownian motion with added normal noise at discrete times. In particular, we demonstrate that the observed sequence of random variables is not Markov. Consequently the expected occupation time between two successively observed locations does not depend on just those two observations; the whole path must be taken into account. Nonetheless, the exact likelihood function of the observed time series remains tractable; it requires only sparse matrix computations. The likelihood-based estimation procedure is described in detail and compared to the BBMM estimation.

Random Numbers Demonstrate the Frequency of Type I Errors: Three Spreadsheets for Class Instruction

Science.gov (United States)

Duffy, Sean

2010-01-01

This paper describes three spreadsheet exercises demonstrating the nature and frequency of type I errors using random number generation. The exercises are designed specifically to address issues related to testing multiple relations using correlation (Demonstration I), t tests varying in sample size (Demonstration II) and multiple comparisons…

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.

Covariance-Based Estimation from Multisensor Delayed Measurements with Random Parameter Matrices and Correlated Noises

Directory of Open Access Journals (Sweden)

R. Caballero-Águila

2014-01-01

Full Text Available The optimal least-squares linear estimation problem is addressed for a class of discrete-time multisensor linear stochastic systems subject to randomly delayed measurements with different delay rates. For each sensor, a different binary sequence is used to model the delay process. The measured outputs are perturbed by both random parameter matrices and one-step autocorrelated and cross correlated noises. Using an innovation approach, computationally simple recursive algorithms are obtained for the prediction, filtering, and smoothing problems, without requiring full knowledge of the state-space model generating the signal process, but only the information provided by the delay probabilities and the mean and covariance functions of the processes (signal, random parameter matrices, and noises involved in the observation model. The accuracy of the estimators is measured by their error covariance matrices, which allow us to analyze the estimator performance in a numerical simulation example that illustrates the feasibility of the proposed algorithms.

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

Estimation of Total Error in DWPF Reported Radionuclide Inventories

International Nuclear Information System (INIS)

Edwards, T.B.

1995-01-01

This report investigates the impact of random errors due to measurement and sampling on the reported concentrations of radionuclides in DWPF's filled canister inventory resulting from each macro-batch. The objective of this investigation is to estimate the variance of the total error in reporting these radionuclide concentrations

Error sensitivity analysis in 10-30-day extended range forecasting by using a nonlinear cross-prediction error model

Science.gov (United States)

Xia, Zhiye; Xu, Lisheng; Chen, Hongbin; Wang, Yongqian; Liu, Jinbao; Feng, Wenlan

2017-06-01

Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error (NCPE) model, and their stability in the prediction validity period in 10-30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small (10-6-10-2), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10-1-2 (i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10-2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect ( m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.

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.

Radon measurements: the sources of uncertainties

International Nuclear Information System (INIS)

Zhukovsky, Michael; Onischenko, Alexandra; Bastrikov, Vladislav

2008-01-01

Full text: Radon measurements are quite complicated process and the correct estimation of uncertainties is very important. The sources of uncertainties for grab sampling, short term measurements (charcoal canisters), long term measurements (track detectors) and retrospective measurements (surface traps) are analyzed. The main sources of uncertainties for grab sampling measurements are: systematic bias of reference equipment; random Poisson and non-Poisson errors during calibration; random Poisson and non-Poisson errors during measurements. These sources are also common both for short term measurements (charcoal canisters) and long term measurements (track detectors). Usually during the calibration the high radon concentrations are used (1-5 kBq/m 3 ) and the Poisson random error rarely exceed some percents. Nevertheless the dispersion of measured values even during the calibration usually exceeds the Poisson dispersion expected on the basis of counting statistic. The origins of such non-Poisson random errors during calibration are different for different kinds of instrumental measurements. At present not all sources of non-Poisson random errors are trustworthy identified. The initial calibration accuracy of working devices rarely exceeds the value 20%. The real radon concentrations usually are in the range from some tens to some hundreds Becquerel per cubic meter and for low radon levels Poisson random error can reach up to 20%. The random non-Poisson errors and residual systematic biases are depends on the kind of measurement technique and the environmental conditions during radon measurements. For charcoal canisters there are additional sources of the measurement errors due to influence of air humidity and the variations of radon concentration during the canister exposure. The accuracy of long term measurements by track detectors will depend on the quality of chemical etching after exposure and the influence of season radon variations. The main sources of

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

Improving Pulse Rate Measurements during Random Motion Using a Wearable Multichannel Reflectance Photoplethysmograph

Directory of Open Access Journals (Sweden)

Kristen M. Warren

2016-03-01

Full Text Available Photoplethysmographic (PPG waveforms are used to acquire pulse rate (PR measurements from pulsatile arterial blood volume. PPG waveforms are highly susceptible to motion artifacts (MA, limiting the implementation of PR measurements in mobile physiological monitoring devices. Previous studies have shown that multichannel photoplethysmograms can successfully acquire diverse signal information during simple, repetitive motion, leading to differences in motion tolerance across channels. In this paper, we investigate the performance of a custom-built multichannel forehead-mounted photoplethysmographic sensor under a variety of intense motion artifacts. We introduce an advanced multichannel template-matching algorithm that chooses the channel with the least motion artifact to calculate PR for each time instant. We show that for a wide variety of random motion, channels respond differently to motion artifacts, and the multichannel estimate outperforms single-channel estimates in terms of motion tolerance, signal quality, and PR errors. We have acquired 31 data sets consisting of PPG waveforms corrupted by random motion and show that the accuracy of PR measurements achieved was increased by up to 2.7 bpm when the multichannel-switching algorithm was compared to individual channels. The percentage of PR measurements with error ≤ 5 bpm during motion increased by 18.9% when the multichannel switching algorithm was compared to the mean PR from all channels. Moreover, our algorithm enables automatic selection of the best signal fidelity channel at each time point among the multichannel PPG data.

Apparently conclusive meta-analyses may be inconclusive--Trial sequential analysis adjustment of random error risk due to repetitive testing of accumulating data in apparently conclusive neonatal meta-analyses

DEFF Research Database (Denmark)

Brok, Jesper; Thorlund, Kristian; Wetterslev, Jørn

2008-01-01

BACKGROUND: Random error may cause misleading evidence in meta-analyses. The required number of participants in a meta-analysis (i.e. information size) should be at least as large as an adequately powered single trial. Trial sequential analysis (TSA) may reduce risk of random errors due to repeti......BACKGROUND: Random error may cause misleading evidence in meta-analyses. The required number of participants in a meta-analysis (i.e. information size) should be at least as large as an adequately powered single trial. Trial sequential analysis (TSA) may reduce risk of random errors due...

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.

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.

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.

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...

Soft errors in dynamic random access memories - a basis for dosimetry

International Nuclear Information System (INIS)

Haque, A.K.M.M.; Yates, J.; Stevens, D.

1986-01-01

The soft error rates of a number of 64k and 256k dRAMs from several manufacturers have been measured, employing a MC 68000 microprocessor. For this 'accelerated test' procedure, a 37 kBq (1 μCi) 241 Am alpha emitting source was used. Both 64k and 256k devices exhibited widely differing error rates. It was generally observed that the spread of errors over a particular device/manufacturer was much smaller than the differences between device families and manufacturers. Bit line errors formed a significant part of the total for 64k dRAMs, whereas in 256k dRAMs cell errors dominated; the latter also showed an enhanced sensitivity to integrated dose leading to total failure, and a time-dependent recovery. Although several theoretical models explain soft error mechanisms and predict responses which are compatible with our experimental results, it is considered that microdosimetric and track structure methods should be applied to the problem for its better appreciation. Finally, attention is drawn to the need for further studies of dRAMs, with a view to their use as digital dosemeters. (author)

'When measurements mean action' decision models for portal image review to eliminate systematic set-up errors

International Nuclear Information System (INIS)

Wratten, C.R.; Denham, J.W.; O; Brien, P.; Hamilton, C.S.; Kron, T.; London Regional Cancer Centre, London, Ontario

2004-01-01

The aim of the present paper is to evaluate how the use of decision models in the review of portal images can eliminate systematic set-up errors during conformal therapy. Sixteen patients undergoing four-field irradiation of prostate cancer have had daily portal images obtained during the first two treatment weeks and weekly thereafter. The magnitude of random and systematic variations has been calculated by comparison of the portal image with the reference simulator images using the two-dimensional decision model embodied in the Hotelling's evaluation process (HEP). Random day-to-day set-up variation was small in this group of patients. Systematic errors were, however, common. In 15 of 16 patients, one or more errors of >2 mm were diagnosed at some stage during treatment. Sixteen of the 23 errors were between 2 and 4 mm. Although there were examples of oversensitivity of the HEP in three cases, and one instance of undersensitivity, the HEP proved highly sensitive to the small (2-4 mm) systematic errors that must be eliminated during high precision radiotherapy. The HEP has proven valuable in diagnosing very small ( 4 mm) systematic errors using one-dimensional decision models, HEP can eliminate the majority of systematic errors during the first 2 treatment weeks. Copyright (2004) Blackwell Science Pty Ltd

Distance error correction for time-of-flight cameras

Science.gov (United States)

Fuersattel, Peter; Schaller, Christian; Maier, Andreas; Riess, Christian

2017-06-01

The measurement accuracy of time-of-flight cameras is limited due to properties of the scene and systematic errors. These errors can accumulate to multiple centimeters which may limit the applicability of these range sensors. In the past, different approaches have been proposed for improving the accuracy of these cameras. In this work, we propose a new method that improves two important aspects of the range calibration. First, we propose a new checkerboard which is augmented by a gray-level gradient. With this addition it becomes possible to capture the calibration features for intrinsic and distance calibration at the same time. The gradient strip allows to acquire a large amount of distance measurements for different surface reflectivities, which results in more meaningful training data. Second, we present multiple new features which are used as input to a random forest regressor. By using random regression forests, we circumvent the problem of finding an accurate model for the measurement error. During application, a correction value for each individual pixel is estimated with the trained forest based on a specifically tailored feature vector. With our approach the measurement error can be reduced by more than 40% for the Mesa SR4000 and by more than 30% for the Microsoft Kinect V2. In our evaluation we also investigate the impact of the individual forest parameters and illustrate the importance of the individual features.

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

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

A spatial error model with continuous random effects and an application to growth convergence

Science.gov (United States)

Laurini, Márcio Poletti

2017-10-01

We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (β -convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.

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

Estimation of measurement variances

International Nuclear Information System (INIS)

Jaech, J.L.

1984-01-01

The estimation of measurement error parameters in safeguards systems is discussed. Both systematic and random errors are considered. A simple analysis of variances to characterize the measurement error structure with biases varying over time is presented

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.

A study of total measurement error in tomographic gamma scanning to assay nuclear material with emphasis on a bias issue for low-activity samples

International Nuclear Information System (INIS)

Burr, T.L.; Mercer, D.J.; Prettyman, T.H.

1998-01-01

Field experience with the tomographic gamma scanner to assay nuclear material suggests that the analysis techniques can significantly impact the assay uncertainty. For example, currently implemented image reconstruction methods exhibit a positive bias for low-activity samples. Preliminary studies indicate that bias reduction could be achieved at the expense of increased random error variance. In this paper, the authors examine three possible bias sources: (1) measurement error in the estimated transmission matrix, (2) the positivity constraint on the estimated mass of nuclear material, and (3) improper treatment of the measurement error structure. The authors present results from many small-scale simulation studies to examine this bias/variance tradeoff for a few image reconstruction methods in the presence of the three possible bias sources

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 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.)

The Relative Importance of Random Error and Observation Frequency in Detecting Trends in Upper Tropospheric Water Vapor

Science.gov (United States)

Whiteman, David N.; Vermeesch, Kevin C.; Oman, Luke D.; Weatherhead, Elizabeth C.

2011-01-01

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

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

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...

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.

Evaluation of Data with Systematic Errors

International Nuclear Information System (INIS)

Froehner, F. H.

2003-01-01

Application-oriented evaluated nuclear data libraries such as ENDF and JEFF contain not only recommended values but also uncertainty information in the form of 'covariance' or 'error files'. These can neither be constructed nor utilized properly without a thorough understanding of uncertainties and correlations. It is shown how incomplete information about errors is described by multivariate probability distributions or, more summarily, by covariance matrices, and how correlations are caused by incompletely known common errors. Parameter estimation for the practically most important case of the Gaussian distribution with common errors is developed in close analogy to the more familiar case without. The formalism shows that, contrary to widespread belief, common ('systematic') and uncorrelated ('random' or 'statistical') errors are to be added in quadrature. It also shows explicitly that repetition of a measurement reduces mainly the statistical uncertainties but not the systematic ones. While statistical uncertainties are readily estimated from the scatter of repeatedly measured data, systematic uncertainties can only be inferred from prior information about common errors and their propagation. The optimal way to handle error-affected auxiliary quantities ('nuisance parameters') in data fitting and parameter estimation is to adjust them on the same footing as the parameters of interest and to integrate (marginalize) them out of the joint posterior distribution afterward

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.

Randomized clinical trials in dentistry: Risks of bias, risks of random errors, reporting quality, and methodologic quality over the years 1955-2013.

Directory of Open Access Journals (Sweden)

Humam Saltaji

Full Text Available To examine the risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions and the development of these aspects over time.We included 540 randomized clinical trials from 64 selected systematic reviews. We extracted, in duplicate, details from each of the selected randomized clinical trials with respect to publication and trial characteristics, reporting and methodologic characteristics, and Cochrane risk of bias domains. We analyzed data using logistic regression and Chi-square statistics.Sequence generation was assessed to be inadequate (at unclear or high risk of bias in 68% (n = 367 of the trials, while allocation concealment was inadequate in the majority of trials (n = 464; 85.9%. Blinding of participants and blinding of the outcome assessment were judged to be inadequate in 28.5% (n = 154 and 40.5% (n = 219 of the trials, respectively. A sample size calculation before the initiation of the study was not performed/reported in 79.1% (n = 427 of the trials, while the sample size was assessed as adequate in only 17.6% (n = 95 of the trials. Two thirds of the trials were not described as double blinded (n = 358; 66.3%, while the method of blinding was appropriate in 53% (n = 286 of the trials. We identified a significant decrease over time (1955-2013 in the proportion of trials assessed as having inadequately addressed methodological quality items (P < 0.05 in 30 out of the 40 quality criteria, or as being inadequate (at high or unclear risk of bias in five domains of the Cochrane risk of bias tool: sequence generation, allocation concealment, incomplete outcome data, other sources of bias, and overall risk of bias.The risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions have improved over time; however, further efforts that contribute to the development of more stringent

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.

Analysis of family-wise error rates in statistical parametric mapping using random field theory.

Science.gov (United States)

Flandin, Guillaume; Friston, Karl J

2017-11-01

This technical report revisits the analysis of family-wise error rates in statistical parametric mapping-using random field theory-reported in (Eklund et al. []: arXiv 1511.01863). Contrary to the understandable spin that these sorts of analyses attract, a review of their results suggests that they endorse the use of parametric assumptions-and random field theory-in the analysis of functional neuroimaging data. We briefly rehearse the advantages parametric analyses offer over nonparametric alternatives and then unpack the implications of (Eklund et al. []: arXiv 1511.01863) for parametric procedures. Hum Brain Mapp, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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.

Reliability of perceived neighbourhood conditions and the effects of measurement error on self-rated health across urban and rural neighbourhoods.

Science.gov (United States)

Pruitt, Sandi L; Jeffe, Donna B; Yan, Yan; Schootman, Mario

2012-04-01

Limited psychometric research has examined the reliability of self-reported measures of neighbourhood conditions, the effect of measurement error on associations between neighbourhood conditions and health, and potential differences in the reliabilities between neighbourhood strata (urban vs rural and low vs high poverty). We assessed overall and stratified reliability of self-reported perceived neighbourhood conditions using five scales (social and physical disorder, social control, social cohesion, fear) and four single items (multidimensional neighbouring). We also assessed measurement error-corrected associations of these conditions with self-rated health. Using random-digit dialling, 367 women without breast cancer (matched controls from a larger study) were interviewed twice, 2-3 weeks apart. Test-retest (intraclass correlation coefficients (ICC)/weighted κ) and internal consistency reliability (Cronbach's α) were assessed. Differences in reliability across neighbourhood strata were tested using bootstrap methods. Regression calibration corrected estimates for measurement error. All measures demonstrated satisfactory internal consistency (α ≥ 0.70) and either moderate (ICC/κ=0.41-0.60) or substantial (ICC/κ=0.61-0.80) test-retest reliability in the full sample. Internal consistency did not differ by neighbourhood strata. Test-retest reliability was significantly lower among rural (vs urban) residents for two scales (social control, physical disorder) and two multidimensional neighbouring items; test-retest reliability was higher for physical disorder and lower for one multidimensional neighbouring item among the high (vs low) poverty strata. After measurement error correction, the magnitude of associations between neighbourhood conditions and self-rated health were larger, particularly in the rural population. Research is needed to develop and test reliable measures of perceived neighbourhood conditions relevant to the health of rural populations.

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

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.

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…

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

Analytical model and error analysis of arbitrary phasing technique for bunch length measurement

Science.gov (United States)

Chen, Qushan; Qin, Bin; Chen, Wei; Fan, Kuanjun; Pei, Yuanji

2018-05-01

An analytical model of an RF phasing method using arbitrary phase scanning for bunch length measurement is reported. We set up a statistical model instead of a linear chirp approximation to analyze the energy modulation process. It is found that, assuming a short bunch (σφ / 2 π → 0) and small relative energy spread (σγ /γr → 0), the energy spread (Y =σγ 2) at the exit of the traveling wave linac has a parabolic relationship with the cosine value of the injection phase (X = cosφr|z=0), i.e., Y = AX2 + BX + C. Analogous to quadrupole strength scanning for emittance measurement, this phase scanning method can be used to obtain the bunch length by measuring the energy spread at different injection phases. The injection phases can be randomly chosen, which is significantly different from the commonly used zero-phasing method. Further, the systematic error of the reported method, such as the influence of the space charge effect, is analyzed. This technique will be especially useful at low energies when the beam quality is dramatically degraded and is hard to measure using the zero-phasing method.

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.

NLO error propagation exercise: statistical results

International Nuclear Information System (INIS)

Pack, D.J.; Downing, D.J.

1985-09-01

Error propagation is the extrapolation and cumulation of uncertainty (variance) above total amounts of special nuclear material, for example, uranium or 235 U, that are present in a defined location at a given time. The uncertainty results from the inevitable inexactness of individual measurements of weight, uranium concentration, 235 U enrichment, etc. The extrapolated and cumulated uncertainty leads directly to quantified limits of error on inventory differences (LEIDs) for such material. The NLO error propagation exercise was planned as a field demonstration of the utilization of statistical error propagation methodology at the Feed Materials Production Center in Fernald, Ohio from April 1 to July 1, 1983 in a single material balance area formed specially for the exercise. Major elements of the error propagation methodology were: variance approximation by Taylor Series expansion; variance cumulation by uncorrelated primary error sources as suggested by Jaech; random effects ANOVA model estimation of variance effects (systematic error); provision for inclusion of process variance in addition to measurement variance; and exclusion of static material. The methodology was applied to material balance area transactions from the indicated time period through a FORTRAN computer code developed specifically for this purpose on the NLO HP-3000 computer. This paper contains a complete description of the error propagation methodology and a full summary of the numerical results of applying the methodlogy in the field demonstration. The error propagation LEIDs did encompass the actual uranium and 235 U inventory differences. Further, one can see that error propagation actually provides guidance for reducing inventory differences and LEIDs in future time periods

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

Error analysis of the microradiographical determination of mineral content in mineralised tissue slices

International Nuclear Information System (INIS)

Jong, E. de J. de; Bosch, J.J. ten

1985-01-01

The microradiographic method, used to measure the mineral content in slices of mineralised tissues as a function of position, is analysed. The total error in the measured mineral content is split into systematic errors per microradiogram and random noise errors. These errors are measured quantitatively. Predominant contributions to systematic errors appear to be x-ray beam inhomogeneity, the determination of the step wedge thickness and stray light in the densitometer microscope, while noise errors are under the influence of the choice of film, the value of the optical film transmission of the microradiographic image and the area of the densitometer window. Optimisation criteria are given. The authors used these criteria, together with the requirement that the method be fast and easy to build an optimised microradiographic system. (author)

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.

Tropical systematic and random error energetics based on NCEP ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

Systematic error growth rate peak is observed at wavenumber 2 up to 4-day forecast then .... the influence of summer systematic error and ran- ... total exchange. When the error energy budgets are examined in spectral domain, one may ask ques- tions on the error growth at a certain wavenum- ber from its interaction with ...

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)

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.

Estimation of measurement variances

International Nuclear Information System (INIS)

Anon.

1981-01-01

In the previous two sessions, it was assumed that the measurement error variances were known quantities when the variances of the safeguards indices were calculated. These known quantities are actually estimates based on historical data and on data generated by the measurement program. Session 34 discusses how measurement error parameters are estimated for different situations. The various error types are considered. The purpose of the session is to enable participants to: (1) estimate systematic error variances from standard data; (2) estimate random error variances from data as replicate measurement data; (3) perform a simple analysis of variances to characterize the measurement error structure when biases vary over time

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

Evaluation of domain randomness in periodically poled lithium niobate by diffraction noise measurement.

Science.gov (United States)

Dwivedi, Prashant Povel; Choi, Hee Joo; Kim, Byoung Joo; Cha, Myoungsik

2013-12-16

Random duty-cycle errors (RDE) in ferroelectric quasi-phase-matching (QPM) devices not only affect the frequency conversion efficiency, but also generate non-phase-matched parasitic noise that can be detrimental to some applications. We demonstrate an accurate but simple method for measuring the RDE in periodically poled lithium niobate. Due to the equivalence between the undepleted harmonic generation spectrum and the diffraction pattern from the QPM grating, we employed linear diffraction measurement which is much simpler than tunable harmonic generation experiments [J. S. Pelc, et al., Opt. Lett.36, 864-866 (2011)]. As a result, we could relate the RDE for the QPM device to the relative noise intensity between the diffraction orders.

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.)

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,...

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.

Analysis of errors in forensic science

Directory of Open Access Journals (Sweden)

Mingxiao Du

2017-01-01

Full Text Available Reliability of expert testimony is one of the foundations of judicial justice. Both expert bias and scientific errors affect the reliability of expert opinion, which in turn affects the trustworthiness of the findings of fact in legal proceedings. Expert bias can be eliminated by replacing experts; however, it may be more difficult to eliminate scientific errors. From the perspective of statistics, errors in operation of forensic science include systematic errors, random errors, and gross errors. In general, process repetition and abiding by the standard ISO/IEC:17025: 2005, general requirements for the competence of testing and calibration laboratories, during operation are common measures used to reduce errors that originate from experts and equipment, respectively. For example, to reduce gross errors, the laboratory can ensure that a test is repeated several times by different experts. In applying for forensic principles and methods, the Federal Rules of Evidence 702 mandate that judges consider factors such as peer review, to ensure the reliability of the expert testimony. As the scientific principles and methods may not undergo professional review by specialists in a certain field, peer review serves as an exclusive standard. This study also examines two types of statistical errors. As false-positive errors involve a higher possibility of an unfair decision-making, they should receive more attention than false-negative errors.

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.

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.

Bayesian Nonparametric Regression Analysis of Data with Random Effects Covariates from Longitudinal Measurements

KAUST Repository

Ryu, Duchwan

2010-09-28

We consider nonparametric regression analysis in a generalized linear model (GLM) framework for data with covariates that are the subject-specific random effects of longitudinal measurements. The usual assumption that the effects of the longitudinal covariate processes are linear in the GLM may be unrealistic and if this happens it can cast doubt on the inference of observed covariate effects. Allowing the regression functions to be unknown, we propose to apply Bayesian nonparametric methods including cubic smoothing splines or P-splines for the possible nonlinearity and use an additive model in this complex setting. To improve computational efficiency, we propose the use of data-augmentation schemes. The approach allows flexible covariance structures for the random effects and within-subject measurement errors of the longitudinal processes. The posterior model space is explored through a Markov chain Monte Carlo (MCMC) sampler. The proposed methods are illustrated and compared to other approaches, the "naive" approach and the regression calibration, via simulations and by an application that investigates the relationship between obesity in adulthood and childhood growth curves. © 2010, The International Biometric Society.

Pencil kernel correction and residual error estimation for quality-index-based dose calculations

International Nuclear Information System (INIS)

Nyholm, Tufve; Olofsson, Joergen; Ahnesjoe, Anders; Georg, Dietmar; Karlsson, Mikael

2006-01-01

Experimental data from 593 photon beams were used to quantify the errors in dose calculations using a previously published pencil kernel model. A correction of the kernel was derived in order to remove the observed systematic errors. The remaining residual error for individual beams was modelled through uncertainty associated with the kernel model. The methods were tested against an independent set of measurements. No significant systematic error was observed in the calculations using the derived correction of the kernel and the remaining random errors were found to be adequately predicted by the proposed method

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.

Determining random counts in liquid scintillation counting

International Nuclear Information System (INIS)

Horrocks, D.L.

1979-01-01

During measurements involving coincidence counting techniques, errors can arise due to the detection of chance or random coincidences in the multiple detectors used. A method and the electronic circuits necessary are here described for eliminating this source of error in liquid scintillation detectors used in coincidence counting. (UK)

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.

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...

Dose error analysis for a scanned proton beam delivery system

International Nuclear Information System (INIS)

Coutrakon, G; Wang, N; Miller, D W; Yang, Y

2010-01-01

All particle beam scanning systems are subject to dose delivery errors due to errors in position, energy and intensity of the delivered beam. In addition, finite scan speeds, beam spill non-uniformities, and delays in detector, detector electronics and magnet responses will all contribute errors in delivery. In this paper, we present dose errors for an 8 x 10 x 8 cm 3 target of uniform water equivalent density with 8 cm spread out Bragg peak and a prescribed dose of 2 Gy. Lower doses are also analyzed and presented later in the paper. Beam energy errors and errors due to limitations of scanning system hardware have been included in the analysis. By using Gaussian shaped pencil beams derived from measurements in the research room of the James M Slater Proton Treatment and Research Center at Loma Linda, CA and executing treatment simulations multiple times, statistical dose errors have been calculated in each 2.5 mm cubic voxel in the target. These errors were calculated by delivering multiple treatments to the same volume and calculating the rms variation in delivered dose at each voxel in the target. The variations in dose were the result of random beam delivery errors such as proton energy, spot position and intensity fluctuations. The results show that with reasonable assumptions of random beam delivery errors, the spot scanning technique yielded an rms dose error in each voxel less than 2% or 3% of the 2 Gy prescribed dose. These calculated errors are within acceptable clinical limits for radiation therapy.

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.

Frequency characteristic measurement of a fiber optic gyroscope using a correlation spectrum analysis method based on a pseudo-random sequence

International Nuclear Information System (INIS)

Li, Yang; Chen, Xingfan; Liu, Cheng

2015-01-01

The frequency characteristic is an important indicator of a system’s dynamic performance. The identification of a fiber optic gyroscope (FOG)’s frequency characteristic using a correlation spectrum analysis method based on a pseudo-random sequence is proposed. Taking the angle vibrator as the source of the test rotation stimulation and a pseudo-random sequence as the test signal, the frequency characteristic of a FOG is calculated according to the power spectral density of the rotation rate signal and the cross-power spectral density of the FOG’s output signal and rotation rate signal. A theoretical simulation is done to confirm the validity of this method. An experiment system is built and the test results indicate that the measurement error of the normalized amplitude–frequency response is less than 0.01, that the error of the phase–frequency response is less than 0.3 rad, and the overall measurement accuracy is superior to the traditional frequency-sweep method. By using this method, the FOG’s amplitude–frequency response and phase–frequency response can be measured simultaneously, quickly, accurately, and with a high frequency resolution. The described method meets the requirements of engineering applications. (paper)

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)

Analysis of covariance with pre-treatment measurements in randomized trials: comparison of equal and unequal slopes.

Science.gov (United States)

Funatogawa, Ikuko; Funatogawa, Takashi

2011-09-01

In randomized trials, an analysis of covariance (ANCOVA) is often used to analyze post-treatment measurements with pre-treatment measurements as a covariate to compare two treatment groups. Random allocation guarantees only equal variances of pre-treatment measurements. We hence consider data with unequal covariances and variances of post-treatment measurements without assuming normality. Recently, we showed that the actual type I error rate of the usual ANCOVA assuming equal slopes and equal residual variances is asymptotically at a nominal level under equal sample sizes, and that of the ANCOVA with unequal variances is asymptotically at a nominal level, even under unequal sample sizes. In this paper, we investigated the asymptotic properties of the ANCOVA with unequal slopes for such data. The estimators of the treatment effect at the observed mean are identical between equal and unequal variance assumptions, and these are asymptotically normal estimators for the treatment effect at the true mean. However, the variances of these estimators based on standard formulas are biased, and the actual type I error rates are not at a nominal level, irrespective of variance assumptions. In equal sample sizes, the efficiency of the usual ANCOVA assuming equal slopes and equal variances is asymptotically the same as those of the ANCOVA with unequal slopes and higher than that of the ANCOVA with equal slopes and unequal variances. Therefore, the use of the usual ANCOVA is appropriate in equal sample sizes. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Analysis of errors in spectral reconstruction with a Laplace transform pair model

International Nuclear Information System (INIS)

Archer, B.R.; Bushong, S.C.

1985-01-01

The sensitivity of a Laplace transform pair model for spectral reconstruction to random errors in attenuation measurements of diagnostic x-ray units has been investigated. No spectral deformation or significant alteration resulted from the simulated attenuation errors. It is concluded that the range of spectral uncertainties to be expected from the application of this model is acceptable for most scientific applications. (author)

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

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

Design, calibration and error analysis of instrumentation for heat transfer measurements in internal combustion engines

Science.gov (United States)

Ferguson, C. R.; Tree, D. R.; Dewitt, D. P.; Wahiduzzaman, S. A. H.

1987-01-01

The paper reports the methodology and uncertainty analyses of instrumentation for heat transfer measurements in internal combustion engines. Results are presented for determining the local wall heat flux in an internal combustion engine (using a surface thermocouple-type heat flux gage) and the apparent flame-temperature and soot volume fraction path length product in a diesel engine (using two-color pyrometry). It is shown that a surface thermocouple heat transfer gage suitably constructed and calibrated will have an accuracy of 5 to 10 percent. It is also shown that, when applying two-color pyrometry to measure the apparent flame temperature and soot volume fraction-path length, it is important to choose at least one of the two wavelengths to lie in the range of 1.3 to 2.3 micrometers. Carefully calibrated two-color pyrometer can ensure that random errors in the apparent flame temperature and in the soot volume fraction path length will remain small (within about 1 percent and 10-percent, respectively).

Error budget calculations in laboratory medicine: linking the concepts of biological variation and allowable medical errors

NARCIS (Netherlands)

Stroobants, A. K.; Goldschmidt, H. M. J.; Plebani, M.

2003-01-01

Background: Random, systematic and sporadic errors, which unfortunately are not uncommon in laboratory medicine, can have a considerable impact on the well being of patients. Although somewhat difficult to attain, our main goal should be to prevent all possible errors. A good insight on error-prone

Impact of mixed modes on measurement errors and estimates of change in panel data

Directory of Open Access Journals (Sweden)

Alexandru Cernat

2015-07-01

Full Text Available Mixed mode designs are receiving increased interest as a possible solution for saving costs in panel surveys, although the lasting effects on data quality are unknown. To better understand the effects of mixed mode designs on panel data we will examine its impact on random and systematic error and on estimates of change. The SF12, a health scale, in the Understanding Society Innovation Panel is used for the analysis. Results indicate that only one variable out of 12 has systematic differences due to the mixed mode design. Also, four of the 12 items overestimate variance of change in time in the mixed mode design. We conclude that using a mixed mode approach leads to minor measurement differences but it can result in the overestimation of individual change compared to a single mode design.

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.

Medication error detection in two major teaching hospitals: What are the types of errors?

Directory of Open Access Journals (Sweden)

Fatemeh Saghafi

2014-01-01

Full Text Available Background: Increasing number of reports on medication errors and relevant subsequent damages, especially in medical centers has become a growing concern for patient safety in recent decades. Patient safety and in particular, medication safety is a major concern and challenge for health care professionals around the world. Our prospective study was designed to detect prescribing, transcribing, dispensing, and administering medication errors in two major university hospitals. Materials and Methods: After choosing 20 similar hospital wards in two large teaching hospitals in the city of Isfahan, Iran, the sequence was randomly selected. Diagrams for drug distribution were drawn by the help of pharmacy directors. Direct observation technique was chosen as the method for detecting the errors. A total of 50 doses were studied in each ward to detect prescribing, transcribing and administering errors in each ward. The dispensing error was studied on 1000 doses dispensed in each hospital pharmacy. Results: A total of 8162 number of doses of medications were studied during the four stages, of which 8000 were complete data to be analyzed. 73% of prescribing orders were incomplete and did not have all six parameters (name, dosage form, dose and measuring unit, administration route, and intervals of administration. We found 15% transcribing errors. One-third of administration of medications on average was erroneous in both hospitals. Dispensing errors ranged between 1.4% and 2.2%. Conclusion: Although prescribing and administrating compromise most of the medication errors, improvements are needed in all four stages with regard to medication errors. Clear guidelines must be written and executed in both hospitals to reduce the incidence of medication errors.

Experimental nonlocality-based randomness generation with nonprojective measurements

Science.gov (United States)

Gómez, S.; Mattar, A.; Gómez, E. S.; Cavalcanti, D.; Farías, O. Jiménez; Acín, A.; Lima, G.

2018-04-01

We report on an optical setup generating more than one bit of randomness from one entangled bit (i.e., a maximally entangled state of two qubits). The amount of randomness is certified through the observation of Bell nonlocal correlations. To attain this result we implemented a high-purity entanglement source and a nonprojective three-outcome measurement. Our implementation achieves a gain of 27% of randomness as compared with the standard methods using projective measurements. Additionally, we estimate the amount of randomness certified in a one-sided device-independent scenario, through the observation of Einstein-Podolsky-Rosen steering. Our results prove that nonprojective quantum measurements allow extending the limits for nonlocality-based certified randomness generation using current technology.

Measurement Error and Bias in Value-Added Models. Research Report. ETS RR-17-25

Science.gov (United States)

Kane, Michael T.

2017-01-01

By aggregating residual gain scores (the differences between each student's current score and a predicted score based on prior performance) for a school or a teacher, value-added models (VAMs) can be used to generate estimates of school or teacher effects. It is known that random errors in the prior scores will introduce bias into predictions of…

A comparison of two least-squared random coefficient autoregressive models: with and without autocorrelated errors

OpenAIRE

Autcha Araveeporn

2013-01-01

This paper compares a Least-Squared Random Coefficient Autoregressive (RCA) model with a Least-Squared RCA model based on Autocorrelated Errors (RCA-AR). We looked at only the first order models, denoted RCA(1) and RCA(1)-AR(1). The efficiency of the Least-Squared method was checked by applying the models to Brownian motion and Wiener process, and the efficiency followed closely the asymptotic properties of a normal distribution. In a simulation study, we compared the performance of RCA(1) an...

Learning a locomotor task: with or without errors?

Science.gov (United States)

Marchal-Crespo, Laura; Schneider, Jasmin; Jaeger, Lukas; Riener, Robert

2014-03-04

Robotic haptic guidance is the most commonly used robotic training strategy to reduce performance errors while training. However, research on motor learning has emphasized that errors are a fundamental neural signal that drive motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. However, to date, no study has analyzed with precision which training strategy is the most appropriate to learn an especially simple task. In this study, the impact of robotic training strategies that amplify or reduce errors on muscle activation and motor learning of a simple locomotor task was investigated in twenty two healthy subjects. The experiment was conducted with the MAgnetic Resonance COmpatible Stepper (MARCOS) a special robotic device developed for investigations in the MR scanner. The robot moved the dominant leg passively and the subject was requested to actively synchronize the non-dominant leg to achieve an alternating stepping-like movement. Learning with four different training strategies that reduce or amplify errors was evaluated: (i) Haptic guidance: errors were eliminated by passively moving the limbs, (ii) No guidance: no robot disturbances were presented, (iii) Error amplification: existing errors were amplified with repulsive forces, (iv) Noise disturbance: errors were evoked intentionally with a randomly-varying force disturbance on top of the no guidance strategy. Additionally, the activation of four lower limb muscles was measured by the means of surface electromyography (EMG). Strategies that reduce or do not amplify errors limit muscle activation during training and result in poor learning gains. Adding random disturbing forces during training seems to increase attention, and therefore improve motor learning. Error amplification seems to be the most suitable strategy for initially less skilled subjects, perhaps because subjects could better detect their errors and correct them

An Empirical State Error Covariance Matrix Orbit Determination Example

Science.gov (United States)

Frisbee, Joseph H., Jr.

2015-01-01

is suspect. In its most straight forward form, the technique only requires supplemental calculations to be added to existing batch estimation algorithms. In the current problem being studied a truth model making use of gravity with spherical, J2 and J4 terms plus a standard exponential type atmosphere with simple diurnal and random walk components is used. The ability of the empirical state error covariance matrix to account for errors is investigated under four scenarios during orbit estimation. These scenarios are: exact modeling under known measurement errors, exact modeling under corrupted measurement errors, inexact modeling under known measurement errors, and inexact modeling under corrupted measurement errors. For this problem a simple analog of a distributed space surveillance network is used. The sensors in this network make only range measurements and with simple normally distributed measurement errors. The sensors are assumed to have full horizon to horizon viewing at any azimuth. For definiteness, an orbit at the approximate altitude and inclination of the International Space Station is used for the study. The comparison analyses of the data involve only total vectors. No investigation of specific orbital elements is undertaken. The total vector analyses will look at the chisquare values of the error in the difference between the estimated state and the true modeled state using both the empirical and theoretical error covariance matrices for each of scenario.

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.

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.

Application of Vector Triggering Random Decrement

DEFF Research Database (Denmark)

Asmussen, J. C.; Ibrahim, S. R.; Brincker, Rune

result is a Random Decrement function from each measurement. In traditional Random Decrement estimation the triggering condition is a scalar condition, which should only be fulfilled in a single measurement. In vector triggering Random Decrement the triggering condition is a vector condition......This paper deals with applications of the vector triggering Random Decrement technique. This technique is new and developed with the aim of minimizing estimation time and identification errors. The theory behind the technique is discussed in an accompanying paper. The results presented...... in this paper should be regarded as a further documentation of the technique. The key point in Random Decrement estimation is the formulation of a triggering condition. If the triggering condition is fulfilled a time segment from each measurement is picked out and averaged with previous time segments. The final...

Application of Vector Triggering Random Decrement

DEFF Research Database (Denmark)

Asmussen, J. C.; Ibrahim, S. R.; Brincker, Rune

1997-01-01

result is a Random Decrement function from each measurement. In traditional Random Decrement estimation the triggering condition is a scalar condition, which should only be fulfilled in a single measurement. In vector triggering Random Decrement the triggering condition is a vector condition......This paper deals with applications of the vector triggering Random Decrement technique. This technique is new and developed with the aim of minimizing estimation time and identification errors. The theory behind the technique is discussed in an accompanying paper. The results presented...... in this paper should be regarded as a further documentation of the technique. The key point in Random Decrement estimation is the formulation of a triggering condition. If the triggering condition is fulfilled a time segment from each measurement is picked out and averaged with previous time segments. The final...

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.

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.

Standard practice for construction of a stepped block and its use to estimate errors produced by speed-of-sound measurement systems for use on solids

CERN Document Server

American Society for Testing and Materials. Philadelphia

1999-01-01

1.1 This practice provides a means for evaluating both systematic and random errors for ultrasonic speed-of-sound measurement systems which are used for evaluating material characteristics associated with residual stress and which may also be used for nondestructive measurements of the dynamic elastic moduli of materials. Important features and construction details of a reference block crucial to these error evaluations are described. This practice can be used whenever the precision and bias of sound speed values are in question. 1.2 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

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.

Formal Analysis of Soft Errors using Theorem Proving

Directory of Open Access Journals (Sweden)

Sofiène Tahar

2013-07-01

Full Text Available Modeling and analysis of soft errors in electronic circuits has traditionally been done using computer simulations. Computer simulations cannot guarantee correctness of analysis because they utilize approximate real number representations and pseudo random numbers in the analysis and thus are not well suited for analyzing safety-critical applications. In this paper, we present a higher-order logic theorem proving based method for modeling and analysis of soft errors in electronic circuits. Our developed infrastructure includes formalized continuous random variable pairs, their Cumulative Distribution Function (CDF properties and independent standard uniform and Gaussian random variables. We illustrate the usefulness of our approach by modeling and analyzing soft errors in commonly used dynamic random access memory sense amplifier circuits.

On influential analysis of random observation errors in water environment evaluation%水环境评价中随机观测误差的影响分析

Institute of Scientific and Technical Information of China (English)

田鹏伟

2015-01-01

The paper illustrates the reasons for the random observation errors in water environment,analyzes definitions,features and regulation of the random observation errors,and explores precautions in the random observation errors in water environment evaluation,so as to provide some reference for the treatment of water pollution.%阐述了水环境评价中产生随机观测误差的原因，分析了随机观测误差的定义、特点及其规律性，并对随机观测误差需注意的事项进行了研究探讨，为水污染的治理提供了一定的参考依据。

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

Irregular analytical errors in diagnostic testing - a novel concept.

Science.gov (United States)

Vogeser, Michael; Seger, Christoph

2018-02-23

In laboratory medicine, routine periodic analyses for internal and external quality control measurements interpreted by statistical methods are mandatory for batch clearance. Data analysis of these process-oriented measurements allows for insight into random analytical variation and systematic calibration bias over time. However, in such a setting, any individual sample is not under individual quality control. The quality control measurements act only at the batch level. Quantitative or qualitative data derived for many effects and interferences associated with an individual diagnostic sample can compromise any analyte. It is obvious that a process for a quality-control-sample-based approach of quality assurance is not sensitive to such errors. To address the potential causes and nature of such analytical interference in individual samples more systematically, we suggest the introduction of a new term called the irregular (individual) analytical error. Practically, this term can be applied in any analytical assay that is traceable to a reference measurement system. For an individual sample an irregular analytical error is defined as an inaccuracy (which is the deviation from a reference measurement procedure result) of a test result that is so high it cannot be explained by measurement uncertainty of the utilized routine assay operating within the accepted limitations of the associated process quality control measurements. The deviation can be defined as the linear combination of the process measurement uncertainty and the method bias for the reference measurement system. Such errors should be coined irregular analytical errors of the individual sample. The measurement result is compromised either by an irregular effect associated with the individual composition (matrix) of the sample or an individual single sample associated processing error in the analytical process. Currently, the availability of reference measurement procedures is still highly limited, but LC

Fast decoding techniques for extended single-and-double-error-correcting Reed Solomon codes

Science.gov (United States)

Costello, D. J., Jr.; Deng, H.; Lin, S.

1984-01-01

A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. For example, some 256K-bit dynamic random access memories are organized as 32K x 8 bit-bytes. Byte-oriented codes such as Reed Solomon (RS) codes provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. Some special high speed decoding techniques for extended single and double error correcting RS codes. These techniques are designed to find the error locations and the error values directly from the syndrome without having to form the error locator polynomial and solve for its roots.

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.

Stochastic goal-oriented error estimation with memory

Science.gov (United States)

Ackmann, Jan; Marotzke, Jochem; Korn, Peter

2017-11-01

We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.

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.

Electronic portal image assisted reduction of systematic set-up errors in head and neck irradiation

International Nuclear Information System (INIS)

Boer, Hans C.J. de; Soernsen de Koste, John R. van; Creutzberg, Carien L.; Visser, Andries G.; Levendag, Peter C.; Heijmen, Ben J.M.

2001-01-01

Purpose: To quantify systematic and random patient set-up errors in head and neck irradiation and to investigate the impact of an off-line correction protocol on the systematic errors. Material and methods: Electronic portal images were obtained for 31 patients treated for primary supra-glottic larynx carcinoma who were immobilised using a polyvinyl chloride cast. The observed patient set-up errors were input to the shrinking action level (SAL) off-line decision protocol and appropriate set-up corrections were applied. To assess the impact of the protocol, the positioning accuracy without application of set-up corrections was reconstructed. Results: The set-up errors obtained without set-up corrections (1 standard deviation (SD)=1.5-2 mm for random and systematic errors) were comparable to those reported in other studies on similar fixation devices. On an average, six fractions per patient were imaged and the set-up of half the patients was changed due to the decision protocol. Most changes were detected during weekly check measurements, not during the first days of treatment. The application of the SAL protocol reduced the width of the distribution of systematic errors to 1 mm (1 SD), as expected from simulations. A retrospective analysis showed that this accuracy should be attainable with only two measurements per patient using a different off-line correction protocol, which does not apply action levels. Conclusions: Off-line verification protocols can be particularly effective in head and neck patients due to the smallness of the random set-up errors. The excellent set-up reproducibility that can be achieved with such protocols enables accurate dose delivery in conformal treatments

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.jp; Nakamura, Mitsuhiro; Mizowaki, Takashi; Hiraoka, Masahiro [Department of Radiation Oncology and Image-applied Therapy, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo, Kyoto 606-8507 (Japan)

2016-09-15

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiple causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

International Nuclear Information System (INIS)

Matsuo, Yukinori; Nakamura, Mitsuhiro; Mizowaki, Takashi; Hiraoka, Masahiro

2016-01-01

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiple causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.

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...

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.

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

[Efficacy of motivational interviewing for reducing medication errors in chronic patients over 65 years with polypharmacy: Results of a cluster randomized trial].

Science.gov (United States)

Pérula de Torres, Luis Angel; Pulido Ortega, Laura; Pérula de Torres, Carlos; González Lama, Jesús; Olaya Caro, Inmaculada; Ruiz Moral, Roger

2014-10-21

To evaluate the effectiveness of an intervention based on motivational interviewing to reduce medication errors in chronic patients over 65 with polypharmacy. Cluster randomized trial that included doctors and nurses of 16 Primary Care centers and chronic patients with polypharmacy over 65 years. The professionals were assigned to the experimental or the control group using stratified randomization. Interventions consisted of training of professionals and revision of patient treatments, application of motivational interviewing in the experimental group and also the usual approach in the control group. The primary endpoint (medication error) was analyzed at individual level, and was estimated with the absolute risk reduction (ARR), relative risk reduction (RRR), number of subjects to treat (NNT) and by multiple logistic regression analysis. Thirty-two professionals were randomized (19 doctors and 13 nurses), 27 of them recruited 154 patients consecutively (13 professionals in the experimental group recruited 70 patients and 14 professionals recruited 84 patients in the control group) and completed 6 months of follow-up. The mean age of patients was 76 years (68.8% women). A decrease in the average of medication errors was observed along the period. The reduction was greater in the experimental than in the control group (F=5.109, P=.035). RRA 29% (95% confidence interval [95% CI] 15.0-43.0%), RRR 0.59 (95% CI:0.31-0.76), and NNT 3.5 (95% CI 2.3-6.8). Motivational interviewing is more efficient than the usual approach to reduce medication errors in patients over 65 with polypharmacy. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

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

Conclusive meta-analyses on antenatal magnesium may be inconclusive! Are we underestimating the risk of random error?

DEFF Research Database (Denmark)

Brok, Jesper; Huusom, Lene D; Thorlund, Kristian

2012-01-01

Results from meta-analyses significantly influence clinical practice. Both simulation and empirical studies have demonstrated that the risk of random error (i.e. spurious chance findings) in meta-analyses is much higher than previously anticipated. Hence, authors and users of systematic reviews a...... about the investigated intervention effect(s). We outline the rationale for conducting trial sequential analysis including some examples of the meta-analysis on antenatal magnesium for women at risk of preterm birth....

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.

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

Estimation of total error in DWPF reported radionuclide inventories. Revision 1

International Nuclear Information System (INIS)

Edwards, T.B.

1995-01-01

The Defense Waste Processing Facility (DWPF) at the Savannah River Site is required to determine and report the radionuclide inventory of its glass product. For each macro-batch, the DWPF will report both the total amount (in curies) of each reportable radionuclide and the average concentration (in curies/gram of glass) of each reportable radionuclide. The DWPF is to provide the estimated error of these reported values of its radionuclide inventory as well. The objective of this document is to provide a framework for determining the estimated error in DWPF's reporting of these radionuclide inventories. This report investigates the impact of random errors due to measurement and sampling on the total amount of each reportable radionuclide in a given macro-batch. In addition, the impact of these measurement and sampling errors and process variation are evaluated to determine the uncertainty in the reported average concentrations of radionuclides in DWPF's filled canister inventory resulting from each macro-batch

Large errors and severe conditions

CERN Document Server

Smith, D L; Van Wormer, L A

2002-01-01

Physical parameters that can assume real-number values over a continuous range are generally represented by inherently positive random variables. However, if the uncertainties in these parameters are significant (large errors), conventional means of representing and manipulating the associated variables can lead to erroneous results. Instead, all analyses involving them must be conducted in a probabilistic framework. Several issues must be considered: First, non-linear functional relations between primary and derived variables may lead to significant 'error amplification' (severe conditions). Second, the commonly used normal (Gaussian) probability distribution must be replaced by a more appropriate function that avoids the occurrence of negative sampling results. Third, both primary random variables and those derived through well-defined functions must be dealt with entirely in terms of their probability distributions. Parameter 'values' and 'errors' should be interpreted as specific moments of these probabil...

Classical randomness in quantum measurements

International Nuclear Information System (INIS)

D'Ariano, Giacomo Mauro; Presti, Paoloplacido Lo; Perinotti, Paolo

2005-01-01

Similarly to quantum states, also quantum measurements can be 'mixed', corresponding to a random choice within an ensemble of measuring apparatuses. Such mixing is equivalent to a sort of hidden variable, which produces a noise of purely classical nature. It is then natural to ask which apparatuses are indecomposable, i.e. do not correspond to any random choice of apparatuses. This problem is interesting not only for foundations, but also for applications, since most optimization strategies give optimal apparatuses that are indecomposable. Mathematically the problem is posed describing each measuring apparatus by a positive operator-valued measure (POVM), which gives the statistics of the outcomes for any input state. The POVMs form a convex set, and in this language the indecomposable apparatuses are represented by extremal points-the analogous of 'pure states' in the convex set of states. Differently from the case of states, however, indecomposable POVMs are not necessarily rank-one, e.g. von Neumann measurements. In this paper we give a complete classification of indecomposable apparatuses (for discrete spectrum), by providing different necessary and sufficient conditions for extremality of POVMs, along with a simple general algorithm for the decomposition of a POVM into extremals. As an interesting application, 'informationally complete' measurements are analysed in this respect. The convex set of POVMs is fully characterized by determining its border in terms of simple algebraic properties of the corresponding POVMs

Positioning errors assessed with kV cone-beam CT for image-guided prostate radiotherapy

International Nuclear Information System (INIS)

Li Jiongyan; Guo Xiaomao; Yao Weiqiang; Wang Yanyang; Ma Jinli; Chen Jiayi; Zhang Zhen; Feng Yan

2010-01-01

Objective: To assess set-up errors measured with kilovoltage cone-beam CT (KV-CBCT), and the impact of online corrections on margins required to account for set-up variability during IMRT for patients with prostate cancer. Methods: Seven patients with prostate cancer undergoing IMRT were enrolled onto the study. The KV-CBCT scans were acquired at least twice weekly. After initial set-up using the skin marks, a CBCT scan was acquired and registered with the planning CT to determine the setup errors using an auto grey-scale registration software. Corrections would be made by moving the table if the setup errors were considered clinically significant (i. e. , > 2 mm). A second CBCT scan was acquired immediately after the corrections to evaluate the residual error. PTV margins were derived to account for the measured set-up errors and residual errors determined for this group of patients. Results: 197 KV-CBCT images in total were acquired. The random and systematic positioning errors and calculated PTV margins without correction in mm were : a) Lateral 3.1, 2.1, 9.3; b) Longitudinal 1.5, 1.8, 5.1;c) Vertical 4.2, 3.7, 13.0. The random and systematic positioning errors and calculated PTV margin with correction in mm were : a) Lateral 1.1, 0.9, 3.4; b) Longitudinal 0.7, 1.1, 2.5; c) Vertical 1.1, 1.3, 3.7. Conclusions: With the guidance of online KV-CBCT, set-up errors could be reduced significantly for patients with prostate cancer receiving IMRT. The margin required after online CBCT correction for the patients enrolled in the study would be appoximatively 3-4 mm. (authors)

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.…

The Hurst Phenomenon in Error Estimates Related to Atmospheric Turbulence

Science.gov (United States)

Dias, Nelson Luís; Crivellaro, Bianca Luhm; Chamecki, Marcelo

2018-05-01

The Hurst phenomenon is a well-known feature of long-range persistence first observed in hydrological and geophysical time series by E. Hurst in the 1950s. It has also been found in several cases in turbulence time series measured in the wind tunnel, the atmosphere, and in rivers. Here, we conduct a systematic investigation of the value of the Hurst coefficient H in atmospheric surface-layer data, and its impact on the estimation of random errors. We show that usually H > 0.5 , which implies the non-existence (in the statistical sense) of the integral time scale. Since the integral time scale is present in the Lumley-Panofsky equation for the estimation of random errors, this has important practical consequences. We estimated H in two principal ways: (1) with an extension of the recently proposed filtering method to estimate the random error (H_p ), and (2) with the classical rescaled range introduced by Hurst (H_R ). Other estimators were tried but were found less able to capture the statistical behaviour of the large scales of turbulence. Using data from three micrometeorological campaigns we found that both first- and second-order turbulence statistics display the Hurst phenomenon. Usually, H_R is larger than H_p for the same dataset, raising the question that one, or even both, of these estimators, may be biased. For the relative error, we found that the errors estimated with the approach adopted by us, that we call the relaxed filtering method, and that takes into account the occurrence of the Hurst phenomenon, are larger than both the filtering method and the classical Lumley-Panofsky estimates. Finally, we found that there is no apparent relationship between H and the Obukhov stability parameter. The relative errors, however, do show stability dependence, particularly in the case of the error of the kinematic momentum flux in unstable conditions, and that of the kinematic sensible heat flux in stable conditions.

Detection of random alterations to time-varying musical instrument spectra.

Science.gov (United States)

Horner, Andrew; Beauchamp, James; So, Richard

2004-09-01

The time-varying spectra of eight musical instrument sounds were randomly altered by a time-invariant process to determine how detection of spectral alteration varies with degree of alteration, instrument, musical experience, and spectral variation. Sounds were resynthesized with centroids equalized to the original sounds, with frequencies harmonically flattened, and with average spectral error levels of 8%, 16%, 24%, 32%, and 48%. Listeners were asked to discriminate the randomly altered sounds from reference sounds resynthesized from the original data. For all eight instruments, discrimination was very good for the 32% and 48% error levels, moderate for the 16% and 24% error levels, and poor for the 8% error levels. When the error levels were 16%, 24%, and 32%, the scores of musically experienced listeners were found to be significantly better than the scores of listeners with no musical experience. Also, in this same error level range, discrimination was significantly affected by the instrument tested. For error levels of 16% and 24%, discrimination scores were significantly, but negatively correlated with measures of spectral incoherence and normalized centroid deviation on unaltered instrument spectra, suggesting that the presence of dynamic spectral variations tends to increase the difficulty of detecting spectral alterations. Correlation between discrimination and a measure of spectral irregularity was comparatively low.

Demonstrating the robustness of population surveillance data: implications of error rates on demographic and mortality estimates.

Science.gov (United States)

Fottrell, Edward; Byass, Peter; Berhane, Yemane

2008-03-25

As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs). Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity. This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP) DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty) were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data. The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data. The low sensitivity of parameter estimates and regression analyses to significant amounts of

Demonstrating the robustness of population surveillance data: implications of error rates on demographic and mortality estimates

Directory of Open Access Journals (Sweden)

Berhane Yemane

2008-03-01

Full Text Available Abstract Background As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs. Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity. Methods This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data. Results The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data. Conclusion The low sensitivity of parameter

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

Scattering analysis of point processes and random measures

International Nuclear Information System (INIS)

Hanisch, K.H.

1984-01-01

In the present paper scattering analysis of point processes and random measures is studied. Known formulae which connect the scattering intensity with the pair distribution function of the studied structures are proved in a rigorous manner with tools of the theory of point processes and random measures. For some special fibre processes the scattering intensity is computed. For a class of random measures, namely for 'grain-germ-models', a new formula is proved which yields the pair distribution function of the 'grain-germ-model' in terms of the pair distribution function of the underlying point process (the 'germs') and of the mean structure factor and the mean squared structure factor of the particles (the 'grains'). (author)

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…

Optimizing learning of a locomotor task: amplifying errors as needed.

Science.gov (United States)

Marchal-Crespo, Laura; López-Olóriz, Jorge; Jaeger, Lukas; Riener, Robert

2014-01-01

Research on motor learning has emphasized that errors drive motor adaptation. Thereby, several researchers have proposed robotic training strategies that amplify movement errors rather than decrease them. In this study, the effect of different robotic training strategies that amplify errors on learning a complex locomotor task was investigated. The experiment was conducted with a one degree-of freedom robotic stepper (MARCOS). Subjects were requested to actively coordinate their legs in a desired gait-like pattern in order to track a Lissajous figure presented on a visual display. Learning with three different training strategies was evaluated: (i) No perturbation: the robot follows the subjects' movement without applying any perturbation, (ii) Error amplification: existing errors were amplified with repulsive forces proportional to errors, (iii) Noise disturbance: errors were evoked with a randomly-varying force disturbance. Results showed that training without perturbations was especially suitable for a subset of initially less-skilled subjects, while error amplification seemed to benefit more skilled subjects. Training with error amplification, however, limited transfer of learning. Random disturbing forces benefited learning and promoted transfer in all subjects, probably because it increased attention. These results suggest that learning a locomotor task can be optimized when errors are randomly evoked or amplified based on subjects' initial skill level.

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.

Learning mechanisms to limit medication administration errors.

Science.gov (United States)

Drach-Zahavy, Anat; Pud, Dorit

2010-04-01

This paper is a report of a study conducted to identify and test the effectiveness of learning mechanisms applied by the nursing staff of hospital wards as a means of limiting medication administration errors. Since the influential report ;To Err Is Human', research has emphasized the role of team learning in reducing medication administration errors. Nevertheless, little is known about the mechanisms underlying team learning. Thirty-two hospital wards were randomly recruited. Data were collected during 2006 in Israel by a multi-method (observations, interviews and administrative data), multi-source (head nurses, bedside nurses) approach. Medication administration error was defined as any deviation from procedures, policies and/or best practices for medication administration, and was identified using semi-structured observations of nurses administering medication. Organizational learning was measured using semi-structured interviews with head nurses, and the previous year's reported medication administration errors were assessed using administrative data. The interview data revealed four learning mechanism patterns employed in an attempt to learn from medication administration errors: integrated, non-integrated, supervisory and patchy learning. Regression analysis results demonstrated that whereas the integrated pattern of learning mechanisms was associated with decreased errors, the non-integrated pattern was associated with increased errors. Supervisory and patchy learning mechanisms were not associated with errors. Superior learning mechanisms are those that represent the whole cycle of team learning, are enacted by nurses who administer medications to patients, and emphasize a system approach to data analysis instead of analysis of individual cases.

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