Estimates Of Measurement Error Research Articles

Many classes, restricted measurement (MACREM) models for improved measurement of activities of daily living.

Scientists use latent class (LC) models to identify subgroups in heterogeneous data. LC models reduce an item set to a latent variable and estimate measurement error. Researchers typically use unrestricted LC models, which have many measurement estimates, yet scientific interest primarily concerns the classes. We present highly restricted LC measurement models as an alternate method of operationalization. MACREM (Many Classes, Restricted Measurement) models have a larger number of latent classes than a typical unrestricted model, but many fewer measurement estimates. Goals of this approach include producing more interpretable classes and better measurement error estimates. Parameter constraints accomplish this structuring. We present unrestricted and MACREM model results using data on activities of daily living (ADL) from a national survey (N = 3485). We compare a four class unrestricted model with a 14 class MACREM model. The four class unrestricted model approximates a dimension of functional limitation. The 14 class model includes unordered classes at lower levels of limitation, but ordered classes at higher levels of limitation. In contrast to the four class model, all measurement error rates are reasonably small in the 14 class model. The four class model fits the data better, but the 14 class model is more parsimonious (43 vs. 25 parameters). Three covariates reveal specific associations with MACREM classes. In multinomial logistic regression models with a no limitation class as the reference class, past 12 month diabetes only distinguishes low limitation classes that include cutting one's own toenails as a limitation. It does not distinguish low limitation classes characterized by other common limitations. Past 12 month asthma and current disability status perform similarly, but for heavy housework and walking limitation classes, respectively. These limitation specific covariate associations are not apparent in the unrestricted model analyses. Identifying such connections could provide useful information to advance theory and intervention efforts.

Estimation of sensor measurement errors in reactor coolant systems using multi-sensor fusion

A nuclear power plant is typically instrumented with a variety of sensors to continually monitor its variables, and their sensor’s measurements may be used to assess the plant state and initiate safety actions, if needed. Errors in sensor measurements, due to factors such as calibration drifts, critically affect such state assessments. We address a problem of estimating sensor errors using physics-informed machine learning methods that use measurements collected under known plant conditions. For a given sensor, we propose an information fusion method that uses measurements from other sensors to estimate its output assuming it is error-free and provides its difference from an actual measurement as an error estimate. We present the ensemble of trees and support vector machine fusers, and evaluate their performance using measurements collected over an emulated test loop of a pressurized water reactor. The plant variables are related to each other through the underlying physical laws under inertial constraints that place bounds on their derivatives, which analytically justify the applicability of machine learning methods for computing these fusers. Under twenty scenarios, we assess their sensor error estimates for pressure sensors of the heat exchanger of a reactor’s primary coolant system. Multiple types of errors are captured by both fusers under externally induced calibration drifts, blockages, minor leaks and air gaps in sensing lines, and electromagnetic interference; the root mean square error of the estimation of error is under 2.2% percent of the maximum measurement. We present generalization equations, in the framework of statistical learning theory, for these methods that characterize the confidence probability that the estimation error is bounded by a specified parameter in future test scenarios.

Estimation of optical speed measurement error for traffic monitoring systems

This article is devoted to the problem of accurate vehicle speed measurement from video images. The analysis of existing methods of optical speed measurement is carried out, and the need to estimate the measurement error is justified. An idealized mathematical model of speed measurement based on binding to the size of the license plate is studied and the influence of various factors on the measurement accuracy is shown: the influence of the intrinsic and extrinsic camera parameters, the influence of license plate size in images, influence of data averaging. A comparison of the obtained results with the accuracy of widely used in practice radar technologies is shown.

Evaluation of the error of indirect measurements of physical-mechanical characteristics of materials by dynamic indentation method

The metrological problems of measuring the physic and mechanical characteristics of materials by dynamic indentation are considered. It is shown that the estimation of measurement error demanding the creation of the reference blocks is ineffective due to the wide variety of controlled materials and a wide range of changes in their properties. A technique has been developed for evaluating the accuracy of measurements based on the errors of individual parameters included in the calculation equation, i.e. by determining the error of indirect measurements. The technique is based on the estimation of the boundaries of the random error of the measured characteristics of the material and the non-excluded systematic errors of the parameters that are used for the calculations of needed characteristics. The results of experimental studies are presented, indicating that due to the different character of the dependencies of hardness and elastic modulus, the error in measuring the elastic modulus exceeds the error in measuring hardness. In addition, it was found that the error in measuring the characteristics of materials by the dynamic indentation method exceeds the measurement error by the static indentation method and can be reduced by increasing the accuracy of the equipment used for the registration of impact process. The obtained values of the physic and mechanical characteristics of the materials and the values of the measurement error show that the dynamic indentation method can effectively solve the problem of non-destructive testing of hardness, elastic modulus, and strain hardening exponent of metals and products with an appropriate error.

Knee-specific gait biomechanics are reliable when collected in multiple laboratories by independent raters

Multi-centre gait biomechanics studies provide the opportunity to increase sample size and the confidence in results, yet differences between centres may introduce additional error. While previous investigations have compared gait biomechanics from different laboratories assessed by different raters, estimates of relative reliability, measurement error, and thresholds for real change are still unknown. These metrics are imperative to interpret multi-centre study results. Therefore, we examined the reliability of gait biomechanics assessed in two different laboratories, by two different raters, and using the same study sample. Twelve healthy participants underwent gait assessments by two raters in two laboratories at different institutions. Identical protocols were used to collect five walking trials per participant. Discrete data were examined for knee joint angles and moments, gait speed, and stride length. Reliability was assessed using the intraclass correlation coefficient (ICC), standardized error of the measurement (SEM), minimum detectable difference (MDD), and Bland and Altman plots. All spatiotemporal, joint angle, and joint moment measures had ICCs = 0.83–0.94, except for the knee adduction moment peak in late stance (ICC = 0.69 and 0.72). The knee adduction moment SEMs indicate that measurement errors due to the laboratory effect are between 0.19% and 0.31% body weight times height (0.03–0.05 Nm/kg). Meanwhile, measurement error for the knee flexion-extension angle is <2°. Our results are similar to previous test-retest reliability results from a single laboratory, and multiple laboratories, while adding previously unreported reliability metrics necessary for interpreting multi-centre study results.

Development of a Computerized Adaptive Version of the Turkish Driving Licence Exam

This study tested the applicability of the theoretical Examination for Candidates of Driving License (ECODL) in Turkey as a computerized adaptive test (CAT). Firstly, various simulation conditions were tested for the live CAT through an item response theory-based calibrated item bank. The application of the simulated CAT was based on data from e-exams administered by the Ministry of National Education (MoNE). Results of the first stage of the study were used to determine the rules for starting, continuing, and terminating the live CAT exam for ECODL. Secondly, the live CAT exam was applied according to the results of the simulation. Candidate drivers (n = 280) who had taken the ECODL as an e-test participated in the second stage. Thirdly, the opinions of the individuals who took the computer-based test towards the computer-based testing application were mapped. In the termination rule of the CAT-based ECODL, testing with a fixed number of questions yielded the smallest estimated measurement error. We also found that when ECODL was implemented as CAT, it could reliably differentiate among testers in terms of competence of theoretical knowledge of driving and provide basis for accurate decisions regarding their proficiency. According to the findings obtained on the candidates’ opinions on the computer-based testing application, it was seen that they considered computer-based application more practical an easier in terms of testing.

A METHOD OF REDUCING THE ERROR IN DETERMINING THE ANGULAR DISPLACEMENTS WHEN USING INDUCTIVE SENSORS

Goal. Representation of a special mathematical software for determining the angular displacements of the rotor of the induction angle sensor – resolver (rotating transformer) for applications in which the speed of the sensor's rotor is close to zero. As well as performing its experimental verification. Methodology. The presented method is based on the determination of the phase shift angle of the output signals of the induction sensor, which is determined by comparing the obtained arrangements of signal values with a circular discrete convolution in order to achieve the most precise approximation of the obtained signal values to cosine and sine. The conversion of orthogonal components to an angle is based on the use of a digital phase detector which is use of a software comparator and inverse trigonometric functions. Results. Based on the obtained results of mathematical modeling and experimental research, the characteristic dependencies of the angle of rotation of the rotor of the induction sensor relative to its stator, the nature of which is linear, were obtained. In addition, the estimation of measurement errors of angular displacements is carried out that occur when defining such angles by the method offered. The obtained results of the computer simulation taking into account the high signal noise, as well as the results of experimental investigations, confirm the high precision of this method and the fact that it can be used in systems where high positioning accuracy is required and the speed of the sensor shaft is close to zero. Originality. This article introduces, for the first time, special mathematical software for a new method of determining the angular displacements of the rotor of an induction sensor, which is based on the determination of the orthogonal components of the signal in combination with the use of a circular discrete convolution in the determination of the phase shift angle of the induction sensor signals. Practical meaning. The proposed method does not require the use of demodulators, counters and quadrant tables associated with conventional methods for determining the phase shift of signals. The presented method can be used to measure the full range of 0-2p angular displacements in real time, is simple and can be easily implemented using digital electronic circuitry.

How accurately do mothers recall prenatal visits and gestational age? A validation of Uruguayan survey data

Background: Many household surveys collect mothers’ retrospective reports of reproductive, maternal, and child health. However, few empirical exercises assess survey measurement error in these data, based on comparisons with administrative records. Objective: We provide evidence on the accuracy of maternal recall regarding weeks of gestation, premature births, and the timing and number of prenatal visits. Methods: We compare the survey maternal recall and the vital statistics administrative records based on the 2013 Nutrition, Child Development and Health Survey (ENDIS) for Uruguay (2,963 children aged 0‒3). We estimate measurement error and its determinants by using a set of probit models. Results: Mothers tend to overestimate gestational weeks and the incidence of prematurity by 0.1 weeks and 2.4 percentage points, respectively. Differences are larger regarding the timeliness and sufficiency of prenatal visits (respectively, 17.0 and 14.4 pp). Discrepancies are associated with lower educational levels, the length of the recall period (child’s age) and birth order. Conclusions: In general, our findings validate the use of survey data, although the identification of premature births and prenatal care sufficiency presents differences that could lead to errors in the evaluation of compliance with, for example, the United Nations’ Sustainable Development Goals. Since recall accuracy is negatively associated with maternal schooling, discrepancies could be larger in relatively less developed countries. Contribution: The main contribution of this paper lies in the assessment of measurement error levels arising from maternal reports of gestational age and prenatal visits for a relatively short recall period in a Latin American country. Although previous studies estimate measurement errors using administrative records linked to maternal recall data, this is the only study that is based on a nationally representative survey.

Agricultural products moisture content measurement error estimation with the use of a four-element capacitive sensor model

The article is devoted to the consideration of agricultural products moisture content measurement error estimation with the use of a four-element capacitive sensor model by means of the authors’ method for multi-element bipoles parameters determining. The results of the specified method mathematical modeling and experimental investigations, which confirm measurement accuracy increasing by reducing the resultant method error in comparison with known methods, are presented in the article.

Float-laser device for measuring the water table and freshwater–saltwater interface in laboratory-scale experimental systems

Processes in coastal aquifers involving variable-density fluids are often investigated using laboratory sand tanks. However, experimental monitoring of the interface between liquids of different densities is challenging, typically requiring dye tracers and photographic analysis. These are susceptible to problems of tracer adsorption and image inhomogeneity, and experiments are often limited to two-dimensional cross-sections. In addition, the water-table position is an important factor, but its accurate measurement is often difficult. A device has been developed for sand-tank experiments to obtain high-frequency, high-precision measurements of both the freshwater–saltwater interface (inferred from density) and the water-table depth, using a float and a laser sensor in a monitoring well. The proposed device was tested using a two-column experiment, allowing for the estimation of measurement errors, which were generally less than 1 mm. The measurement device can be modified to allow for the monitoring of multiple salinity values, and is well suited to sand-box experiments where salinity dynamics are otherwise difficult to visualize.

Instrumental validity and intra/inter-rater reliability of a novel low-cost digital pressure algometer.

BackgroundPain assessment is a key measure that accompanies treatments in a wide range of clinical settings. A low-cost valid and reliable pressure algometer would allow objective assessment of pressure pain to assist a variety of health professionals. However, the pressure algometer is often expensive, which limits its daily use in both clinical and research settings.ObjectivesThis study aimed to assess the instrumental validity, and the intra- and inter-rater reliability of an inexpensive digital adapted pressure algometer.MethodsA single rater applied 60 random compressions on a force platform. The pressure pain thresholds of 20 volunteers were collected twice (3 days apart) by two raters. The main outcome measurements were as follows: the maximal peak force (in kPa) and the pressure pain threshold (adapted pressure algometer vs. force platform). Cronbach’s α test was used to assess internal consistency. The standard error of measurement provided estimates of measurement error, and the measurement bias was estimated with the Bland–Altman method, with lower and upper limits of agreement.ResultsNo differences were observed when comparing the compression results (P = 0.51). The validity and internal intra-rater consistencies ranged from 0.84 to 0.99, and the standard error of measurement from 0.005 to 0.04 kPa. Very strong (r = 0.73–0.74) to near-perfect (r = 0.99) correlations were found, with a low risk of bias for all measurements. The results demonstrated the validity and intra-rater reliability of the digitally adapted pressure algometer. Inter-rater reliability results were moderate (r = 0.55–0.60; Cronbach’s α = 0.71–0.75).ConclusionThe adapted pressure algometer provide valid and reliable measurements of pressure pain threshold. The results support more widespread use of the pressure pain threshold method among clinicians.

Velocity Measurement of Blast Furnace Molten Iron Based on Local Multi-Feature Correction Using Multi-Stage Filtered High-Speed Camera

Accurately measuring the velocity of molten iron at the taphole of a blast furnace is of great significance for safe tapping and reflecting the operating state of the blast furnace. The presence of dust-induced brightness changes and weakly textured areas on the surface of molten iron seriously affects the accuracy of the surface velocity field reconstructed by traditional methods. This paper presents a local multi-feature correction using multi-stage filtered high-speed camera to achieve high-precision measurement of the surface velocity field of molten iron. First, two sets of local molten iron features were extracted according to a theoretical analysis of the influence of dust-induced brightness changes and the molten iron texture on the accuracy of combined local-global approach with total variation regularization (CLG-TV) and digital image correlation (DIC). Then, a mixed semifuzzy approximation network based on the characteristics of local molten iron features is proposed to estimate measurement errors under the influence of brightness changes and weak textures. Finally, an ingenious decision maker is designed to determine a more accurate displacement field of the molten iron surface. Additionally, a designed multi-stage filtered high-speed camera is installed beside the taphole to provide good optical images of molten iron surface. Industrial experiments and applications illustrate that the proposed method can stably and accurately measure the molten iron velocity at the taphole and provide reliable guidance for tapping operations.

Expanding G-Theory Models to Incorporate Congeneric Relationships: Illustrations Using the Big Five Inventory

We used structural equation modeling techniques to expand traditional generalizability theory (G-theory) models to allow for congeneric relationships among item responses while accounting for the primary sources of measurement error that affect results from objectively scored, self-report measures. Data came from 919 respondents who completed the Agreeableness, Conscientiousness, Extraversion, Neuroticism, and Openness subscales of the Big Five Inventory (BFI; John et al., 1991) on two occasions. When compared to traditional and factor-based essential tau-equivalent G-theory models, congeneric models on average yielded superior fit statistics, higher estimates of reliability, and lower estimates of transient and specific-factor measurement error. Essential tau-equivalent and congeneric factor models also were configured to allow for simultaneous partitioning of systematic and measurement error variance at both total score and individual item levels. We provide detailed guidelines, examples, and computer code in R for all models discussed in an extended online supplement to enable readers to apply the demonstrated techniques.

A New Profile Least-Squares Approach for Partially Linear Nonparametric Models with Measurement Errors

Partially linear nonparametric models, as a generalization of partially linear models and nonparametric models, have good adaptability and robustness. In this paper, based on the selection of this model, and a new method of contour least squares estimation, the focus is on the estimation of partially linear nonparametric models with measurement errors of covariance. Because when the measurement error is ignored, the parametric and non-parametric components are usually biased estimates. On this basis, we propose a modified contour least squares estimation of measurement error, and also obtain the error variance estimation results. Finally, through numerical simulation, the feasibility of the model proposed in this paper when the covariant has additive measurement error is verified.

Estimation of measurement error and depth of field in PDIA experiments: a comparative study using water droplets and a calibration target

The particle/droplet image analysis (PDIA) technique is often used for droplet sizing in sprays. Successful use of PDIA for drop size measurement in sprays mandates careful calibration, and determination of the depth of field (DOF) for particles of different size classes. This is typically done with a calibration target that has circles etched on it. In the present study, a calibration experiment was performed with a calibration target as well as droplets, to evaluate the uncertainties in the measured sizes and also to compare the measured DOF values. A continuous-jet droplet generator was used to produce mono-disperse droplets of sizes ranging from 54–393 µm, and the calibration glass plate used contained circles of sizes ranging from 20–400 µm. Images of these were captured using a CCD camera equipped with a long-distance microscope, and were processed using a code written in MATLAB®. Differences in the measured sizes of droplets and circles, and their DOF values are reported. It was observed that the use of the calibration target led to an underestimation of the error in droplet size measurements, and an overestimation of the DOF. For the droplets, the measurement error was observed to be less than 5%, with the parameters chosen.

Measurement error estimation and calibration for on-line detection phase variations in the laser-induced damage growth features of optical components.

The amplitude and phase distributions of reflection or transmission light are locally disturbed by damage regions. The damage state of optical components under successive laser irradiation can be evaluated according to the phase variation of a transmitted beam. The measurement accuracy of phase information related to the phase-unwrapping method is a critical factor for evaluating the damage state. This study analyzes and compares the performance of two important phase-unwrapping methods for detecting on-line large damage sites based on optimal modified lateral shearing interferometry. Meanwhile, the system stability and the measurement repeatability are also validated according to the retrieved phase pattern, which is beneficial to estimating the measurement accuracy. Experimental results of optical films are also presented and discussed to verify the feasibility of the estimation method utilized and the recommended phase-unwrapping method for on-line detection of the laser-induced damage growth features.

Estimation of errors in indirect measurement of aircraft aerodynamic angles using accelerometers and pressure sensors

Estimation of errors in indirect measurement of aircraft aerodynamic angles using accelerometers and pressure sensors

Optimization of prism-based stereoscopic imaging systems at the optical design stage with respect to required 3D measurement accuracy.

We address the optical design procedure of prism-based stereoscopic imaging systems. Conventional approach includes two sequential stages: selection of the hardware and development of the proper digital image processing algorithms. At each of these stages, specific techniques are applied, which are almost unrelated to each other. The main requirements to the imaging system include only the key parameters and the image quality. Therefore, the insufficient measurement accuracy may be revealed only after the prototype is assembled and tested. In this case, even applying complex time-consuming image processing and calibration procedures does not ensure the necessary precision. A radical solution of this issue is to include the measurement error estimation into the optical design stage. In this research, we discuss a simplified implementation of this approach and demonstrate the capabilities of optical design software for this purpose. We demonstrate the effectiveness of this approach by the analysis and optimization of a prism-based stereoscopic imager with respect to required 3D measurement accuracy. The results are meaningful for the development of 3D imaging techniques for machine vision, endoscopic and measurement systems.

Cyclist-vehicle crash modeling with measurement error in traffic exposure

Exposure measures are always among the explanatory variables of any crash model. Regardless of the technique used to model crash, the mean crash frequency will increase with an increase in exposure since more crashes are likely to occur at higher exposure. For cyclist-vehicle crash models, bike and vehicle exposure measures are essential for an accurate and reliable estimate of the cyclist crash risk. However, traffic exposure measures are an example of variables that are measured with error. Generally, measurement error in regression estimates has three effects: 1) produce bias in parameter estimation for statistical models, 2) lead to a loss of explanation power, 3) mask important features of the data. This study proposes a full Bayesian Poisson Lognormal crash models that account for measurement error in traffic exposure measures (i.e., Vehicle Kilometers Travelled and Bike Kilometers Travelled). The underlying approach is to adjust the traffic exposure measures for measurement error to improve the accuracy of the crash model and crash model estimates. The full Bayesian models are developed using data for 134 traffic analysis zones (TAZs) in the city of Vancouver, Canada. The results show that Poisson Lognormal models that account for measurement error have a better fit for the modeled cyclist-vehicle crash data compared to traditional Poisson Lognormal models. The estimates of the Poisson Lognormal model that accounts for measurement error are consistent, with traditional Poisson Lognormal models’ estimates except for the BKT and VKT estimates. Estimates of the BKT and VKT increased after introducing measurement error, which indicates an underestimation (downward bias) to BKT and VKT estimates in case of overlooking measurement error.

Analysis of measurement errors from electrical resistivity imaging investigation of First World War mining tunnels in La Boisselle, France

ABSTRACTTo derive reliable electrical resistivity subsurface models using error‐weighted inversion schemes, a meaningful and correct error model is required. An over‐estimated error leads to a lack of resolution and reduced target detectability. Furthermore, biased data are easily overlooked and can lead to artefacts and significant miss‐interpretation. We carried out an electrical resistivity tomography survey to detect mining tunnels of World War I in La Boisselle, France. French, British and German troops extensively used mining warfare, such as tunnel constructions, to undermine opponents. While the location and orientation of some British tunnels are known from archaeological excavations, the exact location of the German tunnels is currently unknown. Due to systematic measurement errors resulting from a malfunction in the system, the acquired electrical resistivity tomography data in La Boisselle were significantly biased. Therefore, a detailed systematic error analysis scheme was developed. Using a workflow of systematic error examination to identify biased data such as outliers or other bias, an unbiased dataset was retrieved. Subsequently, two‐dimensional electrical resistivity tomography inversions using different error models provided a qualitative estimate of how the data errors influence the tunnel detectability within an inversion scheme. The field data from La Boisselle demonstrates the importance of correctly estimating measurement errors, especially in view of the detection of small‐scale targets, such as tunnels.