Random Measurement Error Research Articles

Concepts and Software Package for Efficient Quality Control in Targeted Metabolomics Studies: MeTaQuaC.

Targeted quantitative mass spectrometry metabolite profiling is the workhorse of metabolomics research. Robust and reproducible data are essential for confidence in analytical results and are particularly important with large-scale studies. Commercial kits are now available which use carefully calibrated and validated internal and external standards to provide such reliability. However, they are still subject to processing and technical errors in their use and should be subject to a laboratory's routine quality assurance and quality control measures to maintain confidence in the results. We discuss important systematic and random measurement errors when using these kits and suggest measures to detect and quantify them. We demonstrate how wider analysis of the entire data set alongside standard analyses of quality control samples can be used to identify outliers and quantify systematic trends to improve downstream analysis. Finally, we present the MeTaQuaC software which implements the above concepts and methods for Biocrates kits and other target data sets and creates a comprehensive quality control report containing rich visualization and informative scores and summary statistics. Preliminary unsupervised multivariate analysis methods are also included to provide rapid insight into study variables and groups. MeTaQuaC is provided as an open source R package under a permissive MIT license and includes detailed user documentation.

Data validation and reconciliation for error correction and gross error detection in multiphase allocation systems

In upstream oil and gas production, flow measurement errors are common at multiple locations in the production system. These measurement errors lead to imbalances, which are reconciled by using allocation methods. The allocation method should redistribute the imbalance in a fair manner to all involved stakeholders. In this paper, data validation and reconciliation (DVR) is proposed as an alternative allocation method in multiphase production systems. DVR is a model-based optimization method that exploits redundancies in process data to minimize random measurement errors, and simultaneously provides a basis for the detection of gross errors. To study the applicability of DVR compared to conventional allocation methods, a model for generic multiphase production systems is developed, and the corresponding DVR problem is formulated. In order to deal with nonlinear flow effects (e.g. interphase mass transfer) the model is linearized around the operating conditions and the DVR problem is solved iteratively. From the simulation studies, it is concluded that DVR reduces measurement errors by up to 56% for gas allocation systems and 33% for multiphase systems. Gross errors in interior locations of the network can be located precisely, while allocating gross errors to exterior locations is generally not possible, due to limited network redundancy. Compared to conventional methods, DVR provides a better means for the detection of gross errors, and results in more accurate attribution of oil/gas ownership and more fair division of revenues between stakeholders.

Vision-Based Methodology for Characterizing the Flow of a High-Density Crowd on Footbridges: Strategy and Application

Obtaining pedestrian trajectories by a vision-based methodology is receiving increasing attention in the literature over recent decades. Within the field of study of human-induced vibrations on footbridges, practical challenges arise when collecting the trajectories of high-density crowds during measurement campaigns. A cheap and robust methodology tackling these issues is presented and applied on a case study consisting of a real-life footbridge occupied with many pedestrians. A static camera setup consisting of low-cost action cameras with limited installation height is used. In addition, a drone camera was employed to collect a limited amount of footage. Pedestrians are equipped with colored hats and detected using a straightforward color-segmenting approach. The measurements are subjected to both systematic and random measurement errors. The influence of the former is theoretically investigated and is found to be of limited importance. The effect of the latter is minimized using a Kalman filter and smoother. A thorough assessment of the accuracy results reveals that the remaining uncertainty is in the order of magnitude of 2 to 3 cm, which is largely sufficient for the envisaged purpose. Although the methodology is applied on a specific case study in the present work, the conclusions regarding the obtained accuracy and employability are generic since the measurement setup can be extended to a footbridge with virtually any length. Moreover, the empirically obtained results of the presented case study should find use in the calibration of pedestrian dynamic models that describe the flow of high-density crowds on footbridges and the further development of load models describing crowd-induced loading.

Measurement properties of the musculoskeletal health questionnaire (MSK-HQ): a between country comparison

BackgroundThe Musculoskeletal Health Questionnaire (MSK-HQ) has been developed to measure musculoskeletal health status across musculoskeletal conditions and settings. However, the MSK-HQ needs to be further evaluated across settings and different languages.ObjectiveThe objective of the study was to evaluate and compare measurement properties of the MSK-HQ across Danish (DK) and English (UK) cohorts of patients from primary care physiotherapy services with musculoskeletal pain.MethodsMSK-HQ was translated into Danish according to international guidelines. Measurement invariance was assessed by differential item functioning (DIF) analyses. Test-retest reliability, measurement error, responsiveness and minimal clinically important change (MCIC) were evaluated and compared between DK (n = 153) and UK (n = 166) cohorts.ResultsThe Danish version demonstrated acceptable face and construct validity. Out of the 14 MSK-HQ items, three items showed DIF for language (pain/stiffness at night, understanding condition and confidence in managing symptoms) and three items showed DIF for pain location (walking, washing/dressing and physical activity levels). Intraclass Correlation Coefficients for test-retest were 0.86 (95% CI 0.81 to 0.91) for DK cohort and 0.77 (95% CI 0.49 to 0.90) for the UK cohort. The systematic measurement error was 1.6 and 3.9 points for the DK and UK cohorts respectively, with random measurement error being 8.6 and 9.9 points. Receiver operating characteristic (ROC) curves of the change scores against patients’ own judgment at 12 weeks exceeded 0.70 in both cohorts. Absolute and relative MCIC estimates were 8–10 points and 26% for the DK cohort and 6–8 points and 29% for the UK cohort.ConclusionsThe measurement properties of MSK-HQ were acceptable across countries, but seem more suited for group than individual level evaluation. Researchers and clinicians should be aware that some discrepancy exits and should take the observed measurement error into account when evaluating change in scores over time.

The initial engraftment of tumor cells is critical for the future growth pattern: a mathematical study based on simulations and animal experiments

BackgroundXenograft mouse tumor models are used to study mechanisms of tumor growth and metastasis formation and to investigate the efficacy of different therapeutic interventions. After injection the engrafted cells form a local tumor nodule. Following an initial lag period of several days, the size of the tumor is measured periodically throughout the experiment using calipers. This method of determining tumor size is error prone because the measurement is two-dimensional (calipers do not measure tumor depth). Primary tumor growth can be described mathematically by suitable growth functions, the choice of which is not always obvious. Growth parameters provide information on tumor growth and are determined by applying nonlinear curve fitting.MethodsWe used self-generated synthetic data including random measurement errors to research the accuracy of parameter estimation based on caliper measured tumor data. Fit metrics were investigated to identify the most appropriate growth function for a given synthetic dataset. We studied the effects of measuring tumor size at different frequencies on the accuracy and precision of the estimated parameters. For curve fitting with fixed initial tumor volume, we varied this fixed initial volume during the fitting process to investigate the effect on the resulting estimated parameters. We determined the number of surviving engrafted tumor cells after injection using ex vivo bioluminescence imaging, to demonstrate the effect on experiments of incorrect assumptions about the initial tumor volume.ResultsTo select a suitable growth function, measurement data from at least 15 animals should be considered. Tumor volume should be measured at least every three days to estimate accurate growth parameters. Daily measurement of the tumor volume is the most accurate way to improve long-term predictability of tumor growth. The initial tumor volume needs to have a fixed value in order to achieve meaningful results. An incorrect value for the initial tumor volume leads to large deviations in the resulting growth parameters.ConclusionsThe actual number of cancer cells engrafting directly after subcutaneous injection is critical for future tumor growth and distinctly influences the parameters for tumor growth determined by curve fitting.

Tomographic filtering via the generalized inverse: a way to account for seismic data uncertainty

SUMMARY Tomographic-geodynamic model comparisons are a key component in studies of the present-day state and evolution of Earth’s mantle. To account for the limited seismic resolution, ‘tomographic filtering’ of the geodynamically predicted mantle structures is a standard processing step in this context. The filtered model provides valuable information on how heterogeneities are smeared and modified in amplitude given the available seismic data and underlying inversion strategy. An important aspect that has so far not been taken into account are the effects of data uncertainties. We present a new method for ‘tomographic filtering’ in which it is possible to include the effects of random and systematic errors in the seismic measurements and to analyse the associated uncertainties in the tomographic model space. The ‘imaged’ model is constructed by computing the generalized-inverse projection (GIP) of synthetic data calculated in an earth model of choice. An advantage of this approach is that a reparametrization onto the tomographic grid can be avoided, depending on how the synthetic data are calculated. To demonstrate the viability of the method, we compute traveltimes in an existing mantle circulation model (MCM), add specific realizations of random seismic ‘noise’ to the synthetic data and apply the generalized inverse operator of a recent Backus–Gilbert-type global S-wave tomography. GIP models based on different noise realizations show a significant variability of the shape and amplitude of seismic anomalies. This highlights the importance of interpreting tomographic images in a prudent and cautious manner. Systematic errors, such as event mislocation or imperfect crustal corrections, can be investigated by introducing an additional term to the noise component so that the resulting noise distributions are biased. In contrast to Gaussian zero-mean noise, this leads to a bias in model space; that is, the mean of all GIP realizations also is non-zero. Knowledge of the statistical properties of model uncertainties together with tomographic resolution is crucial for obtaining meaningful estimates of Earth’s present-day thermodynamic state. A practicable treatment of error propagation and uncertainty quantification will therefore be increasingly important, especially in view of geodynamic inversions that aim at ‘retrodicting’ past mantle evolution based on tomographic images.

Influence of heating intensity and size of gel fuel droplets on ignition characteristics

This experimental research studies the influence of heating intensity and typical initial size of particles (or droplets in molten state) on the main process parameter – ignition delay time – for a group of gel fuel compositions. The first group of fuels is based on oil-filled cryogels: the aqueous solution of polyvinyl alcohol (5 wt%) + 40–60 vol% of oil + 2 vol% of emulsifier. The second one was produced from identical oil-filled cryogels with fine solid combustible particles: the aqueous solution of polyvinyl alcohol (10 wt%) + 35 vol% of oil + 30% of coal (particle size 100 µm) + 2 vol% of emulsifier. Combustion was initiated in a chamber with a motionless air medium at 700–1,000°C, by introducing fuel particles into it at a rate of 0.04–0.10 m/s, their size varying from 2.5 to 3.1 mm. The consistent patterns and characteristics of processes during the induction period were recorded by a high-speed video camera and fast-response thermocouples. It has been established that the ignition delay times change in the range from 0.5 to 15 s, depending on the heating intensity (characterized by the air temperature in the chamber and the rate of introducing fuel particles into it) and component composition of the gel fuel. The calculated minimum density of the heat flux, required for the gel fuel ignition, is 40 kW/m2. At lower values, ignition does not occur even when the fuel is heated for more than 15 s, which is due to the complete evaporation of molten fuel components. The ignition delay times for all the fuel compositions and particles of different sizes differ by less than 10% (random error of measurement) at the heat flux density over 100 kW/m2. The factors under study affect the duration of the induction period only under the near-threshold (minimum) ignition conditions, when the air temperature in the chamber is 700–800°C. The higher the rates of introducing the fuel particles into the heating chamber (in the range of 0.04–0.10 m/s), the higher the oil concentration in the oil-filled cryogels (in the range of 40–60%), and the smaller the size of particles (ranging from 2.5 to 3.1 mm), the shorter the ignition delay times (by 30–40%, 25–35%, and 20–45%, respectively). At air temperatures above 900°C, the initial size of fuel particles does not have a significant effect on the ignition delay times (the difference in the recorded values does not exceed the random error of measurement).

On the (Lack of) Evolution of the Stellar Mass Function of Massive Galaxies from z = 1.5 to 0.4

Abstract We study the evolution in the number density of galaxies at the highest stellar masses over the past ≈9 Gyr ( ) using the Spitzer/HETDEX Exploratory Large-Area Survey (SHELA). SHELA includes complete imaging in eight photometric bands spanning 0.3–4.5 μm over 17.5 deg2 within the SDSS Stripe 82 field. The size of SHELA produces the lowest counting uncertainties and cosmic variance yet for massive galaxies at z ∼ 1.0. We study the evolution in the intrinsic stellar mass function (SMF) for galaxies with using a forward-modeling method that takes into full account the statistical and systematic uncertainties on stellar mass. From z = 0.4 to 1.5, the evolution in the massive end of the intrinsic SMF shows minimal change in its shape: the characteristic mass (M*) evolves by less than 0.1 dex (±0.05 dex); furthermore, the number density of galaxies with 11 stays roughly constant at (±0.05) from z = 1 to z = 0.4, consistent with no evolution, then declines to = −3.7 (±0.05) at z = 1.5. We discuss the uncertainties in the derived SMF, which are dominated by assumptions in the star formation history and details of stellar population synthesis models for stellar mass estimations. We also study the evolution in the SMF for samples of star-forming and quiescent galaxies selected by their specific star formation rate. For quiescent galaxies, the data are consistent with no (or slight) evolution (≲0.1 dex) in either the characteristic mass or number density from z ∼ 1.5 to the present even after accounting for the systematic uncertainty and the random error in the stellar mass measurement. The lack of number density evolution in the quiescent massive galaxy population means that any mass growth (presumably through “dry” mergers) must balance the rate of stellar mass losses owing to processes of late-stage stellar evolution and the formation of newly quiescent galaxies from the star-forming population. We provide an upper limit on this mass growth from z = 1.0 to 0.4 of ΔM */M * = 45% (i.e., ≃0.16 dex) for quiescent galaxies more massive than 1011 M ⊙.

Absolute reliability of tongue pressure measurement in young healthy adults and elderly patients with certification of needing long-term care or support.

We aimed to determine systematic bias and the range of random error in tongue pressure measurements among young healthy adults and elderly patients with certification of requiring long-term care or support, considering sex, and to establish a measurement method. Subjects were 226 adults (88 young healthy adults and 138 elderly patients with certification of requiring long-term care or support). Tongue pressure was measured thrice. Bland-Altman analysis was performed for the first and second trials, and second and third trials. Fixed bias was revealed for the first and second trials among young healthy adults. Systematic bias was not found for the second and third trials. Fixed bias was revealed for the first and second trials among elderly patients, with a proportional bias with a negative slope for the second and third trials. For young healthy adults, the minimal detectable change was 6.0 and 5.4 kPa in males and females, respectively. For elderly patients, the limit of agreement ranged from -5.9 to 8.6 and from -5.4 to 8.8 kPa in males and females, respectively. There was a difference in systematic bias in tongue pressure measurement between young healthy adults and elderly patients with certification of needing long-term care or support. In young healthy adults, the third trial results showed stability, whereas they decreased in elderly patients. In elderly patients, it was suggested that the number of measurements reduced from three to two when a maximum value was adopted. No differences were observed among sexes in either young or elderly patients. Geriatr Gerontol Int 2020; 20: 488-493.

Reliability and discriminative accuracy of 5 measures for craniocaudal humeral position: an assessment on conventional radiographs

HypothesisThis study aimed to examine the reliability and diagnostic discriminative accuracy of 5 different methods that quantity the craniocaudal humeral position with respect to the scapula on conventional radiographs.MethodsIn this retrospective, cross-sectional diagnostic study, 2 observers randomly assessed the conventional anteroposterior shoulder radiographs of 280 subjects with rotator cuff imaging for the (1) acromiohumeral (AH) interval, (2) upward migration index (UMI), (3) glenohumeral center-to-center measurement (GHCC), (4) glenohumeral arc measurement (GHa), and (5) scapular spine–humeral head center method (SHC). Reliability was assessed by means of relative consistency (intraclass correlation coefficient) and absolute consistency. Discriminative accuracy for detecting a rotator cuff tear was calculated.ResultsRelative consistency (intraclass correlation coefficient) for the AH interval, UMI, GHCC, GHa, and SHC was 0.961, 0.913, 0.806, 0.924, and 0.726, respectively. The AH interval had the highest absolute consistency with a random residual measurement error of 0.58 mm compared with 1.0-3.2 mm for the other measurements. The discriminative accuracy of the AH interval did not significantly differ from that of the UMI (−0.010; 95% confidence interval [CI], −0.042 to 0.022; P = .545) but was significantly better than that of the GHCC (0.112; 95% CI, 0.043-0.181; P = .001), GHa (0.074; 95% CI, 0.009-0.139; P = .027), and SHC (0.178; 95% CI, 0.100-0.256; P < .001).ConclusionAssessment of the craniocaudal humeral position is performed with good to excellent intraobserver and interobserver reliability. The discriminative accuracy for detecting a rotator cuff tear on a single radiograph was highest for the AH interval and UMI. We recommend using the AH interval or UMI as an indirect measure of the presence of a rotator cuff tear on conventional radiographs.

Are "Dichotic" Deficits Uniquely Dichotic? Investigating Dichotic Performance with the Dichotic Digits Difference Test (DDdT) in a Large Clinical Population of Children Referred for an Auditory Processing Assessment.

Previous studies in a large population of typically developing (TD) children and a small clinical group showed high correlations between the dichotic and diotic conditions of the Dichotic Digits difference Test (DDdT), as well as between DDdT performance and measures of memory and attention. The purpose of the study was to investigate the performance on the DDdT in a large clinical sample. Correlational analysis between the DDdT diotic condition and the dichotic free recall (FR) right-ear, left-ear, and total (ear-averaged) conditions, as well as between DDdT and memory performance. One hundred one children (6 years 3 months to 15 years 0 month, mean 9 years 6 months) were referred for assessment to the Australian Hearing Central Auditory Processing Disorder (CAPD) service. Results were compared with data from 112 TD children collected from previously published studies. Z-scores were used to account for the effect of age on performance. Mean differences between clinical and TD children were investigated using analysis of variance (ANOVA). Pearson product-moment correlations determined the strength of relationships between DDdT conditions and the number memory forward (NMF) and reversed (NMR) subtests of the Test of Auditory Processing Skills-Third Edition. Performance by the clinical group on the DDdT dichotic FR (RE, LE, and total) conditions was significantly correlated with the diotic condition (r = 0.7; 0.7, 0.8; p < 0.001). Significant correlations were found between the DDdT diotic and dichotic FR conditions and the NMF (r = 0.5-0.6, p < 0.001) and NMR (r = 0.2-0.5, p < 0.025-0.001). ANOVA revealed no significant difference between the TD and clinical groups (p = 1.0000) in respect to the advantage they got from dichotic listening (calculated as dichotic FR total minus diotic score). Multiple regression revealed that diotic performance and short-term memory accounted for 68% of the variation in dichotic performance. Random measurement error accounted for a further 16%. Factors other than dichotic performance strongly impact a child's ability to perform a dichotic digit listening task. This result has widespread implications in respect to the interpretation of CAPD test results.

Determination of the single point precision associated with tactile gear measurements in scanning mode

Abstract. The framework of the single point uncertainty developed at the Institute of Manufacturing Metrology (FMT) presents a methodology to determine and evaluate the local measurement uncertainty for a measurement setup by local comparison of a measurement series with an associated reference geometry. This approach, which was originally developed and optimized for the processing of complete areal measurements of work pieces using industrial X-ray computed tomography, was now also extended to line scans found in dimensional testing using tactile coordinate measuring machines (CMMs). The targets of the investigation are spur (involute) steel gear wheels, which can be dimensionally characterized by both helix and profile scans using a CMM in scanning mode in combination with a rotatory table. A second measurement procedure is characterized by a single scan of the complete gear profile without the usage of a rotatory table, using the “free-form scan” CMM functionality. The modification of the single point uncertainty framework in order to determine the single point precision of repeated gear wheel measurements was implemented successfully for gear measurements using the Zeiss Gear Pro evaluation software in combination with a rotatory table as well as unassisted free-form scans of the same gear. The examinations yielded abnormally high random measurement errors, which could not fully be explained within our examinations and was for the most part caused by the accuracy of the used rotatory table of the CMM. The alternative measurement method showed that the CMM system is capable of measuring very precisely in scanning mode if the changes in the curvature of the scan trajectory are favourable.

Practice Effects and Test-Retest Reliability of the Continuous Performance Test, Identical Pairs Version in Patients with Schizophrenia over Four Serial Assessments.

The purposes of this study were to examine the practice effects and test-retest reliability of the Continuous Performance Test, Identical Pairs version (CPT-IP) over four serial assessments in patients with schizophrenia. Fifty-six patients with schizophrenia were assessed with the CPT-IP four times, once per week. The CPT-IP contains four indices: "2-digit score," "3-digit score," "4-digit score," and "total score." The four indices showed trivial-to-small practice effects (Cohen's d=-0.13-0.24), good-to-excellent test-retest reliability (ICC=0.62-0.88), and unacceptable random measurement error (MDC%=33.8%-110.8%). The total score had the best reliability among the four indices. Although practice effects of the four indices all appeared cumulative, all four CPT-IP indices reached a plateau after the second assessment. These results indicate that clinicians should interpret the change scores of the CPT-IP conservatively and use the total-score index in their routine repeated assessments.

Determination of the single point uncertainty of customized polymer gear wheels using structured-light scanning with various polygonization settings

Abstract. During the manufacturing of work pieces, geometrical deviations from the intended nominal geometry of the designer are inevitable. The procedure of conformance testing defined in ISO 14253-1:2018-07 is used to ensure the function of a work piece by verifying the geometrical compliance with pre-defined tolerance specifications. Depending on the measurement setup used for the validation step, it is possible that the local measurement uncertainty is too large in order to provide a meaningful conformance evaluation. This paper aims to demonstrate the complete workflow of the determination of the locally defined single point uncertainty and its components (systematic and random measurement error, respectively) for a given measurement task. It was shown for an optical measurement setup in combination with an industrial X-ray computed tomography reference measurement system that different necessary colouring methods of polymer (POM) gear wheels, which are required to enable measurements using structured-light scanning, have a measurable influence on the local distribution of the measurement uncertainty. Because of the fact that the presented method is dependent on a discrete surface sampling, the effects of different polygonization settings during the creation of the areal measurement result were evaluated in order to rate the reduced data complexity against the hereby possibly increased measurement uncertainty. The gained information regarding the local measurement uncertainty of a measurement setup can then be used for downstream processes in various use cases, e.g. for the improvement of holistic tolerance simulation models or the improvement of geometrical measurements using weighted regression analysis. Additionally, the visualization of the areal distribution of the measurement uncertainty enables a powerful tool to optimize the used measurement setup.

Methods for Evaluating Causality in Observational Studies.

In clinical medical research, causality is demonstrated b controlled trials (RCTs). Often, however, an RCT cannot be conducted for ethical reasons, and sometimes for practical reasons as well. In such cases, knowledge can be derived from an observational study instead. In this article, we present two methods that have not been widely used in medical research to date. The methods of assessing causal inferences in observational studies are described on the basis of publications retrieved by a selective literature search. Two relatively new approaches-regression-discontinuity methods and interrupted time series-can be used to demonstrate a causal relationship under certain circumstances. The regression-discontinuity design is a quasi-experimental approach that can be applied if a continuous assignment variable is used with a threshold value. Patients are assigned to different treatment schemes on the basis of the threshold value. For assignment variables that are subject to random measurement error, it is assumed that, in a small interval around a threshold value, e.g., cholesterol values of 160 mg/dL, subjects are assigned essentially at random to one of two treatment groups. If patients with a value above the threshold are given a certain treatment, those with values below the threshold can serve as control group. Interrupted time series are a special type of regression-discontinuity design in which time is the assignment variable, and the threshold is a cutoff point. This is often an external event, such as the imposition of a smoking ban. A before-and-after comparison can be used to determine the effect of the intervention (e.g., the smoking ban) on health parameters such as the frequency of cardiovascular disease. The approaches described here can be used to derive causal inferences ies. They should only be applied after the prerequisites for their use have been carefully checked.

Nonlinear and time-dependent effects of sparsely measured continuous time-varying covariates in time-to-event analysis.

Many flexible extensions of the Cox proportional hazards model incorporate time-dependent (TD) and/or nonlinear (NL) effects of time-invariant covariates. In contrast, little attention has been given to the assessment of such effects for continuous time-varying covariates (TVCs). We propose a flexible regression B-spline-based model for TD and NL effects of a TVC. To account for sparse TVC measurements, we added to this model the effect of time elapsed since last observation (TEL), which acts as an effect modifier. TD, NL, and TEL effects are estimated with the iterative alternative conditional estimation algorithm. Furthermore, a simulation extrapolation (SIMEX)-like procedure was adapted to correct the estimated effects for random measurement errors in the observed TVC values. In simulations, TD and NL estimates were unbiased if the TVC was measured with a high frequency. With sparse measurements, the strength of the effects was underestimated but the TEL estimate helped reduce the bias, whereas SIMEX helped further to correct for bias toward the null due to "white noise" measurement errors. We reassessed the effects of systolic blood pressure (SBP) and total cholesterol, measured at two-year intervals, on cardiovascular risks in women participating in the Framingham Heart Study. Accounting for TD effects of SBP, cholesterol and age, the NL effect of cholesterol, and the TEL effect of SBP improved substantially the model's fit to data. Flexible estimates yielded clinically important insights regarding the role of these risk factors. These results illustrate the advantages of flexible modeling of TVC effects.

Influence of different mounting strategies on the random measurement error in industrial computed tomography

In order to perform measurements in industrial computed tomography (CT), the specimen in question has to be mounted on the kinematic system of the CT device. In principle this applies to all measuring machines, however, it is an especially critical step of a CT measurement as there are no companies providing mounting systems in particular for CT applications that have been tried and tested by many years of usage. As a mounting system for CT applications should not interfere with x-ray beams to ensure an uncorrupted measurement, many users rely on special mountings cut from foam, 3D printed mounts or custom- made parts. However, there has not been a systematic survey on which mounting strategy leads to minimal random error in measurement results. Therefore, this paper aims at determining the influence of different mounting strategies on the random measurement error and image quality of the resulting scans. To this end, measurements of a defined test-object using different mountings are performed and compared with respect to these quality parameters. Finally, a recommendation for the optimal choice of a mounting system based on the results is given.

Proxy Means Testing Vulnerability to Measurement Errors?

Proxy Means Testing (PMT) is a popular method to target the poor in developing countries. PMT usually relies on survey-based consumption data and assumes random measurement errors – an assumption that has been challenged by recent literature. Using a survey experiment conducted in Tanzania, this paper brings causal evidence on the impact of non-random errors on PMT performances. Results show that non-random errors bias the coefficients from PMT models, resulting in a 5 to 27 per cent reduction in PMT predictive performances. Moreover, non-random errors induce a 10 to 34 per cent increase in the incidence of targeting errors when poverty is defined in absolute terms. More reassuringly, impacts on the ranking of households are smaller and essentially non-significant. Taken together, these results indicate that PMT performances are quite vulnerable to non-random errors when the objective is to target absolutely poor households, but remain largely unaffected when the objective is to target a fixed share of the population.

Automated evaluation of the surface point quality in dimensional X-ray computed tomography

AbstractX-ray computed tomography (CT) enables dimensional measurements of numerous measurands with a single scan, including the measurement of inner structures. However, measurement artefacts complicate the applicability of the technology in some cases. This paper presents a methodology to assess the surface point quality of computed tomography measurements without the requirement of a CAD model. Measurement artefacts lowering the surface point quality can therefore automatically be detected. The correlation of quality values with the random measurement error is demonstrated. The presented method can in principle be used to weight single fit points to reduce the measurement uncertainty of CT measurements.

Use Omega Rather than Cronbach’s Alpha for Estimating Reliability. But…

ABSTRACTCronbach’s alpha (α) is a widely-used measure of reliability used to quantify the amount of random measurement error that exists in a sum score or average generated by a multi-item measurement scale. Yet methodologists have warned that α is not an optimal measure of reliability relative to its more general form, McDonald’s omega (). Among other reasons, that the computation of is not available as an option in many popular statistics programs and requires items loadings from a confirmatory factor analysis (CFA) have probably hindered more widespread adoption. After a bit of discussion of α versus , we illustrate the computation of using two structural equation modeling programs (Mplus and AMOS) and the MBESS package for R. We then describe a macro for SPSS and SAS (OMEGA) that calculates in two ways without relying on the estimation of loadings or error variances using CFA. We show that it produces estimates of that are nearly identical to when using CFA-based estimates of item loadings and error variances. We also discuss the use of the OMEGA macro for certain forms of item analysis and brief form construction based on the removal of items from a longer scale.