Random Measurement Error Research Articles

Reliability of the Gap–Kalamazoo communication skills assessment form in occupational therapy

Introduction: The Gap–Kalamazoo Communication Skills Assessment Form (GKCSAF) is widely used in medical education, yet its reliability in real occupational therapy clinical settings remains unexplored. This study aimed to assess the intra-rater and inter-rater reliability, as well as random measurement error, of the GKCSAF in occupational therapy. Method: Five independent raters evaluated audio-recordings and transcripts of conversations involving 30 patients treated by 22 assessors (7 therapists and 15 students). Both direct and coded ratings were used. Results: For direct ratings, intra-rater reliability was moderate for total score (intraclass correlation coefficient (ICC) = 0.76), but poor for inter-rater (ICC = 0.31). minimal detectable change (MDC%) was acceptable for the same rater (17.8%) but not for different raters (38.3%). Weighted kappa values indicated poor to fair reliability (−0.01 to 0.34) for each domain score. Coded ratings showed moderate intra-rater reliability (ICC = 0.69) and poor inter-rater reliability (ICC = 0.22). MDC% was acceptable for the same rater (24.8%) but not for different raters (65.5%). Weighted kappa values indicated poor to fair reliability (−0.02 to 0.33) for each domain score. Conclusion: GKCSAF displays acceptable intra-rater but poor inter-rater reliability in occupational therapy clinical scenarios. Multiple raters are advised for enhanced reliability, while coding might not significantly enhance it. It is advisable to use the GKCSAF cautiously in occupational therapy education, ensuring adequate training, and possibly incorporating multiple raters for assessment consistency.

Accumulative Assessment of Upper Extremity.

The Fugl-Meyer assessment for upper extremity (FMA-UE) is a measure for assessing upper extremity motor function in patients with stroke. However, the considerable administration time of the assessment decreases its feasibility. This study aimed to develop an accumulative assessment system of upper extremity motor function (AAS-UE) based on the FMA-UE to improve administrative efficiency while retaining sufficient psychometric properties. The study used secondary data from 3 previous studies having FMA-UE datasets, including 2 follow-up studies for subacute stroke individuals and 1 test-retest study for individuals with chronic stroke. The AAS-UE adopted deep learning algorithms to use patients' prior information (ie, the FMA-UE scores in previous assessments, time interval of adjacent assessments, and chronicity of stroke) to select a short and personalized item set for the following assessment items and reproduce their FMA-UE scores. Our data included a total of 682 patients after stroke. The AAS-UE administered 10 different items for each patient. The AAS-UE demonstrated good concurrent validity (r = 0.97-0.99 with the FMA-UE), high test-retest reliability (intra-class correlation coefficient = 0.96), low random measurement error (percentage of minimal detectable change = 15.6%), good group-level responsiveness (standardized response mean = 0.65-1.07), and good individual-level responsiveness (30.5%-53.2% of patients showed significant improvement). These psychometric properties were comparable to those of the FMA-UE. The AAS-UE uses an innovative assessment method which makes good use of patients' prior information to achieve administrative efficiency with good psychometric properties. This study demonstrates a new assessment method to improve administrative efficiency while retaining psychometric properties, especially individual-level responsiveness and random measurement error, by making good use of patients' basic information and medical records.

Cognitive Functioning and the Quality of Survey Responses: An Individual Participant Data Meta-Analysis of 10 Epidemiological Studies of Aging.

Self-reported survey data are essential for monitoring the health and well-being of the population as it ages. For studies of aging to provide precise and unbiased results, it is necessary that the self-reported information meets high psychometric standards. In this study, we examined whether the quality of survey responses in panel studies of aging depends on respondents' cognitive abilities. Over 17 million survey responses from 157,844 participants aged 50 years and older in 10 epidemiological studies of aging were analyzed. We derived 6 common statistical indicators of response quality from each participant's data and estimated the correlations with participants' cognitive test scores at each study wave. Effect sizes (correlations) were synthesized across studies, cognitive tests, and waves using individual participant data meta-analysis methods. Respondents with lower cognitive scores showed significantly more missing item responses (overall effect size ρ^ = -0.144), random measurement error (ρ^ = -0.192), Guttman errors (ρ^ = -0.233), multivariate outliers (ρ^ = -0.254), and acquiescent responses (ρ^ = -0.078); the overall effect for extreme responses (ρ^ = -0.045) was not significant. Effect sizes were consistent across studies, modes of survey administsration, and different cognitive functioning domains, although some cognitive domain specificity was also observed. Lower-quality responses among respondents with lower cognitive abilities add random and systematic errors to survey measures, reducing the reliability, validity, and reproducibility of survey study results in aging research.

Correction: Interrogating Random and Systematic Measurement Error in Morphometric Data

Correction: Interrogating Random and Systematic Measurement Error in Morphometric Data

Interrogating Random and Systematic Measurement Error in Morphometric Data

Interrogating Random and Systematic Measurement Error in Morphometric Data

Active Compensation Technology for the Target Measurement Error of Two-Axis Electro-Optical Measurement Equipment.

For two-axis electro-optical measurement equipment, there are many error sources in parts manufacturing, assembly, sensors, calibration, and so on, which cause some random errors in the final measurement results of the target. In order to eliminate the random measurement error as much as possible and improve the measurement accuracy, an active compensation technique for target measurement error is proposed in this paper. Firstly, the error formation mechanism and error transfer model establishment of the two-axis electro-optical measurement equipment were studied, and based on that, three error compensation and correction methods were proposed: the least square (LS)-based error compensation method, adaptive Kalman filter(AKF)-based error correction method, and radial basis function neural network (RBFNN)-based error compensation method. According to the theoretical analysis and numerical simulation comparison, the proposed RBFNN-based error compensation method was identified as the optimal error compensation method, which can approximate the random error space surface more precisely, so that a more accurate error compensation value can be obtained, and in order to improve the measurement accuracy with higher precision. Finally, the experimental results proved that the proposed active compensation technology was valid in engineering applicability and could efficiently enhance the measurement accuracy of the two-axis electro-optical measurement equipment.

A general class of improved population variance estimators under non-sampling errors using calibrated weights in stratified sampling.

This paper proposes a new calibration estimator for population variance within a stratified two-phase sampling design. It takes into account random non-response and measurement errors, specifically applying this method to estimate the variance in Gas turbine exhaust pressure data. The study integrates additional information from two highly positively correlated auxiliary variables to develop a general class of estimators tailored for the stratified two-phase sampling scheme. The properties of these estimators, in terms of their biases and mean square errors, have been thoroughly examined and extensively analyzed through numerical and simulation studies. Furthermore, the calibrated weights of the strata are derived. The proposed estimators outperform the natural estimator of population variance. Finally, suitable recommendations have been made for survey statisticians intending to apply these findings to real-life problems.

Comparing revised latent state-trait models including autoregressive effects.

Understanding the longitudinal dynamics of behavior, their stability and change over time, are of great interest in the social and behavioral sciences. Researchers investigate the degree to which an observed measure reflects stable components of the construct, situational fluctuations, method effects, or just random measurement error. An important question in such models is whether autoregressive effects occur between the residuals, as in the trait-state occasion model (TSO model), or between the state variables, as in the latent state-trait model with autoregression (LST-AR model). In this article, we compare the two approaches by applying revised latent state-trait theory (LST-R theory). Similarly to Eid et al. (2017) regarding the TSO model, we show how to formulate the LST-AR model using definitions from LST-R theory, and we discuss the practical implications. We demonstrate that the two models are equivalent when the trait loadings are allowed to vary over time. This is also true for bivariate model versions. The different but same approaches to modeling latent states and traits with autoregressive effects are illustrated with a longitudinal study of cancer-related fatigue in Hodgkin lymphoma patients. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Constructions of statistical estimates of digital measurement error in the case of small samples

The paper presents a computational-experimental method for the construction of statistical estimates of the error of digital measurements carried out on complex technical objects with metrological support. The algorithm of construction of the estimation of the distribution density function of random error of measurements on the basis of complex application of methods of the theory of characteristic functions, the theory of Lie operator series and methods of statistical modeling in the processing of a limited amount of statistical information in the conditions of small samples is described. The solution of the practical problem on the construction of the estimation of the measurement error distribution density and the problem on the zero mark of the measuring instrument in the probabilistic formulation is given. The presented computational and experimental method can be used to construct statistical estimates for the probability distribution density of the general type, including those given by implicit functions, characteristic functions and operator series.

Concurrent validity and test-retest reliability for the assessment of body segment lengths using two-dimensional video-recordings in weightlifting

ABSTRACT The aims of this study were 1) to propose a simple two-dimensional (2D) video-based method to measure segment lengths in the clean and jerk during weightlifting competitions, and 2) to check concurrent validity and test-retest reliability compared to 3D video-based measurements. In the first part of the study, key body positions for the assessment of segment lengths via 2D measurement method were determined. In the second part, concurrent validity was verified, comparing the 2D segment length measurements to 3D measurements. In the third part, the test-retest reliability of the 2D approach was investigated. In the clean and in the jerk, the lift-off/start position and the position of maximum barbell velocity displayed a minimised offset between ‘real’ 3D segment lengths and 2D projections of the segment lengths. For the concurrent validity assessment, the overall random measurement error was 4.3% with concordance correlation coefficients ranging from 0.64 to 0.88. The standard error of measurement in the test-retest procedure was 2.4% on average with intraclass correlation coefficients ranging from 0.85 to 0.96. The proposed 2D video-based approach to measure body segment lengths during weightlifting exercises is proven to be a valid and reliable procedure.

Evaluation of measurement errors in the Patient-Oriented Eczema Measure (POEM) outcome.

The Patient-Oriented Eczema Measure (POEM) is the recommended core outcome instrument for atopic dermatitis (AD) symptoms. POEM is reported by recalling the presence/absence of seven symptoms in the last 7 days. To evaluate measurement errors in POEM recordings due to imperfect recall. Using data from a clinical trial of 247 AD patients aged 12-65 years, we analysed the reported POEM score (r-POEM) and the POEM derived from the corresponding daily scores for the same seven symptoms without weekly recall (d-POEM). We quantified recall error by comparing the r-POEM and d-POEM for 777 patient-weeks collected from 207 patients, and estimated two components of recall error: (1) recall bias due to systematic errors in measurements and (2) recall noise due to random errors in measurements, using a bespoke statistical model. POEM scores have a relatively low recall bias, but a high recall noise. Recall bias was estimated at 1.2 points lower for the r-POEM on average than the d-POEM, with a recall noise of 5.7 points. For example, a patient with a recall-free POEM of 11 (moderate) could report their POEM score anywhere from 5 to 14 (with 95% probability) because of recall error. Model estimates suggested that patients tend to recall itch and dryness more often than experienced (positive bias of less than 1 day), but less often for the other symptoms (bleeding, cracking, flaking, oozing/weeping and sleep disturbance; negative bias ranging 1-4 days). In this clinical trial data set, we found that patients tended to slightly underestimate their symptoms when reporting POEM, with significant variation in how well they were able to recall the frequency of their symptoms every time they reported POEM. A large recall noise should be taken into consideration when interpreting POEM scores.

Influence of dual purging jets on interferometric measurement of optical path difference

Incompressible large eddy simulations of dual purging jets at three Reynolds numbers of ReL = 1500, 1000, and 500 are performed, providing the database for simulated interferometric measurements subjected to the spatiotemporally varying temperature fields. The temperature is modeled as a passive scalar, and the index-of-refraction field is calculated from the air temperature and pressure using the modified Edlén equation. Based on wave optics, wavefront distortions of laser beams traversing the flow field are computed, and the optical path difference measurement is simulated. Statistical results of the velocity and temperature indicate distinctly different flow patterns at three Reynolds numbers. Spectral proper orthogonal decomposition is adopted to analyze the relationship between coherent flow structures and temperature wavepackets. There is a dominant frequency (St = 0.29) at ReL = 1500 and 1000, which is attributed to the Kelvin–Helmholtz instability, whereas the two jets have notable flapping behaviors at ReL = 500. The wavefront distortions are found to be insensitive to the Reynolds number. The effects of the flow region and tracing distance are examined, and the optical performances of different beam pairs for interferometry are evaluated. The optical beams passing through the outer shear layers of the dual jets and wall jets are distorted severely, resulting in large systematic and random errors in the interferometric measurement.

Base on -Learning Pareto Optimality for Linear Itô Stochastic Systems With Markovian Jumps

This article investigate the cooperative differential game (CDG) for continuous-time linear Itô stochastic systems with markovian jumps (SSMJ) to obtain the Pareto solutions. Different from most existing works studying nonzero-sum games, this article studies the CDG on the quadratic infinite horizon for the Itô-type SSMJ with unknown system matrix and transition probability. A novel <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$</tex-math> </inline-formula> -learning online algorithm is developed, which consists of that (i) the optimal control problem is equivalent to solving a stochastic algebraic Riccatic equation (ARE); (ii) the joint cost function is approximated by a critic neural network (NN) and Pareto efficient is approximated by two actor NNs. The rigorous stability analysis shows that the system state for SSMJ and the NN weight errors are uniformly ultimately bounded (UUB). Finally, the theory analysis is validated by a numerical example with detailed discussions. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In practical applications, many systems are often affected by the change of external environment or the failure of internal components, which leads to the random jump of system parameters. Markovian jump system can effectively describe the above problems. And when the system model is disturbed by the internal parameters, the system control input and external environment, the random errors of state measurement, and other random factors, the deterministic model can no longer accurately describe the controlled system. Therefore, the SSMJ can describe practical problems more accurately. By cooperation, in general, the cost one specific player incurs is not uniquely determined anymore. If all players decide, for example, to use their control variables to reduce the cost of player 1 as much as possible, a different minimum is attained for player 1 compared with that in the case where all players agree collectively to help a different player in minimizing his cost. So, depending on how the players choose to ‘divide’ their control efforts, a player incurs different ‘minima’. Therefore, we will design an online learning algorithm to obtain pareto solutions with different weights. On the other hand, in practice, it is difficult to obtain an accurate system model. In order to solve this problem, a novel scheme is designed by using <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$</tex-math> </inline-formula> -learning technology, which does not need system matrix.

Estimation of the density for censored and contaminated data

AbstractConsider a situation where one is interested in estimating the density of a survival time that is subject to random right censoring and measurement errors. This happens often in practice, like in public health (pregnancy length), medicine (duration of infection), ecology (duration of forest fire), among others. We assume a classical additive measurement error model with Gaussian noise and unknown error variance and a random right censoring scheme. Under this setup, we develop minimal conditions under which the assumed model is identifiable when no auxiliary variables or validation data are available, and we offer a flexible estimation strategy using Laguerre polynomials for the estimation of the error variance and the density of the survival time. The asymptotic normality of the proposed estimators is established, and the numerical performance of the methodology is investigated on both simulated and real data on gestational age.

Test-Retest Reliability, Criterion-Related Validity, and Ecological Validity of the Test of Visual-Motor Skills, Third Edition, in Kindergarten Children With Developmental Coordination Disorder.

Establishing empirical evidence on the psychometric properties of the Test of Visual-Motor Skills (3rd ed.; TVMS-3) is helpful for guiding its use as an assessment of visual-motor integration (VMI) skills in kindergarten children with developmental coordination disorder (DCD). To investigate the test-retest reliability, criterion-related validity, and ecological validity of the TVMS-3 in Taiwanese kindergarten children with DCD. A nonexperimental, descriptive, correlational design. A hospital in Central Taiwan. Fifty-seven kindergarten children with DCD were recruited in the study. Intraclass correlation coefficient, percentage of minimal detectable change, and paired t test (Wilcoxon signed rank test) were used to investigate the test-retest reliability of the TVMS-3. The correlations (Pearson's r) between the TVMS-3 accuracy score and the scores of each of the four domains and the adaptive behavior composite score of the Vineland Adaptive Behavior Scales (3rd ed.; Vineland-3) were calculated, respectively, to examine criterion-related validity and ecological validity. The accuracy score of the TVMS-3 had excellent test-retest reliability and acceptable random measurement error. Moreover, it showed good criterion-related validity and sufficient ecological validity with the Vineland-3 in Taiwanese kindergarten children with DCD. The accuracy score of the TVMS-3 is applicable to Taiwanese kindergarten children with DCD in clinical and research settings. Plain-Language Summary: The accuracy score of the Test of Visual-Motor Skills (3rd ed.; TVMS-3) is a useful assessment tool to detect deficits in visual-motor integration for Taiwanese kindergarten children with developmental coordination disorder. The TVMS-3 has excellent test-retest reliability, good criterion-related validity, and sufficient ecological validity.

Synchronous Vibration Parameter Recognition of Constant-Speed Blades Based on Blade Tip Clearance Measurement

A new method for the synchronous vibration parameter identification of constant-speed rotating blades based on blade tip clearance (BTC) measurement and blade tip timing (BTT) is introduced. A BTC sensor is used to measure the BTC when the blade tip passes through each sensor. The BTT method is used to determine whether the blade tip arrives in advance or lags. The geometric model between the BTC and the blade tip vibration displacement (BTVD) is established, and the BTVD of the blade tip passing through each sensor is obtained. Then, the nonlinear least squares method is used to determine the synchronous vibration parameters of the constant-speed rotating blade. The results show that with an increase in amplitude, the higher the accuracy of the vibration parameter identification proposed in this paper; with a decrease in the random error of the BTC measurement, the higher the accuracy of the vibration parameter identification proposed in this paper; with a decrease in the random error in the measurement of the blade disk dimensions, the higher the accuracy of the vibration parameter identification proposed in this paper. In addition, the smaller the ratio of the blade length to the blade disk radius, the higher the accuracy of the vibration parameter identification method introduced in this paper. Because the structure of the gas turbine compressor and turbine blade disk has a small blade disk ratio, the method proposed in this paper is suitable for the simultaneous vibration parameter identification of gas turbine compressor blades and turbine blades.

Adjusting for Random Measurement Error and Misclassification Using SIMEX

Adjusting for Random Measurement Error and Misclassification Using SIMEX

A muon high-resolution pseudorange measurement method: Application to muon navigation in confined spaces

Confined spaces such as polar regions, deep earth and deep ocean are crucial navigation scenarios where traditional navigation techniques have difficulty in obtaining external signals for positioning. The cosmic ray muons, which carry the spatial and energetic information, are easy to penetrate these confined spaces. Therefore, the unique muon characteristic provides a new perspective to estimate detector position, which can be considered using in confined spaces navigation. In this paper, a well-developed theory of muon navigation is established by combining a muon pseudorange measurement method. Moreover, an Equivalent Velocity Calculation Model (EVCM) and a Muon Sequence Matching Technology (MSMT) are proposed. The first model corrects flight pseudorange error caused by the relativistic energy loss and the second technology compensates the random error in pseudorange measurement. Further, a series of simulations are performed to analyze the muon events number which can be received by detector in different scenarios with the variations of zenith angle, detector area, varied detector plates gap, and muon flight distance. Meanwhile, the simulation results demonstrate that the muon navigation update rate every 10 minutes can reach 5.989 in confined spaces at 100 m, and further pseudorange error analysis indicates that the meter-level positioning accuracy can be acquired. Finally, we construct a muon coincidence measurement scheme and verify that the laws of the muon positioning system for high-energy muons are consistent with the simulation results.

A Case Study of the Short-Term Development of Body Composition and Substrate Utilization Following Prolonged Low-Intensity Ski Trekking with Inadequate Energy Intake in Svalbard

This case study aimed to examine the short-term development of body composition and substrate utilization (i.e., contribution of fat and carbohydrates to energy supply) following prolonged low-intensity ski trekking (LIST) with inadequate energy intake in an Arctic region. For 23 days, two highly aerobically fit, male recreational athletes (24 and 26 years) performed ~2 – 11 hours of LIST each day, while pulling supply sledges (initially ~80 kg) across the length of Svalbard’s largest island, Spitsbergen (~640 km). We estimated body composition using bioelectrical impedance analysis (BIA). For evaluation of substrate utilization, we analyzed pulmonary respiratory gas-exchange ratio (RER) using an ergospirometry system during treadmill trekking (ski trekking simulation). Results indicated that the energy intake of each participant during this unsupported expedition was ~21.4 MJ·day-1 (~5107 kcal·day-1), of which ~33% (~5.0 g·kg-1·day-1), ~51% (~3.4 g·kg-1·day-1), and ~16% (~2.4 g·kg-1·day-1) came from carbohydrates, fat, and proteins, respectively. Body mass decreased by 7.2 kg (8.4%) in Subject A, and 4.4 kg (5.2%) in Subject B. Absolute fat mass decreased by 5.4 kg (37%) and 4.7 kg (30%) in Subject A and Subject B, respectively, whereas the changes in fat-free mass (–1.8 kg in Subject A, and +0.3 kg in Subject B) were within the random measurement error of the BIA analyser. Changes in RER in Subject A (–0.01 to –0.02 units) were within the random measurement error, whereas the RER data in Subject B were not interpretable due to excessive fluctuations in ventilatory equivalent for oxygen. In conclusion, this study indicates that short-term, prolonged LIST, performed with an energy deficit corresponding to a weight loss of ~2 kg·week-1, can lead to leaner body composition without notable changes in fat-free mass in well-trained, male recreational athletes. Furthermore, substrate utilization does not appear to be affected by short-term, prolonged LIST in this subgroup of athletes.

Laser Heterodyne Detection Based on Photon Time–Domain Differential Detection Avoiding the Effect of Decoherence Phase Noise

Laser heterodyne detection (LHD) is a key velocimetry technique that provides better accuracy and sensitivity than direct laser detection. However, random phase noise can be introduced by the surface topography of the moving target undulation or atmospheric turbulence during transmission. The random phase noise causes the target echo to undergo decoherence, resulting in degradation of the signal-to-noise ratio (SNR). Here, we propose a novel LHD method based on photon time–domain differential detection. It can infer the heterodyne spectrum of the target echo and the local oscillator light from the time intervals of the photon arrival. The time interval statistic is a relative quantity, which can effectively avoid the effect of random phase noise in LHD. With our method, the SNR of LHD can be improved in application scenarios where the target echo is decoherent. We developed a complete solution model for acquiring the heterodyne spectrum based on photon time–domain differential detection and performed proof-of-principle experiments. The experimental results show that in the presence of random phase noise, the SNR and velocity measurement error of our method are significantly better than that of the conventional method, and the larger the phase noise is, the more the SNR and velocity measurement error of our method are improved. Moreover, along with the increase in phase noise, the SNR of our method is basically unchanged, which also indicates that our method is not affected by random phase noise. This advantage is significant for photon-level weak echoes that require long detection times to be detected.