Nonparametric Evidence of Validity,Reliability, and Fairness for Rater‐Mediated Assessments: An Illustration Using Mokken Scale Analysis

Numerous researchers have proposed methods for evaluating the quality of rater‐mediated assessments using nonparametric methods (e.g., kappa coefficients) and parametric methods (e.g., the many‐facet Rasch model). Generally speaking, popular nonparametric methods for evaluating rating quality are not based on a particular measurement theory. On the other hand, popular parametric methods for evaluating rating quality are often based on measurement theories such as invariant measurement. However, these methods are based on assumptions and transformations that may not be appropriate for ordinal ratings. In this study, I show how researchers can use Mokken scale analysis (MSA), which is a nonparametric approach to item response theory, to evaluate rating quality within the framework of invariant measurement without the use of potentially inappropriate parametric techniques. I use an illustrative analysis of data from a rater‐mediated writing assessment to demonstrate how one can use numeric and graphical indicators from MSA to gather evidence of validity, reliability, and fairness. The results from the analyses suggest that MSA provides a useful framework within which to evaluate rater‐mediated assessments for evidence of validity, reliability, and fairness that can supplement existing popular methods for evaluating ratings.     

Stochastic simulation and analysis of geological corrosion defects in dam foundation

Uncertainty in geological structural modeling, especially geological corrosion(a kind of karst cave), is a bottleneck that restricts the development and application of geological computer modeling and effect estimation. To solve this issue, a stochastic modeling method based on the random field theory is proposed in comparison with the deterministic geometric modeling method. Then the constraint random field modeling method and the random field modeling method without constrained parameters are compared and analyzed. A case study shows that the novel stochastic simulation method is an effective tool to describe the distribution characteristics of corrosion parameters and reflect the updated geological prospecting information. The influence of geological corrosion on the dam behavior can also be better analyzed by using the stochastic simulation method. At the same time, the unconfined random field ignores the sample location information and may lead to higher variability. Therefore, the constraint random field modeling method can provide a useful reference for the numerical analysis under complex geological conditions.     

基于神经网络重要抽样法的结构可靠度评估

文章提出基于神经网络重要抽样法的结构可靠度评估方法,该方法通过训练神经网络,建立随机变量与结构响应之间的非线性映射关系,模拟结构极限状态方程,采用优化算法计算设计点．在重要抽样法中利用训练好的神经网络代替有限元求解器进行数值计算．结果表明,所训练的神经网络能够有效地模拟真实的结构极限状态方程,结构失效概率计算结果具有很高的精度,调用有限元分析的次数显著减少,有效地提高了计算效率．     

考虑高阶相关性的灌注桩沉降可靠度分析

为精准确定灌注桩的沉降,将桩周土体参数看作随机变量,并采用响应面法对桩基可靠度进行研究。由于,与桩沉降相关的多个土体参数之间高阶项可能存在高度相关性,基于高阶正交原理提出了新型非相关响应面法,以克服传统响应面法不考虑高阶参数高阶相关性的难题。结合实际工程计算发现,提出的新型响应面法比传统响应面法得到的值更为保守。可见,如果不考虑参数的高阶相关性,可能导致高估的计算结果。     

Improved Estimation of Maximal Reliability for Unidimensional Multicomponent Measuring Instruments in Repeated Measure Studies

In repeated measure studies with unidimensional scales, measurement invariance, and specificity stability over time, the specificity variance in each instrument component can be identified. This article describes for that setting an improved point and interval estimation procedure for the maximal reliability coefficient associated with a given set of homogeneous measures. The method is developed within the framework of latent variable modeling and can also be readily used in longitudinal studies for improved point and interval estimation of individual measure reliability and scale reliability at each assessment occasion. The procedure is based on empirically testable conditions and is illustrated with an example.     

边坡稳定随机场模型效应研究

土体性质表现出其具有固有的应变特性,土体每一点的参数都会发生变化,故在边坡稳定的可靠度分析中不能被忽略。在边坡稳定分析中,常用的模拟土体随机场的模型有折减法、中点法和局部平均离散法。针对一个典型边坡,应用了三个随机场模型导出该边坡的稳定分析结果,对不同随机场模型方法得到的可靠度分析结果进行了互相对比。结果表明边坡的可靠度结果受到土体特性空间变异性的影响,并且这个影响取决于相关距离的相对尺寸和临界滑裂面长度的影响。     

Scale Reliability Evaluation Under Multiple Assumption Violations

A latent variable modeling approach to evaluate scale reliability under realistic conditions in empirical behavioral and social research is discussed. The method provides point and interval estimation of reliability of multicomponent measuring instruments when several assumptions are violated. These assumptions include missing data, correlated errors, nonnormality, lack of unidimensionality, and data not missing at random. The procedure can be readily used to aid scale construction and development efforts in applied settings, and is illustrated using data from an educational study.     

Implementation of autofocus in alignment system for layered imprint fabrication

Autofocus method based on the analysis of image content information is investigated to reduce the alignment error resulting from mark positioning uncertainty due to defocus in microstructure layered fabrication process based on multilevel imprint lithography, The applicability of several autofocus functions to the alignment mark images is evaluated concerning their uniformity, sharpness near peak, reliability and measure computation efficiency and the most suitable one based on power spectrum in frequency domain (PSFD) is adopted. To solve the problem of too much computation amount needed in PSFD algorithm, the strategy of interested region detection and effective image reconstruction is proposed and the algorithm efficiency is improved. The test results show that the computation time is reduced from 0.316 s to 0.023 s under the same conditions while the other merits of the function are preserved, which indicates that the modified algorithm can meet the mark image autofocusing require-ments in response time, accuracy and robustness. The alignment error due to defocus which is about 0.5 μm indi-cated by experimental results can be reduced or eliminated by the autofocusing implementation.     

Resistance partial factor and reliability of cast ball-and-socket support joint

Considering the uncertainty of material performance, geometric characteristic and analysis method, the analysis of statistical parameters of the resistance of cast ball-and-socket support joints and the reliability analysis are carried out by JC method (improved first-order second-moment method) based on the relevant experimental data. Results show that the resistance partial factor of the joint increases with the increase of the reliability index. The resistance partial factors are suggested corresponding to the reliability index under different load combinations. Moreover, the suggested resistance partial factor is adopted in reliability design, and it is found that the reliability index of the joint is larger than the target reliability index. The optimal load combination is the one in which live load plays an important control role. Finally, based on the suggested resistance partial factors, the reliability analysis of cast ball-and-socket support joints of a project is conducted.     

Evaluation of Reliability Coefficients for Two-Level Models via Latent Variable Analysis

A latent variable analysis procedure for evaluation of reliability coefficients for 2-level models is outlined. The method provides point and interval estimates of group means' reliability, overall reliability of means, and conditional reliability. In addition, the approach can be used to test simple hypotheses about these parameters. The procedure is applicable with unconditional models as well as with conditional models including higher level explanatory variables. The proposed method is illustrated with an empirical example.     

Nonparametric estimation of employee stock options

1 Introduction a Employee stock options (ESOs) are the most important compensation vehicle used by companies to retain and motivate their employees. The increased popularity can be attributed to the perceived alignment of employees’ interests with those …     

Dynamic modeling and nonlinear control strategy for an underactuated quad rotor rotorcraft

In this paper, a nonlinear dynamic MIMO model of a 6-DOF underactuated quad rotor rotorcraft is derived based on Newton-Euler formalism. The derivation comprises determining equations of motion of the quad rotor in three dimensions and seeking to approximate the actuation forces through modeling of the aerodynamic coefficients and electric motor dynamics. The derived model is dynamically unstable, so a sequential nonlinear control strategy is implemented for the quad rotor. The control strategy includes exact feedback linearization technique, using the geometric methods of nonlinear control. The performance of the nonlinear control algorithm is evaluated using simulation and the results show the effectiveness of the proposed control strategy for the quad rotor rotorcraft near quasi-stationary flight.     

Monte Carlo Confidence Intervals for Complex Functions of Indirect Effects

One challenge in mediation analysis is to generate a confidence interval (CI) with high coverage and power that maintains a nominal significance level for any well-defined function of indirect and direct effects in the general context of structural equation modeling (SEM). This study discusses a proposed Monte Carlo extension that finds the CIs for any well-defined function of the coefficients of SEM such as the product of k coefficients and the ratio of the contrasts of indirect effects, using the Monte Carlo method. Finally, we conduct a small-scale simulation study to compare CIs produced by the Monte Carlo, nonparametric bootstrap, and asymptotic-delta methods. Based on our simulation study, we recommend researchers use the Monte Carlo method to test a complex function of indirect effects.     

Model Selection in Structural Equation Models With Continuous and Polytomous Data

Recently, analysis of structural equation models with polytomous and continuous variables has received a lot of attention. However, contributions to the selection of good models are limited. The main objective of this article is to investigate the maximum likelihood estimation of unknown parameters in a general LISREL-type model with mixed polytomous and continuous data and propose a model selection procedure for obtaining good models for the underlying substantive theory. The maximum likelihood estimate is obtained by a Monte Carlo Expectation Maximization algorithm, in which the E step is evaluated via the Gibbs sampler and the M step is completed via the method of conditional maximization. The convergence of the Monte Carlo Expectation Maximization algorithm is monitored by the bridge sampling. A model selection procedure based on Bayes factor and Occam's window search strategy is proposed. The effectiveness of the procedure in accounting for the model uncertainty and in picking good models is discussed. The proposed methodology is illustrated with a real example.     

Alternative 3D Modeling Approaches Based on Complex Multi-Source Geological Data Interpretation简

Due to the complex nature of multi-source geological data, it is difficult to rebuild every geological struc-ture through a single 3D modeling method. The multi-source data interpretation method put forward in this analysis is based on a database-driven pattern and focuses on the discrete and irregular features of geological data. The geological data from a variety of sources covering a range of accuracy, resolution, quantity and quality are classified and inte-grated according to their reliability and consistency for 3D modeling. The new interpolation-approximation fitting construction algorithm of geological surfaces with the non-uniform rational B-spline （NURBS） technique is then pre-sented. The NURBS technique can retain the balance among the requirements for accuracy, surface continuity and data storage of geological structures. Finally, four alternative 3D modeling approaches are demonstrated with reference to some examples, which are selected according to the data quantity and accuracy specification. The proposed approaches offer flexible modeling patterns for different practical engineering demands.     

Monte Carlo法在含体积缺陷压力管道可靠性分析中的应用

工业生产装置中,压力管道是重要的组成部分.通常压力管道中存在着局部减薄,而且局部减薄尺寸等参数具有物理不确定性和统计不确定性,所以应该用可靠性来定量衡量其安全状况.依据GB/T 19624-2004计算模型进行蒙特卡罗模拟,计算局部减薄管道的可靠性.该计算方法使用方便,结果可靠.     

Interval Estimation of Optimal Scores from Multiple-Component Measuring Instruments via SEM

A structural equation modeling based method is outlined that accomplishes interval estimation of individual optimal scores resulting from multiple-component measuring instruments evaluating single underlying latent dimensions. The procedure capitalizes on the linear combination of a prespecified set of measures that is associated with maximal reliability and validity. The approach is useful when one is interested in evaluating plausible ranges for subject scores on the composite exhibiting highest measurement consistency and strongest linear relation with a given criterion. The method is illustrated with a numerical example.     

Design and implementation of a position sensorless control method for brushless DC motors

Because brushless direct current (BLDC) motors have the advantages of a compact size, high power density, high efficiency, and long operating life time, they are widely used in many industrial products and electric traction systems. It is known that the BLDC motors have no brushes for commutation. They are commutated with electronically commutation. So, the rotor position information of the BLDC motors must be known to understand which winding will be energized according to the energizing sequence. In most of the existing BLDC motor drivers, rotor position information is detected by Hall effect sensors. This kind of mechanical position sensors will bring additional connections and costs, reliability decrease and noise increase. In order to improve the control performance and extend the range of speed regulation for BLDC motors, a position sensorless control method is proposed in this paper. In the proposed control method, rotor position information of the BLDC motors is detected from the back electromagnetic forces (back-EMFs) which are estimated by an unknown-input observer with line to line currents and line to line voltages. For the purpose of verifying the effectiveness of the proposed control method, a model is built and simulated on the Matlab/Simulink platform. The simulation results show that the speed regulation performance of BLDC motors is improved compared with using Hall effect sensors. At the same time, the reliability of the BLDC motors is improved and the costs of them are reduced because the position sensor is eliminated.     

Evaluation of Maximal Reliability for Unidimensional Measuring Instruments With Correlated Errors

A latent variable modeling method for studying maximal reliability of unidimensional multicomponent measuring instruments with correlated errors is outlined. In the presence of correlation between 2 residual terms, the procedure allows one to point and interval estimate the reliability of the linear combination of the scale components that possesses the highest possible reliability coefficient. The approach is readily applicable with popular latent variable modeling software and also provides an alternative scoring rule to the widely used overall sum score for homogeneous psychometric scales. The discussed method is illustrated with a numerical example.     

一类随机服务系统的非参数统计分析与预测

数据统计分析是解决随机服务系统的基础,在实际应用中极易忽视．首先,基于非参数统计分析理论,给出了分布函数的估计及离散型和连续性两类总体非参数假设检验的数学模型．然后,对某医院眼科排队模型的历史数据进行了详细的统计分析,得到了该随机服务系统的输入过程为Possion分布、服务时间为一般分布的M/G／C／∞／∞排队系统,并依据经验分布函数,给出了非急诊病人等待时间的预测区间．