共查询到20条相似文献，搜索用时 15 毫秒
1.
Daniel F. McCaffrey Katherine E. Castellano J. R. Lockwood 《Educational Measurement》2015,34(1):15-21
Student growth percentiles (SGPs) express students' current observed scores as percentile ranks in the distribution of scores among students with the same prior‐year scores. A common concern about SGPs at the student level, and mean or median SGPs (MGPs) at the aggregate level, is potential bias due to test measurement error (ME). Shang, vanIwaarden, and Betebenner (SVB; this issue) develop a simulation‐extrapolation (SIMEX) approach to adjust SGPs for test ME. In this paper, we use a tractable example in which different SGP estimators, including SVB's SIMEX estimator, can be computed analytically to explain why ME is detrimental to both student‐level and aggregate‐level SGP estimation. A comparison of the alternative SGP estimators to the standard approach demonstrates the common bias‐variance tradeoff problem: estimators that decrease the bias relative to the standard SGP estimator increase variance, and vice versa. Even the most accurate estimator for individual student SGP has large errors of roughly 19 percentile points on average for realistic settings. Those estimators that reduce bias may suffice at the aggregate level but no single estimator is optimal for meeting the dual goals of student‐ and aggregate level inferences. 相似文献
2.
针对车牌字符在车牌图象退化时识别率较低的问题,提出一种基于神经网络集成的车牌字符识别方法。基于小生境遗传算法在提高进化的局部搜索方面的良好性能来动态构建个体网络差异性大的神经网络集成,进而提高整个集成系统的泛化能力。将该方法应用于车牌字符的识别,实验结果表明,该方法能有效地生成差异度较大的个体网络,得到的神经网络集成能有效提高车牌字符的识别率。 相似文献
3.
1 Introduction Identification of an unknown systemfrom availabledata is i mportant in many fields . There are severalmodels representing systems that are dominated bynonlinear characteristics . NARMAX model provides aunified and si mple representation for a wide class ofdiscrete-ti me nonlinear stochastic systems , proposedby Leontaritis ,et al.[1]System identification usingNARMAX model consists of two stages : model struc-ture determination and parameter esti mation proce-dure . The ide… 相似文献
4.
Calculation method of ship collision force on bridge using artificial neural network 总被引：1，自引：0，他引：1
Ship collision on bridge is a dynamic process featured by high nonlinearity and instantaneity. Calculating ship-bridge collision force typically involves either the use of design-specification-stipulated equivalent static load, or the use of finite element method （FEM） which is more time-consuming and requires supercomputing resources. In this paper, we proposed an alternative approach that combines FEM with artificial neural network （ANN）. The radial basis function neural network （RBFNN） employed for calculating the impact force in consideration of ship-bridge collision mechanics. With ship velocity and mass as the input vectors and ship collision force as the output vector, the neural networks for different network parameters are trained by the learning samples obtained from finite element simulation results. The error analyses of the learning and testing samples show that the proposed RBFNN is accurate enough to calculate ship-bridge collision force. The input-output relationship obtained by the RBFNN is essentially consistent with the typical empirical formulae. Finally, a special toolbox is developed for calculation effi- ciency in application using MATLAB software. 相似文献
5.
Seang-Hwane Joo John M. Ferron Mariola Moeyaert S. Natasha Beretvas Wim Van den Noortgate 《Journal of Experimental Education》2019,87(1):55-74
Multilevel modeling has been utilized for combining single-case experimental design (SCED) data assuming simple level-1 error structures. The purpose of this study is to compare various multilevel analysis approaches for handling potential complexity in the level-1 error structure within SCED data, including approaches assuming simple and complex error structures (heterogeneous, autocorrelation, and both) and those using fit indices to select between alternative error structures. A Monte Carlo study was conducted to empirically validate the suggested multilevel modeling approaches. Results indicate that each approach leads to fixed effect estimates with little to no bias and that inferences for fixed effects were frequently accurate, particularly when a simple homogeneous level-1 error structure or a first-order autoregressive structure was assumed and the inferences were based on the Kenward-Roger method. Practical implications and recommendations are discussed. 相似文献
6.
The present study examines bias in parameter estimates and standard error in cross-classified random effect modeling (CCREM) caused by omitting the random interaction effects of the cross-classified factors, focusing on the effect of a sample size within cells and ratio of a small cell. A Monte Carlo simulation study was conducted to compare the correctly specified and the misspecified CCREM. While there was negligible bias in fixed effects, substantial biases were found in the random effects of the misspecified model depending on the number of samples within a cell and the proportion of small cells. However, in the case of the correctly specified model, no bias occurred. The present study suggests considering the random interaction effects when conducting CCREM to avoid overestimation of variance components and to calculate an accurate value of estimation. The implications of this study are to illuminate the conditions of cross-classification ratio and to provide a meaningful reference for applied researchers using CCREM. 相似文献
7.
8.
《Structural equation modeling》2013,20(3):431-441
The conventional noncentrality parameter estimator of covariance structure models, which is currently implemented in widely circulated structural modeling programs (e.g., LISREL, EQS, AMOS, RAMONA), is shown to possess asymptotically potentially large bias, variance, and mean squared error (MSE). A formal expression for its large-sample bias is presented, and its large-sample variance and MSE are quantified. Based on these results, it is suggested that future research needs to develop means of possibly unbiased estimation of the noncentrality parameter, with smaller variance and MSE. 相似文献
9.
This study demonstrated the equivalence between the Rasch testlet model and the three‐level one‐parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter estimation in WINBUGS. The estimation accuracy from the MCMC method was compared with those from the marginalized maximum likelihood estimation (MMLE) with the expectation‐maximization algorithm in ConQuest and the sixth‐order Laplace approximation estimation in HLM6. The results indicated that the estimation methods had significant effects on the bias of the testlet variance and ability variance estimation, the random error in the ability parameter estimation, and the bias in the item difficulty parameter estimation. The Laplace method best recovered the testlet variance while the MMLE best recovered the ability variance. The Laplace method resulted in the smallest random error in the ability parameter estimation while the MCMC method produced the smallest bias in item parameter estimates. Analyses of three real tests generally supported the findings from the simulation and indicated that the estimates for item difficulty and ability parameters were highly correlated across estimation methods. 相似文献
10.
Following Cronbach (1970) and others, it is useful to decompose test score variation into common factor, time‐specific, item‐specific, and residual components. In the traditional approach to factor analysis, only two sources of variance can be estimated: common factor variance and a uniqueness term that confounds specific sources of variation and residual error. When the same items are measured on different occasions, however, it is possible to separate specific variance and residual error. Two approaches, the first‐order approach described by Raffalovich and Bohrnstedt (1987) and a second‐order approach based on Jöreskog and Sörbom (1989; Jöreskog, 1974) are considered initially. The two approaches, although based on different rationales, both suffer a similar weakness in that two of the four sources of variance are confounded. In the Raffalovich and Bohrnstedt approach, time‐specific variance is confounded with common factor variance that generalizes across items and time. In the second‐order approach based on Jöreskog and Sörbom, time‐specific variance is confounded with residual error. Here we demonstrate that by combining features from both approaches we can eliminate these weaknesses and estimate all four of Cronbach's sources of variance, and that this combined approach is easily generalized to a wide variety of applications. 相似文献
11.
Peer relations across 2 contexts (in school and after school) were examined for 577 participants, approximately 12 years old, from 3 middle schools in Milan, Italy. The primary research questions were: Do peer networks from different contexts uniquely contribute to explaining variance in individual behavior? Do measures of peer preference and peer network inclusion across contexts uniquely contribute to explaining individual depressive symptoms? Structural equation models showed that both the in-school and the after-school peer networks uniquely contributed to explaining variance in 2 types of individual problem behavior (in-school problem behavior, after-school delinquency), and that similarity with the 2 peer networks varied according to behaviors specific to each context and across gender. Finally, both in-school and after-school peer network inclusion contributed to explaining variance in depressive symptoms, after controlling for classroom peer preference. 相似文献
12.
A framework for accelerating modern long-running astrophysical simulations is presented, which is based on a hierarchical architecture where computational steering in the high-resolution run is performed under the guide of knowledge obtained in the gradually refined ensemble analyses. Several visualization schemes for facilitating ensemble management, error analysis, parameter grouping and tuning are also integrated owing to the pluggable modular design. The proposed approach is prototyped based on the Flash code, and it can be extended by introducing userdefined visualization for specific requirements. Two real-world simulations, i.e., stellar wind and supernova remnant, are carried out to verify the proposed approach. 相似文献
13.
A new approach to the design of the optical fiber direction coupler by using neural network is proposed. To train the artificial neural network, the coupling length is defined as the input sample, and the coupling ratio is defined as the output sample. Compared with the numerical value calculation of the theoretical formula, the error of the neural network model output is 1% less. Then, through the model, to design a broadband or a single wavelength optical fiber direction coupler becomes easy. The method is proved to be reliable, accurate and time-saving. So it is promising in the field of both investigation and application. 相似文献
14.
Brian E. Clauser Michael Kane Jerome C. Clauser 《Journal of Educational Measurement》2020,57(2):216-229
An Angoff standard setting study generally yields judgments on a number of items by a number of judges (who may or may not be nested in panels). Variability associated with judges (and possibly panels) contributes error to the resulting cut score. The variability associated with items plays a more complicated role. To the extent that the mean item judgments directly reflect empirical item difficulties, the variability in Angoff judgments over items would not add error to the cut score, but to the extent that the mean item judgments do not correspond to the empirical item difficulties, variability in mean judgments over items would add error to the cut score. In this article, we present two generalizability-theory–based analyses of the proportion of the item variance that contributes to error in the cut score. For one approach, variance components are estimated on the probability (or proportion-correct) scale of the Angoff judgments, and for the other, the judgments are transferred to the theta scale of an item response theory model before estimating the variance components. The two analyses yield somewhat different results but both indicate that it is not appropriate to simply ignore the item variance component in estimating the error variance. 相似文献
15.
Gautam Puhan 《Journal of Educational Measurement》2010,47(1):54-75
In this study I compared results of chained linear, Tucker, and Levine-observed score equatings under conditions where the new and old forms samples were similar in ability and also when they were different in ability. The length of the anchor test was also varied to examine its effect on the three different equating methods. The three equating methods were compared to a criterion equating to obtain estimates of random equating error, bias, and root mean squared error (RMSE). Results showed that, for most studied conditions, chained linear equating produced fairly good equating results in terms of low bias and RMSE. Levine equating also produced low bias and RMSE in some conditions. Although the Tucker method always produced the lowest random equating error, it produced a larger bias and RMSE than either of the other equating methods. As noted in the literature, these results also suggest that either chained linear or Levine equating be used when new and old form samples differ on ability and/or when the anchor-to-total correlation is not very high. Finally, by testing the missing data assumptions of the three equating methods, this study also shows empirically why an equating method is more or less accurate under certain conditions . 相似文献
16.
王亚娟 《咸阳师范学院学报》2012,27(2):14-16
无线多跳网络因为节点故障的存在,使得网络拓扑退化问题成为了网络生存过程中的关键问题,如何确定网络退化过程中的临界过程转变时间也成为研究网络化的关键。将网络的拓扑退化形式化为一个几何随机图,通过引入渗流理论,定量的描述了临界过程转变中的最后连接时间和首次分割时间,并说明这个网络测量指标的重要性。 相似文献
17.
Zijun Ke 《Structural equation modeling》2013,20(3):382-400
This study examined and compared various statistical methods for detecting individual differences in change. Considering 3 issues including test forms (specific vs. generalized), estimation procedures (constrained vs. unconstrained), and nonnormality, we evaluated 4 variance tests including the specific Wald variance test, the generalized Wald variance test, the specific likelihood ratio (LR) variance test, and the generalized LR variance test under both constrained and unconstrained estimation for both normal and nonnormal data. For the constrained estimation procedure, both the mixture distribution approach and the alpha correction approach were evaluated for their performance in dealing with the boundary problem. To deal with the nonnormality issue, we used the sandwich standard error (SE) estimator for the Wald tests and the Satorra–Bentler scaling correction for the LR tests. Simulation results revealed that testing a variance parameter and the associated covariances (generalized) had higher power than testing the variance solely (specific), unless the true covariances were zero. In addition, the variance tests under constrained estimation outperformed those under unconstrained estimation in terms of higher empirical power and better control of Type I error rates. Among all the studied tests, for both normal and nonnormal data, the robust generalized LR and Wald variance tests with the constrained estimation procedure were generally more powerful and had better Type I error rates for testing variance components than the other tests. Results from the comparisons between specific and generalized variance tests and between constrained and unconstrained estimation were discussed. 相似文献
18.
A Monte Carlo approach was used to examine bias in the estimation of indirect effects and their associated standard errors. In the simulation design, (a) sample size, (b) the level of nonnormality characterizing the data, (c) the population values of the model parameters, and (d) the type of estimator were systematically varied. Estimates of model parameters were generally unaffected by either nonnormality or small sample size. Under severely nonnormal conditions, normal theory maximum likelihood estimates of the standard error of the mediated effect exhibited less bias (approximately 10% to 20% too small) compared to the standard errors of the structural regression coefficients (20% to 45% too small). Asymptotically distribution free standard errors of both the mediated effect and the structural parameters were substantially affected by sample size, but not nonnormality. Robust standard errors consistently yielded the most accurate estimates of sampling variability. 相似文献
19.
SUN Hong-yan XIE Zhi-jiang OUYANG Qi 《重庆大学学报(英文版)》2006,5(2):94-97
1 Background1 The fault diagnosis to equipment is to obtain fault patterns from characteristic parameters, and in fact it is the problem of fault characteristic’s classification. However the mapping of characteristic parameters to fault patterns is serio… 相似文献
20.
Christian Geiser Michael Eid Stephen G. West Tanja Lischetzke Fridtjof W. Nussbeck 《Structural equation modeling》2013,20(3):409-436
It is well known that measurement error in observable variables induces bias in estimates in standard regression analysis and that structural equation models are a typical solution to this problem. Often, multiple indicator equations are subsumed as part of the structural equation model, allowing for consistent estimation of the relevant regression parameters. In many instances, however, embedding the measurement model into structural equation models is not possible because the model would not be identified. To correct for measurement error one has no other recourse than to provide the exact values of the variances of the measurement error terms of the model, although in practice such variances cannot be ascertained exactly, but only estimated from an independent study. The usual approach so far has been to treat the estimated values of error variances as if they were known exact population values in the subsequent structural equation modeling (SEM) analysis. In this article we show that fixing measurement error variance estimates as if they were true values can make the reported standard errors of the structural parameters of the model smaller than they should be. Inferences about the parameters of interest will be incorrect if the estimated nature of the variances is not taken into account. For general SEM, we derive an explicit expression that provides the terms to be added to the standard errors provided by the standard SEM software that treats the estimated variances as exact population values. Interestingly, we find there is a differential impact of the corrections to be added to the standard errors depending on which parameter of the model is estimated. The theoretical results are illustrated with simulations and also with empirical data on a typical SEM model. 相似文献