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1.
A Second-Order Conditionally Linear Mixed Effects Model With Observed and Latent Variable Covariates
Jeffrey R. Harring Nidhi Kohli Rebecca D. Silverman Deborah L. Speece 《Structural equation modeling》2013,20(1):118-136
A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a nonlinear manner are common to all subjects. In this article we describe how a variant of the Michaelis–Menten (M–M) function can be fit within this modeling framework using Mplus 6.0. We demonstrate how observed and latent covariates can be incorporated to help explain individual differences in growth characteristics. Features of the model including an explication of key analytic decision points are illustrated using longitudinal reading data. To aid in making this class of models accessible, annotated Mplus code is provided. 相似文献
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张红霞 《安徽广播电视大学学报》2003,(3):47-51
TEM4听写采用的是较传统的数错扣分法。数错扣分法是负分法，其中存在一些问题。因此我们提出一种实验性的评分方法——部分得分制。实验数据有两组，分别采用TEM4听写评分制和新评分制。数据比较以及部分得分模型(Rasch模型之一)对实验量表效能的分析(如模型与数据拟合值、被试拟合值、信息函数等)说明，实验评分制能较好地测量大多数学生的听写水平。 相似文献
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Eiji Muraki 《Journal of Educational Measurement》1999,36(3):217-232
Bock, Muraki, and Pfeiffenberger (1988) proposed a dichotomous item response theory (IRT) model for the detection of differential item functioning (DIF), and they estimated the IRT parameters and the means and standard deviations of the multiple latent trait distributions. This IRT DIF detection method is extended to the partial credit model (Masters, 1982; Muraki, 1993) and presented as one of the multiple-group IRT models. Uniform and non-uniform DIF items and heterogeneous latent trait distributions were used to generate polytomous responses of multiple groups. The DIF method was applied to this simulated data using a stepwise procedure. The standardized DIF measures for slope and item location parameters successfully detected the non-uniform and uniform DIF items as well as recovered the means and standard deviations of the latent trait distributions.This stepwise DIF analysis based on the multiple-group partial credit model was then applied to the National Assessment of Educational Progress (NAEP) writing trend data. 相似文献
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MplusAutomation is a package for R that facilitates complex latent variable analyses in Mplus involving comparisons among many models and parameters. More specifically, MplusAutomation provides tools to accomplish 3 objectives: to create and manage Mplus syntax for groups of related models; to automate the estimation of many models; and to extract, aggregate, and compare fit statistics, parameter estimates, and ancillary model outputs. We provide an introduction to the package using applied examples including a large-scale simulation study. By reducing the effort required for large-scale studies, a broad goal of MplusAutomation is to support methodological developments in structural equation modeling using Mplus. 相似文献
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作为下位法的《征信业务管理办法》,在落实《个人信息保护法》要求的告知义务上,存在义务主体"信用信息提供者"和义务客体"信用信息"界定过于泛化的问题。它对信用信息采用了"用于识别判断企业和个人信用状况"的限定和"其他相关信息"的兜底,在规范层面导致法律概念限定与开放的自我矛盾。而信用信息范畴的扩张是征信理论体系本身扩张的一个缩影。替代数据的使用、经济征信向公共领域的扩张、信用信息透明与个人信息强保护理念的冲突,在理论层面构成征信体系的自我矛盾。由于《征信业务管理办法》所涵摄的征信属于经济领域,所以落实征信的经济性与政策性的目的可以破解规范矛盾,而理论矛盾则要求重新识别征信体系的场景化应用。 相似文献
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Conventionally, moderated mediation analysis is conducted through adding relevant interaction terms into a mediation model of interest. In this study, we illustrate how to conduct moderated mediation analysis by directly modeling the relation between the indirect effect components including a and b and the moderators, to permit easier specification and interpretation of moderated mediation. With this idea, we introduce a general moderated mediation model that can be used to model many different moderated mediation scenarios including the scenarios described in Preacher, Rucker, and Hayes (2007). Then we discuss how to estimate and test the conditional indirect effects and to test whether a mediation effect is moderated using Bayesian approaches. How to implement the estimation in both BUGS and Mplus is also discussed. Performance of Bayesian methods is evaluated and compared to that of frequentist methods including maximum likelihood (ML) with 1st-order and 2nd-order delta method standard errors and mL with bootstrap (percentile or bias-corrected confidence intervals) via a simulation study. The results show that Bayesian methods with diffuse (vague) priors implemented in both BUGS and Mplus yielded unbiased estimates, higher power than the ML methods with delta method standard errors, and the ML method with bootstrap percentile confidence intervals, and comparable power to the ML method with bootstrap bias-corrected confidence intervals. We also illustrate the application of these methods with the real data example used in Preacher et al. (2007). Advantages and limitations of applying Bayesian methods to moderated mediation analysis are also discussed. 相似文献
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李崇文 《湖南师范大学教育科学学报》2005,4(4):73-75
实行学分制,对促进高等教育教学管理改革,树立和落实“以学生为本”的教育思想,有着积极的作用。多年来,我国的高等学校一直在进行着学分制改革,但由于条件限制,学生的选择受到影响。只有从实际出发,采取适当的措施扩大学生的选择空间,才能探索出适合我国高等教育实际的学分制模式。 相似文献
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Mike W.-L. Cheung 《Structural equation modeling》2013,20(3):429-454
Multivariate meta-analysis has become increasingly popular in the educational, social, and medical sciences. It is because the outcome measures in a meta-analysis can involve more than one effect size. This article proposes 2 mathematically equivalent models to implement multivariate meta-analysis in structural equation modeling (SEM). Specifically, this article shows how multivariate fixed-, random- and mixed-effects meta-analyses can be formulated as structural equation models. metaSEM (a free R package based on OpenMx) and Mplus are used to implement the proposed procedures. A real data set is used to illustrate the procedures. Formulating multivariate meta-analysis as structural equation models provides many new research opportunities for methodological development in both meta-analysis and SEM. Issues related to and extensions on the SEM-based meta-analysis are discussed. 相似文献
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Mixed-dyadic data, collected from distinguishable (nonexchangeable) or indistinguishable (exchangeable) dyads, require statistical analysis techniques that model the variation within dyads and between dyads appropriately. The purpose of this article is to provide a tutorial for performing structural equation modeling analyses of cross-sectional and longitudinal models for mixed independent variable dyadic data, and to clarify questions regarding various dyadic data analysis specifications that have not been addressed elsewhere. Artificially generated data similar to the Newlywed Project and the Swedish Adoption Twin Study on Aging were used to illustrate analysis models for distinguishable and indistinguishable dyads, respectively. Due to their widespread use among applied researchers, the AMOS and Mplus statistical analysis software packages were used to analyze the dyadic data structural equation models illustrated here. These analysis models are presented in sufficient detail to allow researchers to perform these analyses using their preferred statistical analysis software package. 相似文献
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国外学分制模式之比较与我国的教学管理改革 总被引：8，自引：0，他引：8
学分制是为克服学年制的某些弊端而实行的一种较为灵活的教学管理模式。国外的学分制管理模式对我国的教学管理改革有一定的借鉴作用。本文通过分析、比较美国、日本、西欧国家的学分制教学管理模式及其发展趋势,提出了我国发展学分制的设想和建议。 相似文献
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调整了KMV模型中股权市场价值和违约距离的计算,选取中国证券市场30家ST公司和30家非ST公司的数据检验修正后KMV模型的识别能力.结果表明,修正后的KMV模型能够识别上市公司的信用风险,是一种有效的公司债券资信评级方法. 相似文献
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Application of Latent Growth Curve Analysis With Categorical Responses in Social Behavioral Research
Tae Kyoung Lee Kandauda Wickrama Catherine W. O’Neal 《Structural equation modeling》2018,25(2):294-306
Latent growth modeling allows social behavioral researchers to investigate within-person change and between-person differences in within-person change. Typically, conventional latent growth curve models are applied to continuous variables, where the residuals are assumed to be normally distributed, whereas categorical variables (i.e., binary and ordinal variables), which do not hold to normal distribution assumptions, have rarely been used. This article describes the latent growth curve model with categorical variables, and illustrates applications using Mplus software that are applicable to social behavioral research. The illustrations use marital instability data from the Iowa Youth and Family Project. We close with recommendations for the specification and parameterization of growth models that use both logit and probit link functions. 相似文献
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针对个人信用评估，提出了人工神经网络的评估模型。对于训练好的网络模型，用户可在输入客户数据的基础上，调入生成好的规则，正确得到客户的评价结果。 相似文献
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Researchers often have expectations that can be expressed in the form of inequality constraints among the parameters of a structural equation model. It is currently not possible to test these so-called informative hypotheses in structural equation modeling software. We offer a solution to this problem using Mplus. The hypotheses are evaluated using plug-in p values with a calibrated alpha level. The method is introduced and its utility is illustrated by means of an example. 相似文献
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In a recent article, Castro-Schilo, Widaman, and Grimm (2013) compared different approaches for relating multitrait–multimethod (MTMM) data to external variables. Castro-Schilo et al. reported that estimated associations with external variables were in part biased when either the correlated traits–correlated uniqueness (CT-CU) or correlated traits–correlated (methods–1) [CT-C(M–1)] models were fit to data generated from the correlated traits–correlated methods (CT-CM) model, whereas the data-generating CT-CM model accurately reproduced these associations. Castro-Schilo et al. argued that the CT-CM model adequately represents the data-generating mechanism in MTMM studies, whereas the CT-CU and CT-C(M–1) models do not fully represent the MTMM structure. In this comment, we question whether the CT-CM model is more plausible as a data-generating model for MTMM data than the CT-C(M–1) model. We show that the CT-C(M–1) model can be formulated as a reparameterization of a basic MTMM true score model that leads to a meaningful and parsimonious representation of MTMM data. We advocate the use confirmatory factor analysis MTMM models in which latent trait, method, and error variables are explicitly and constructively defined based on psychometric theory. 相似文献
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Most of the software that is available to implement Bayesian approaches uses Markov chain Monte Carlo (MCMC) methods. It is our impression that many researchers are primarily concerned with convergence as assessed by the Potential Scale Reduction (PSR) and that other aspects of MCMC are largely ignored. In this article, we argue that the precision with which the Bayesian estimates are approximated by summary statistics for the MCMC chain is essential to ensure good statistical properties. We discuss the Effective Sample Size (ESS), which indicates how well an estimate is approximated, and present evidence from two simulation studies and an example from organizational research to support our claim that researchers should be concerned not only with convergence but also with precision, particularly when a multilevel model is estimated. In addition, we demonstrate how Mplus can be modified so that users can control the ESS, and we conclude with recommendations. 相似文献
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现有的信用评估模型往往需要在建模前预设模型的基本形态结构,极易因函数形式的误设导致评估结果误差较大,同时现有模型大多面向传统大中型企业、消费信贷用户,对农户这一借款主体缺乏适用性。基于宿迁地区某农村信用社的农户信贷数据库,设计一种面向我国农户贷款信用风险评估模型——Relief-GEP模型。模型首先使用Relief算法,对建模样本集维度进行删减,剔除对预测违约概率影响不大的各项指标,在摈弃部分噪声数据的同时提高后续建模精度;在缺乏最优函数形式的先验信息情况下使用基因表达式编程算法,以“适者生存”的逻辑通过反复演化迭代,动态构筑模型的核心部分。实证研究表明,Relief-GEP模型相比于当前流行的12个信用风险评估模型,拥有更优的拟合精度与更好的泛化能力。 相似文献
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对于银行、P2P等金融机构而言,如何在扩大业务规模的同时,有效控制并合理防范信用风险尤为重要。基于LightGBM算法,根据借款申请人提供的相关个人信息,建立分类预测模型,对借款人是否会逾期、是否该发放贷款进行预测研究。实验结果表明,相较于普通决策树算法,LightGBM预测精度提升了40.8%,且具有较好的鲁棒性,可满足信用评估要求。基于LightGBM的信用评估模型不仅拥有更快的训练速度和更高的训练效率,同时还占用更少的内存,具有支持数据并行处理能力。利用该模型可对用户信用风险进行较为准确的预测,对贷款机构风险管理有重要参考价值。 相似文献