British Journal of Mathematical & Statistical Psychology最新文献_第7页

Correction to ‘a note on computing Louis' observed information matrix identity for IRT and cognitive diagnostic models’ 更正“关于计算Louis的注释”，“IRT和认知诊断模型的观测信息矩阵恒等式”。

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-10-25 DOI: 10.1111/bmsp.12325

引用次数: 0

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-10-16 DOI: 10.1111/bmsp.12324

David Jendryczko, Fridtjof W. Nussbeck

{"title":"A correlated traits correlated (methods – 1) multitrait-multimethod model for augmented round-robin data","authors":"David Jendryczko, Fridtjof W. Nussbeck","doi":"10.1111/bmsp.12324","DOIUrl":"10.1111/bmsp.12324","url":null,"abstract":"We didactically derive a correlated traits correlated (methods – 1) [CTC(M – 1)] multitrait-multimethod (MTMM) model for dyadic round-robin data augmented by self-reports. The model is an extension of the CTC(M – 1) model for cross-classified data and can handle dependencies between raters and targets by including reciprocity covariance parameters that are inherent in augmented round-robin designs. It can be specified as a traditional structural equation model. We present the variance decomposition as well as consistency and reliability coefficients. Moreover, we explain how to evaluate fit of a CTC(M – 1) model for augmented round-robin data. In a simulation study, we explore the properties of the full information maximum likelihood estimation of the model. Model (mis)fit can be quite accurately detected with the test of not close fit and dynamic root mean square errors of approximation. Even with few small round-robin groups, relative parameter estimation bias and coverage rates are satisfactory, but several larger round-robin groups are needed to minimize relative parameter estimation inaccuracy. Further, neglecting the reciprocity covariance-structure of the augmented round-robin data does not severely bias the remaining parameter estimates. All analyses (including data, R scripts, and results) and the simulation study are provided in the Supporting Information. Implications and limitations are discussed.","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"77 1","pages":"1-30"},"PeriodicalIF":2.6,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bmsp.12324","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41241136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Gibbs-INLA algorithm for multidimensional graded response model analysis 用于多维分级响应模型分析的Gibbs INLA算法。

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-09-29 DOI: 10.1111/bmsp.12321

Xiaofan Lin, Siliang Zhang, Yincai Tang, Xuan Li

引用次数: 0

A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data 一种处理评估数据中项目和受试者异质性的贝叶斯非参数方法。

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-09-20 DOI: 10.1111/bmsp.12322

Tianyu Pan, Weining Shen, Clintin P. Davis-Stober, Guanyu Hu

{"title":"A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data","authors":"Tianyu Pan, Weining Shen, Clintin P. Davis-Stober, Guanyu Hu","doi":"10.1111/bmsp.12322","DOIUrl":"10.1111/bmsp.12322","url":null,"abstract":"We propose a novel nonparametric Bayesian item response theory model that estimates clusters at the question level, while simultaneously allowing for heterogeneity at the examinee level under each question cluster, characterized by a mixture of binomial distributions. The main contribution of this work is threefold. First, we present our new model and demonstrate that it is identifiable under a set of conditions. Second, we show that our model can correctly identify question-level clusters asymptotically, and the parameters of interest that measure the proficiency of examinees in solving certain questions can be estimated at a <math>\u0000 <semantics>\u0000 <mrow>\u0000 <msqrt>\u0000 <mrow>\u0000 <mi>n</mi>\u0000 </mrow>\u0000 </msqrt>\u0000 </mrow>\u0000 </semantics></math> rate (up to a log term). Third, we present a tractable sampling algorithm to obtain valid posterior samples from our proposed model. Compared to the existing methods, our model manages to reveal the multi-dimensionality of the examinees' proficiency level in handling different types of questions parsimoniously by imposing a nested clustering structure. The proposed model is evaluated via a series of simulations as well as apply it to an English proficiency assessment data set. This data analysis example nicely illustrates how our model can be used by test makers to distinguish different types of students and aid in the design of future tests.","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"77 1","pages":"196-211"},"PeriodicalIF":2.6,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41174590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Replies to comments on "Which method delivers greater signal-to-noise ratio: Structural equation modelling or regression analysis with weighted composites?" by Yuan and Fang (2023) 袁和方(2023)对“哪种方法能提供更大的信噪比:结构方程建模还是加权复合材料回归分析?”的评论回复

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-09-15 DOI: 10.1111/bmsp.12323

Ke-Hai Yuan, Yongfei Fang

引用次数: 0

Exploring examinees' responses to constructed response items with a supervised topic model 用监督话题模型探索考生对构建的回答项目的反应。

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-09-13 DOI: 10.1111/bmsp.12319

Seohyun Kim, Zhenqiu Lu, Allan S. Cohen

{"title":"Exploring examinees' responses to constructed response items with a supervised topic model","authors":"Seohyun Kim, Zhenqiu Lu, Allan S. Cohen","doi":"10.1111/bmsp.12319","DOIUrl":"10.1111/bmsp.12319","url":null,"abstract":"Textual data are increasingly common in test data as many assessments include constructed response (CR) items as indicators of participants' understanding. The development of techniques based on natural language processing has made it possible for researchers to rapidly analyse large sets of textual data. One family of statistical techniques for this purpose are probabilistic topic models. Topic modelling is a technique for detecting the latent topic structure in a collection of documents and has been widely used to analyse texts in a variety of areas. The detected topics can reveal primary themes in the documents, and the relative use of topics can be useful in investigating the variability of the documents. Supervised latent Dirichlet allocation (SLDA) is a popular topic model in that family that jointly models textual data and paired responses such as could occur with participants' textual answers to CR items and their rubric-based scores. SLDA has an assumption of a homogeneous relationship between textual data and paired responses across all documents. This approach, while useful for some purposes, may not be satisfied for situations in which a population has subgroups that have different relationships. In this study, we introduce a new supervised topic model that incorporates finite-mixture modelling into the SLDA. This new model can detect latent groups of participants that have different relationships between their textual responses and associated scores. The model is illustrated with an example from an analysis of a set of textual responses and paired scores from a middle grades assessment of science inquiry knowledge. A simulation study is presented to investigate the performance of the proposed model under practical testing conditions.","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"77 1","pages":"130-150"},"PeriodicalIF":2.6,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bmsp.12319","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10225777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimation of nonlinear mixed-effects continuous-time models using the continuous-discrete extended Kalman filter 用连续离散扩展卡尔曼滤波估计非线性混合效应连续时间模型

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-09-06 DOI: 10.1111/bmsp.12318

Lu Ou, Michael D. Hunter, Zhaohua Lu, Cynthia A. Stifter, Sy-Miin Chow

{"title":"Estimation of nonlinear mixed-effects continuous-time models using the continuous-discrete extended Kalman filter","authors":"Lu Ou, Michael D. Hunter, Zhaohua Lu, Cynthia A. Stifter, Sy-Miin Chow","doi":"10.1111/bmsp.12318","DOIUrl":"10.1111/bmsp.12318","url":null,"abstract":"Many intensive longitudinal measurements are collected at irregularly spaced time intervals, and involve complex, possibly nonlinear and heterogeneous patterns of change. Effective modelling of such change processes requires continuous-time differential equation models that may be nonlinear and include mixed effects in the parameters. One approach of fitting such models is to define random effect variables as additional latent variables in a stochastic differential equation (SDE) model of choice, and use estimation algorithms designed for fitting SDE models, such as the continuous-discrete extended Kalman filter (CDEKF) approach implemented in the dynr R package, to estimate the random effect variables as latent variables. However, this approach's efficacy and identification constraints in handling mixed-effects SDE models have not been investigated. In the current study, we analytically inspect the identification constraints of using the CDEKF approach to fit nonlinear mixed-effects SDE models; extend a published model of emotions to a nonlinear mixed-effects SDE model as an example, and fit it to a set of irregularly spaced ecological momentary assessment data; and evaluate the feasibility of the proposed approach to fit the model through a Monte Carlo simulation study. Results show that the proposed approach produces reasonable parameter and standard error estimates when some identification constraint is met. We address the effects of sample size, process noise variance, and data spacing conditions on estimation results.","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"76 3","pages":"462-490"},"PeriodicalIF":2.6,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10226412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using item scores and response times in person-fit assessment 在个人适应性评估中使用项目得分和反应时间。

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-09-05 DOI: 10.1111/bmsp.12320

Kylie Gorney, Sandip Sinharay, Xiang Liu

引用次数: 0

Evaluating the performance of existing and novel equivalence tests for fit indices in structural equation modelling 评估结构方程建模中现有和新型拟合指数等效检验的性能。

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-07-13 DOI: 10.1111/bmsp.12317

Nataly Beribisky, Robert A. Cribbie

{"title":"Evaluating the performance of existing and novel equivalence tests for fit indices in structural equation modelling","authors":"Nataly Beribisky, Robert A. Cribbie","doi":"10.1111/bmsp.12317","DOIUrl":"10.1111/bmsp.12317","url":null,"abstract":"It has been suggested that equivalence testing (otherwise known as negligible effect testing) should be used to evaluate model fit within structural equation modelling (SEM). In this study, we propose novel variations of equivalence tests based on the popular root mean squared error of approximation and comparative fit index fit indices. Using Monte Carlo simulations, we compare the performance of these novel tests to other existing equivalence testing-based fit indices in SEM, as well as to other methods commonly used to evaluate model fit. Results indicate that equivalence tests in SEM have good Type I error control and display considerable power for detecting well-fitting models in medium to large sample sizes. At small sample sizes, relative to traditional fit indices, equivalence tests limit the chance of supporting a poorly fitting model. We also present an illustrative example to demonstrate how equivalence tests may be incorporated in model fit reporting. Equivalence tests in SEM also have unique interpretational advantages compared to other methods of model fit evaluation. We recommend that equivalence tests be utilized in conjunction with descriptive fit indices to provide more evidence when evaluating model fit.","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"77 1","pages":"103-129"},"PeriodicalIF":2.6,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bmsp.12317","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10134925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

K-Plus anticlustering: An improved k-means criterion for maximizing between-group similarity K-Plus 反聚类法：最大化组间相似性的改进型 k-means 准则。

IF 2.6 3区心理学

British Journal of Mathematical & Statistical Psychology Pub Date : 2023-07-11 DOI: 10.1111/bmsp.12315

Martin Papenberg

{"title":"K-Plus anticlustering: An improved k-means criterion for maximizing between-group similarity","authors":"Martin Papenberg","doi":"10.1111/bmsp.12315","DOIUrl":"10.1111/bmsp.12315","url":null,"abstract":"Anticlustering refers to the process of partitioning elements into disjoint groups with the goal of obtaining high between-group similarity and high within-group heterogeneity. Anticlustering thereby reverses the logic of its better known twin—cluster analysis—and is usually approached by maximizing instead of minimizing a clustering objective function. This paper presents k-plus, an extension of the classical k-means objective of maximizing between-group similarity in anticlustering applications. K-plus represents between-group similarity as discrepancy in distribution moments (means, variance, and higher-order moments), whereas the k-means criterion only reflects group differences with regard to means. While constituting a new criterion for anticlustering, it is shown that k-plus anticlustering can be implemented by optimizing the original k-means criterion after the input data have been augmented with additional variables. A computer simulation and practical examples show that k-plus anticlustering achieves high between-group similarity with regard to multiple objectives. In particular, optimizing between-group similarity with regard to variances usually does not compromise similarity with regard to means; the k-plus extension is therefore generally preferred over classical k-means anticlustering. Examples are given on how k-plus anticlustering can be applied to real norming data using the open source R package anticlust, which is freely available via CRAN.","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"77 1","pages":"80-102"},"PeriodicalIF":2.6,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bmsp.12315","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9764395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0