British Journal of Mathematical & Statistical Psychology最新文献

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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":"<p>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 <i>k</i>-plus, an extension of the classical <i>k</i>-means objective of maximizing between-group similarity in anticlustering applications. <i>K</i>-plus represents between-group similarity as discrepancy in distribution moments (means, variance, and higher-order moments), whereas the <i>k</i>-means criterion only reflects group differences with regard to means. While constituting a new criterion for anticlustering, it is shown that <i>k</i>-plus anticlustering can be implemented by optimizing the original <i>k</i>-means criterion after the input data have been augmented with additional variables. A computer simulation and practical examples show that <i>k</i>-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 <i>k</i>-plus extension is therefore generally preferred over classical <i>k</i>-means anticlustering. Examples are given on how <i>k</i>-plus anticlustering can be applied to real norming data using the open source R package anticlust, which is freely available via CRAN.</p>","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
Enhancing measurement validity in diverse populations: Modern approaches to evaluating differential item functioning 提高不同人群的测量效度:评估差异项目功能的现代方法
IF 2.6 3区 心理学
British Journal of Mathematical & Statistical Psychology Pub Date : 2023-07-10 DOI: 10.1111/bmsp.12316
Daniel J. Bauer
{"title":"Enhancing measurement validity in diverse populations: Modern approaches to evaluating differential item functioning","authors":"Daniel J. Bauer","doi":"10.1111/bmsp.12316","DOIUrl":"10.1111/bmsp.12316","url":null,"abstract":"<p>When developing and evaluating psychometric measures, a key concern is to ensure that they accurately capture individual differences on the intended construct across the entire population of interest. Inaccurate assessments of individual differences can occur when responses to some items reflect not only the intended construct but also construct-irrelevant characteristics, like a person's race or sex. Unaccounted for, this <i>item bias</i> can lead to apparent differences on the scores that do not reflect true differences, invalidating comparisons between people with different backgrounds. Accordingly, empirically identifying which items manifest bias through the evaluation of <i>differential item functioning</i> (DIF) has been a longstanding focus of much psychometric research. The majority of this work has focused on evaluating DIF across two (or a few) groups. Modern conceptualizations of identity, however, emphasize its multi-determined and intersectional nature, with some aspects better represented as dimensional than categorical. Fortunately, many model-based approaches to modelling DIF now exist that allow for simultaneous evaluation of multiple background variables, including both continuous and categorical variables, and potential interactions among background variables. This paper provides a comparative, integrative review of these new approaches to modelling DIF and clarifies both the opportunities and challenges associated with their application in psychometric research.</p>","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"76 3","pages":"435-461"},"PeriodicalIF":2.6,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bmsp.12316","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10125818","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
Assessment of generalised Bayesian structural equation models for continuous and binary data 连续和二元数据的广义贝叶斯结构方程模型的评价
IF 2.6 3区 心理学
British Journal of Mathematical & Statistical Psychology Pub Date : 2023-07-04 DOI: 10.1111/bmsp.12314
Konstantinos Vamvourellis, Konstantinos Kalogeropoulos, Irini Moustaki
{"title":"Assessment of generalised Bayesian structural equation models for continuous and binary data","authors":"Konstantinos Vamvourellis,&nbsp;Konstantinos Kalogeropoulos,&nbsp;Irini Moustaki","doi":"10.1111/bmsp.12314","DOIUrl":"10.1111/bmsp.12314","url":null,"abstract":"<p>The paper proposes a novel model assessment paradigm aiming to address shortcoming of posterior predictive <math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>p</mi>\u0000 </mrow>\u0000 </semantics></math>-values, which provide the default metric of fit for Bayesian structural equation modelling (BSEM). The model framework presented in the paper focuses on the approximate zero approach (<i>Psychological Methods</i>, <b>17</b>, 2012, 313), which involves formulating certain parameters (such as factor loadings) to be approximately zero through the use of informative priors, instead of explicitly setting them to zero. The introduced model assessment procedure monitors the out-of-sample predictive performance of the fitted model, and together with a list of guidelines we provide, one can investigate whether the hypothesised model is supported by the data. We incorporate scoring rules and cross-validation to supplement existing model assessment metrics for BSEM. The proposed tools can be applied to models for both continuous and binary data. The modelling of categorical and non-normally distributed continuous data is facilitated with the introduction of an item-individual random effect. We study the performance of the proposed methodology via simulation experiments as well as real data on the ‘Big-5’ personality scale and the Fagerstrom test for nicotine dependence.</p>","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"76 3","pages":"559-584"},"PeriodicalIF":2.6,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bmsp.12314","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9748065","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
Testing indirect effect with a complete or incomplete dichotomous mediator 用完全或不完全二分介质检验间接效应
IF 2.6 3区 心理学
British Journal of Mathematical & Statistical Psychology Pub Date : 2023-06-26 DOI: 10.1111/bmsp.12313
Fan Jia, Wei Wu, Po-Yi Chen
{"title":"Testing indirect effect with a complete or incomplete dichotomous mediator","authors":"Fan Jia,&nbsp;Wei Wu,&nbsp;Po-Yi Chen","doi":"10.1111/bmsp.12313","DOIUrl":"10.1111/bmsp.12313","url":null,"abstract":"<p>Past methodological research on mediation analysis mainly focused on situations where all variables were complete and continuous. When issues of categorical data occur combined with missing data, more methodological considerations are involved. Specifically, appropriate decisions need to be made on estimation methods of the indirect effects and on confidence intervals for testing the indirect effects with accommodations of missing data. We compare strategies that address these issues based on a model with a dichotomous mediator, aiming to provide guidelines for researchers facing such challenges in practice.</p>","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"76 3","pages":"539-558"},"PeriodicalIF":2.6,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10063422","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
Variational Bayes inference for hidden Markov diagnostic classification models 隐马尔可夫诊断分类模型的变异贝叶斯推理。
IF 2.6 3区 心理学
British Journal of Mathematical & Statistical Psychology Pub Date : 2023-05-30 DOI: 10.1111/bmsp.12308
Kazuhiro Yamaguchi, Alfonso J. Martinez
{"title":"Variational Bayes inference for hidden Markov diagnostic classification models","authors":"Kazuhiro Yamaguchi,&nbsp;Alfonso J. Martinez","doi":"10.1111/bmsp.12308","DOIUrl":"10.1111/bmsp.12308","url":null,"abstract":"<p>Diagnostic classification models (DCMs) can be used to track the cognitive learning states of students across multiple time points or over repeated measurements. This study developed an effective variational Bayes (VB) inference method for hidden Markov longitudinal general DCMs. The simulations performed in this study verified the validity of the proposed algorithm for satisfactorily recovering true parameters. Simulation and applied data analyses were conducted to compare the proposed VB method to Markov chain Monte Carlo (MCMC) sampling. The results revealed that the parameter estimates provided by the VB method were consistent with the MCMC method with the additional benefit of a faster estimation time. The comparative simulation also indicated differences between the two methods in terms of posterior standard deviation and coverage of 95% credible intervals. Thus, with limited computational resources and time, the proposed VB method can output estimations comparable to that of MCMC.</p>","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"77 1","pages":"55-79"},"PeriodicalIF":2.6,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9533717","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
A sequential exploratory diagnostic model using a Pólya-gamma data augmentation strategy 使用Pólya-gamma数据增强策略的顺序探索性诊断模型
IF 2.6 3区 心理学
British Journal of Mathematical & Statistical Psychology Pub Date : 2023-05-21 DOI: 10.1111/bmsp.12307
Auburn Jimenez, James Joseph Balamuta, Steven Andrew Culpepper
{"title":"A sequential exploratory diagnostic model using a Pólya-gamma data augmentation strategy","authors":"Auburn Jimenez,&nbsp;James Joseph Balamuta,&nbsp;Steven Andrew Culpepper","doi":"10.1111/bmsp.12307","DOIUrl":"10.1111/bmsp.12307","url":null,"abstract":"<p>Cognitive diagnostic models provide a framework for classifying individuals into latent proficiency classes, also known as attribute profiles. Recent research has examined the implementation of a Pólya-gamma data augmentation strategy binary response model using logistic item response functions within a Bayesian Gibbs sampling procedure. In this paper, we propose a sequential exploratory diagnostic model for ordinal response data using a logit-link parameterization at the category level and extend the Pólya-gamma data augmentation strategy to ordinal response processes. A Gibbs sampling procedure is presented for efficient Markov chain Monte Carlo (MCMC) estimation methods. We provide results from a Monte Carlo study for model performance and present an application of the model.</p>","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"76 3","pages":"513-538"},"PeriodicalIF":2.6,"publicationDate":"2023-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41170914","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
Causality and prediction in structural equation modeling: A commentary by Yutaka Kano on: “Which method delivers greater signal-to-noise ratio: Structural equation modeling or regression analysis with weighted composites?” by Yuan and Fang 结构方程建模中的因果关系和预测:Yutaka Kano对以下问题的评论:“哪种方法提供更大的信噪比:结构方程建模还是加权复合回归分析?”袁、方所著
IF 2.6 3区 心理学
British Journal of Mathematical & Statistical Psychology Pub Date : 2023-05-11 DOI: 10.1111/bmsp.12306
Yutaka Kano
{"title":"Causality and prediction in structural equation modeling: A commentary by Yutaka Kano on: “Which method delivers greater signal-to-noise ratio: Structural equation modeling or regression analysis with weighted composites?” by Yuan and Fang","authors":"Yutaka Kano","doi":"10.1111/bmsp.12306","DOIUrl":"10.1111/bmsp.12306","url":null,"abstract":"","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"76 3","pages":"679-681"},"PeriodicalIF":2.6,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9439924","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
A sequential Bayesian changepoint detection procedure for aberrant behaviours in computerized testing 计算机化测试中异常行为的连续贝叶斯变化点检测程序。
IF 2.6 3区 心理学
British Journal of Mathematical & Statistical Psychology Pub Date : 2023-05-10 DOI: 10.1111/bmsp.12305
Jing Lu, Chun Wang, Jiwei Zhang, Xue Wang
{"title":"A sequential Bayesian changepoint detection procedure for aberrant behaviours in computerized testing","authors":"Jing Lu,&nbsp;Chun Wang,&nbsp;Jiwei Zhang,&nbsp;Xue Wang","doi":"10.1111/bmsp.12305","DOIUrl":"10.1111/bmsp.12305","url":null,"abstract":"<p>Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is essential to properly differentiate examinees' aberrant behaviours from solution behaviour to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to monitor the locations of changepoints for response times in real time and, subsequently, further identify types of aberrant behaviours in conjunction with response patterns. Two simulation studies were conducted to investigate the efficiency and accuracy of the proposed detection procedure in terms of identifying one or multiple changepoints at different locations. In addition to manipulating the number and locations of changepoints, two types of aberrant behaviours were also considered: rapid guessing behaviour and cheating behaviour. Simulation results indicate that ability estimates could be improved after removing responses from aberrant behaviours identified by our approach. Two empirical examples were analysed to illustrate the application of the proposed sequential Bayesian changepoint detection procedure.</p>","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"77 1","pages":"31-54"},"PeriodicalIF":2.6,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9813812","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: 1
Premature conclusions about the signal-to-noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023) 关于结构方程建模研究中信噪比的过早结论——评袁和方(2023)
IF 2.6 3区 心理学
British Journal of Mathematical & Statistical Psychology Pub Date : 2023-04-18 DOI: 10.1111/bmsp.12304
Florian Schuberth, Tamara Schamberger, Mikko Rönkkö, Yide Liu, Jörg Henseler
{"title":"Premature conclusions about the signal-to-noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023)","authors":"Florian Schuberth,&nbsp;Tamara Schamberger,&nbsp;Mikko Rönkkö,&nbsp;Yide Liu,&nbsp;Jörg Henseler","doi":"10.1111/bmsp.12304","DOIUrl":"10.1111/bmsp.12304","url":null,"abstract":"<p>In a recent article published in this journal, Yuan and Fang (<i>British Journal of Mathematical and Statistical Psychology</i>, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller standard errors, and thus corresponds to greater values of the [SNR].” In our commentary, we show that Yuan and Fang have made several incorrect assumptions and claims. Consequently, we recommend that empirical researchers not base their methodological choice regarding CB-SEM and regression analysis with composites on the findings of Yuan and Fang as these findings are premature and require further research.</p>","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"76 3","pages":"682-694"},"PeriodicalIF":2.6,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bmsp.12304","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9319019","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: 1
A dual process item response theory model for polytomous multidimensional forced-choice items 多方位多维强迫选择项目的双过程项目反应理论模型
IF 2.6 3区 心理学
British Journal of Mathematical & Statistical Psychology Pub Date : 2023-03-26 DOI: 10.1111/bmsp.12303
Xuelan Qiu, Jimmy de la Torre
{"title":"A dual process item response theory model for polytomous multidimensional forced-choice items","authors":"Xuelan Qiu,&nbsp;Jimmy de la Torre","doi":"10.1111/bmsp.12303","DOIUrl":"10.1111/bmsp.12303","url":null,"abstract":"<p>The use of multidimensional forced-choice (MFC) items to assess non-cognitive traits such as personality, interests and values in psychological tests has a long history, because MFC items show strengths in preventing response bias. Recently, there has been a surge of interest in developing item response theory (IRT) models for MFC items. However, nearly all of the existing IRT models have been developed for MFC items with binary scores. Real tests use MFC items with more than two categories; such items are more informative than their binary counterparts. This study developed a new IRT model for polytomous MFC items based on the cognitive model of choice, which describes the cognitive processes underlying humans' preferential choice behaviours. The new model is unique in its ability to account for the ipsative nature of polytomous MFC items, to assess individual psychological differentiation in interests, values and emotions, and to compare the differentiation levels of latent traits between individuals. Simulation studies were conducted to examine the parameter recovery of the new model with existing computer programs. The results showed that both statement parameters and person parameters were well recovered when the sample size was sufficient. The more complete the linking of the statements was, the more accurate the parameter estimation was. This paper provides an empirical example of a career interest test using four-category MFC items. Although some aspects of the model (e.g., the nature of the person parameters) require additional validation, our approach appears promising.</p>","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":"76 3","pages":"491-512"},"PeriodicalIF":2.6,"publicationDate":"2023-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bmsp.12303","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9229089","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
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