Journal of Educational and Behavioral Statistics最新文献_第6页

Nonparametric Classification Method for Multiple-Choice Items in Cognitive Diagnosis 认知诊断中多项选择题的非参数分类方法

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-11-27 DOI: 10.3102/10769986221133088

Yu Wang, Chia-Yi Chiu, Hans-Friedrich Köhn

{"title":"Nonparametric Classification Method for Multiple-Choice Items in Cognitive Diagnosis","authors":"Yu Wang, Chia-Yi Chiu, Hans-Friedrich Köhn","doi":"10.3102/10769986221133088","DOIUrl":"https://doi.org/10.3102/10769986221133088","url":null,"abstract":"The multiple-choice (MC) item format has been widely used in educational assessments across diverse content domains. MC items purportedly allow for collecting richer diagnostic information. The effectiveness and economy of administering MC items may have further contributed to their popularity not just in educational assessment. The MC item format has also been adapted to the cognitive diagnosis (CD) framework. Early approaches simply dichotomized the responses and analyzed them with a CD model for binary responses. Obviously, this strategy cannot exploit the additional diagnostic information provided by MC items. De la Torre’s MC Deterministic Inputs, Noisy “And” Gate (MC-DINA) model was the first for the explicit analysis of items having MC response format. However, as a drawback, the attribute vectors of the distractors are restricted to be nested within the key and each other. The method presented in this article for the CD of DINA items having MC response format does not require such constraints. Another contribution of the proposed method concerns its implementation using a nonparametric classification algorithm, which predestines it for use especially in small-sample settings like classrooms, where CD is most needed for monitoring instruction and student learning. In contrast, default parametric CD estimation routines that rely on EM- or MCMC-based algorithms cannot guarantee stable and reliable estimates—despite their effectiveness and efficiency when samples are large—due to computational feasibility issues caused by insufficient sample sizes. Results of simulation studies and a real-world application are also reported.","PeriodicalId":48001,"journal":{"name":"Journal of Educational and Behavioral Statistics","volume":"48 1","pages":"189 - 219"},"PeriodicalIF":2.4,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69397792","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

Breaking Our Silence on Factor Score Indeterminacy 打破我们对因子得分不确定性的沉默

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-11-07 DOI: 10.3102/10769986221128810

N. Waller

引用次数: 2

Power Approximations for Overall Average Effects in Meta-Analysis With Dependent Effect Sizes 具有相关效应量的meta分析中总体平均效应的功率近似

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-10-17 DOI: 10.3102/10769986221127379

M. H. Vembye, J. Pustejovsky, T. Pigott

引用次数: 3

Commentary on “Obtaining Interpretable Parameters From Reparameterized Longitudinal Models: Transformation Matrices Between Growth Factors in Two Parameter Spaces” “从重新参数化的纵向模型中获得可解释的参数：两个参数空间中增长因子之间的变换矩阵”述评

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-10-06 DOI: 10.3102/10769986221126747

Ziwei Zhang, Corissa T. Rohloff, N. Kohli

引用次数: 0

Development of a High-Accuracy and Effective Online Calibration Method in CD-CAT Based on Gini Index 基于Gini指数的CD-CAT高精度有效在线标定方法研究

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-10-03 DOI: 10.3102/10769986221126741

Qingrong Tan, Yan Cai, Fen Luo, Dongbo Tu

引用次数: 0

A Collection of Numerical Recipes Useful for Building Scalable Psychometric Applications 构建可扩展的心理测量应用程序有用的数值配方集合

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-08-17 DOI: 10.3102/10769986221116905

Harold C. Doran

引用次数: 1

Estimating Heterogeneous Treatment Effects Within Latent Class Multilevel Models: A Bayesian Approach 在潜在类多水平模型中估计异质性治疗效果:贝叶斯方法

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-08-17 DOI: 10.3102/10769986221115446

Weicong Lyu, Jee-Seon Kim, Youmi Suk

引用次数: 0

Cognitive Diagnosis Modeling Incorporating Response Times and Fixation Counts: Providing Comprehensive Feedback and Accurate Diagnosis 结合反应时间和注视次数的认知诊断模型：提供全面反馈和准确诊断

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-07-28 DOI: 10.3102/10769986221111085

P. Zhan, K. Man, Stefanie A. Wind, Jonathan Malone

{"title":"Cognitive Diagnosis Modeling Incorporating Response Times and Fixation Counts: Providing Comprehensive Feedback and Accurate Diagnosis","authors":"P. Zhan, K. Man, Stefanie A. Wind, Jonathan Malone","doi":"10.3102/10769986221111085","DOIUrl":"https://doi.org/10.3102/10769986221111085","url":null,"abstract":"Respondents’ problem-solving behaviors comprise behaviors that represent complicated cognitive processes that are frequently systematically tied to one another. Biometric data, such as visual fixation counts (FCs), which are an important eye-tracking indicator, can be combined with other types of variables that reflect different aspects of problem-solving behavior to quantify variability in problem-solving behavior. To provide comprehensive feedback and accurate diagnosis when using such multimodal data, the present study proposes a multimodal joint cognitive diagnosis model that accounts for latent attributes, latent ability, processing speed, and visual engagement by simultaneously modeling response accuracy (RA), response times, and FCs. We used two simulation studies to test the feasibility of the proposed model. Findings mainly suggest that the parameters of the proposed model can be well recovered and that modeling FCs, in addition to RA and response times, could increase the comprehensiveness of feedback on problem-solving-related cognitive characteristics as well as the accuracy of knowledge structure diagnosis. An empirical example is used to demonstrate the applicability and benefits of the proposed model. We discuss the implications of our findings as they relate to research and practice.","PeriodicalId":48001,"journal":{"name":"Journal of Educational and Behavioral Statistics","volume":"47 1","pages":"736 - 776"},"PeriodicalIF":2.4,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47269107","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: 8

Testing Differential Item Functioning Without Predefined Anchor Items Using Robust Regression 使用稳健回归测试没有预定义锚项目的差异项目功能

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-07-18 DOI: 10.3102/10769986221109208

Weimeng Wang, Yang Liu, Hongyun Liu

{"title":"Testing Differential Item Functioning Without Predefined Anchor Items Using Robust Regression","authors":"Weimeng Wang, Yang Liu, Hongyun Liu","doi":"10.3102/10769986221109208","DOIUrl":"https://doi.org/10.3102/10769986221109208","url":null,"abstract":"Differential item functioning (DIF) occurs when the probability of endorsing an item differs across groups for individuals with the same latent trait level. The presence of DIF items may jeopardize the validity of an instrument; therefore, it is crucial to identify DIF items in routine operations of educational assessment. While DIF detection procedures based on item response theory (IRT) have been widely used, a majority of IRT-based DIF tests assume predefined anchor (i.e., DIF-free) items. Not only is this assumption strong, but violations to it may also lead to erroneous inferences, for example, an inflated Type I error rate. We propose a general framework to define the effect sizes of DIF without a priori knowledge of anchor items. In particular, we quantify DIF by item-specific residuals from a regression model fitted to the true item parameters in respective groups. Moreover, the null distribution of the proposed test statistic using robust estimator can be derived analytically or approximated numerically even when there is a mix of DIF and non-DIF items, which yields asymptotically justified statistical inference. The Type I error rate and the power performance of the proposed procedure are evaluated and compared with the conventional likelihood-ratio DIF tests in a Monte Carlo experiment. Our simulation study has shown promising results in controlling Type I error rate and power of detecting DIF items. Even when there is a mix of DIF and non-DIF items, the true and false alarm rate can be well controlled when a robust regression estimator is used.","PeriodicalId":48001,"journal":{"name":"Journal of Educational and Behavioral Statistics","volume":"47 1","pages":"666 - 692"},"PeriodicalIF":2.4,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42754815","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: 8

Zero and One Inflated Item Response Theory Models for Bounded Continuous Data 有界连续数据的零和一充气项目反应理论模型

IF 2.4 3区心理学

Journal of Educational and Behavioral Statistics Pub Date : 2022-07-15 DOI: 10.3102/10769986221108455

D. Molenaar, M. Curi, Jorge L. Bazán

{"title":"Zero and One Inflated Item Response Theory Models for Bounded Continuous Data","authors":"D. Molenaar, M. Curi, Jorge L. Bazán","doi":"10.3102/10769986221108455","DOIUrl":"https://doi.org/10.3102/10769986221108455","url":null,"abstract":"Bounded continuous data are encountered in many applications of item response theory, including the measurement of mood, personality, and response times and in the analyses of summed item scores. Although different item response theory models exist to analyze such bounded continuous data, most models assume the data to be in an open interval and cannot accommodate data in a closed interval. As a result, ad hoc transformations are needed to prevent scores on the bounds of the observed variables. To motivate the present study, we demonstrate in real and simulated data that this practice of fitting open interval models to closed interval data can majorly affect parameter estimates even in cases with only 5% of the responses on one of the bounds of the observed variables. To address this problem, we propose a zero and one inflated item response theory modeling framework for bounded continuous responses in the closed interval. We illustrate how four existing models for bounded responses from the literature can be accommodated in the framework. The resulting zero and one inflated item response theory models are studied in a simulation study and a real data application to investigate parameter recovery, model fit, and the consequences of fitting the incorrect distribution to the data. We find that neglecting the bounded nature of the data biases parameters and that misspecification of the exact distribution may affect the results depending on the data generating model.","PeriodicalId":48001,"journal":{"name":"Journal of Educational and Behavioral Statistics","volume":"47 1","pages":"693 - 735"},"PeriodicalIF":2.4,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45894141","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: 3