Applied Psychological Measurement最新文献_第6页

Targeted Double Scoring of Performance Tasks Using a Decision-Theoretic Approach. 使用决策理论方法对绩效任务进行有针对性的双重评分。

IF 1.2 4区心理学

Applied Psychological Measurement Pub Date : 2023-03-01 Epub Date: 2022-09-23 DOI: 10.1177/01466216221129271

Sandip Sinharay, Matthew S Johnson, Wei Wang, Jing Miao

引用次数: 0

Empirical Priors in Polytomous Computerized Adaptive Tests: Risks and Rewards in Clinical Settings. 经验先验在多细胞计算机自适应测试:风险和回报在临床设置。

IF 1.2 4区心理学

Applied Psychological Measurement Pub Date : 2023-01-01 Epub Date: 2022-09-30 DOI: 10.1177/01466216221124091

Niek Frans, Johan Braeken, Bernard P Veldkamp, Muirne C S Paap

{"title":"Empirical Priors in Polytomous Computerized Adaptive Tests: Risks and Rewards in Clinical Settings.","authors":"Niek Frans, Johan Braeken, Bernard P Veldkamp, Muirne C S Paap","doi":"10.1177/01466216221124091","DOIUrl":"https://doi.org/10.1177/01466216221124091","url":null,"abstract":"The use of empirical prior information about participants has been shown to substantially improve the efficiency of computerized adaptive tests (CATs) in educational settings. However, it is unclear how these results translate to clinical settings, where small item banks with highly informative polytomous items often lead to very short CATs. We explored the risks and rewards of using prior information in CAT in two simulation studies, rooted in applied clinical examples. In the first simulation, prior precision and bias in the prior location were manipulated independently. Our results show that a precise personalized prior can meaningfully increase CAT efficiency. However, this reward comes with the potential risk of overconfidence in wrong empirical information (i.e., using a precise severely biased prior), which can lead to unnecessarily long tests, or severely biased estimates. The latter risk can be mitigated by setting a minimum number of items that are to be administered during the CAT, or by setting a less precise prior; be it at the expense of canceling out any efficiency gains. The second simulation, with more realistic bias and precision combinations in the empirical prior, places the prevalence of the potential risks in context. With similar estimation bias, an empirical prior reduced CAT test length, compared to a standard normal prior, in 68% of cases, by a median of 20%; while test length increased in only 3% of cases. The use of prior information in CAT seems to be a feasible and simple method to reduce test burden for patients and clinical practitioners alike.","PeriodicalId":48300,"journal":{"name":"Applied Psychological Measurement","volume":"47 1","pages":"48-63"},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/57/79/10.1177_01466216221124091.PMC9679926.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40494727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

The Standardized S-X ² Statistic for Assessing Item Fit. 用于评估项目契合度的标准化 S-X 2 统计量。

IF 1.2 4区心理学

Applied Psychological Measurement Pub Date : 2023-01-01 Epub Date: 2022-09-17 DOI: 10.1177/01466216221108077

Zhuangzhuang Han, Sandip Sinharay, Matthew S Johnson, Xiang Liu

引用次数: 1

An Investigation Into the Impact of Test Session Disruptions for At-Home Test Administrations. 关于考试时段中断对在家考试的影响的调查。

IF 1.2 4区心理学

Applied Psychological Measurement Pub Date : 2023-01-01 Epub Date: 2022-09-20 DOI: 10.1177/01466216221128011

Katherine E Castellano, Sandip Sinharay, Jiangang Hao, Chen Li

{"title":"An Investigation Into the Impact of Test Session Disruptions for At-Home Test Administrations.","authors":"Katherine E Castellano, Sandip Sinharay, Jiangang Hao, Chen Li","doi":"10.1177/01466216221128011","DOIUrl":"10.1177/01466216221128011","url":null,"abstract":"In response to the closures of test centers worldwide due to the COVID-19 pandemic, several testing programs offered large-scale standardized assessments to examinees remotely. However, due to the varying quality of the performance of personal devices and internet connections, more at-home examinees likely suffered \"disruptions\" or an interruption in the connectivity to their testing session compared to typical test-center administrations. Disruptions have the potential to adversely affect examinees and lead to fairness or validity issues. The goal of this study was to investigate the extent to which disruptions impacted performance of at-home examinees using data from a large-scale admissions test. Specifically, the study involved comparing the average test scores of the disrupted examinees with those of the non-disrupted examinees after weighting the non-disrupted examinees to resemble the disrupted examinees along baseline characteristics. The results show that disruptions had a small negative impact on test scores on average. However, there was little difference in performance between the disrupted and non-disrupted examinees after removing records of the disrupted examinees who were unable to complete the test.","PeriodicalId":48300,"journal":{"name":"Applied Psychological Measurement","volume":"47 1","pages":"76-82"},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40494729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Applying Negative Binomial Distribution in Diagnostic Classification Models for Analyzing Count Data. 在诊断分类模型中应用负二项分布分析计数数据。

IF 1 4区心理学

Applied Psychological Measurement Pub Date : 2023-01-01 Epub Date: 2022-09-06 DOI: 10.1177/01466216221124604

Ren Liu, Ihnwhi Heo, Haiyan Liu, Dexin Shi, Zhehan Jiang

引用次数: 0

autoRasch: An R Package to Do Semi-Automated Rasch Analysis. autoRasch:一个R包来做半自动的Rasch分析。

IF 1.2 4区心理学

Applied Psychological Measurement Pub Date : 2023-01-01 Epub Date: 2022-10-10 DOI: 10.1177/01466216221125178

Feri Wijayanto, Ioan Gabriel Bucur, Perry Groot, Tom Heskes

引用次数: 1

Outlier Detection Using t-test in Rasch IRT Equating under NEAT Design. 在 NEAT 设计下的 Rasch IRT Equating 中使用 t 检验检测离群值。

IF 1.2 4区心理学

Applied Psychological Measurement Pub Date : 2023-01-01 Epub Date: 2022-09-06 DOI: 10.1177/01466216221124045

Chunyan Liu, Daniel Jurich

引用次数: 0

Modeling Rapid Guessing Behaviors in Computer-Based Testlet Items. 基于计算机的小测试项目中的快速猜测行为建模。

IF 1.2 4区心理学

Applied Psychological Measurement Pub Date : 2023-01-01 Epub Date: 2022-09-09 DOI: 10.1177/01466216221125177

Kuan-Yu Jin, Chia-Ling Hsu, Ming Ming Chiu, Po-Hsi Chen

{"title":"Modeling Rapid Guessing Behaviors in Computer-Based Testlet Items.","authors":"Kuan-Yu Jin, Chia-Ling Hsu, Ming Ming Chiu, Po-Hsi Chen","doi":"10.1177/01466216221125177","DOIUrl":"10.1177/01466216221125177","url":null,"abstract":"In traditional test models, test items are independent, and test-takers slowly and thoughtfully respond to each test item. However, some test items have a common stimulus (dependent test items in a testlet), and sometimes test-takers lack motivation, knowledge, or time (speededness), so they perform rapid guessing (RG). Ignoring the dependence in responses to testlet items can negatively bias standard errors of measurement, and ignoring RG by fitting a simpler item response theory (IRT) model can bias the results. Because computer-based testing captures response times on testlet responses, we propose a mixture testlet IRT model with item responses and response time to model RG behaviors in computer-based testlet items. Two simulation studies with Markov chain Monte Carlo estimation using the JAGS program showed (a) good recovery of the item and person parameters in this new model and (b) the harmful consequences of ignoring RG (biased parameter estimates: overestimated item difficulties, underestimated time intensities, underestimated respondent latent speed parameters, and overestimated precision of respondent latent estimates). The application of IRT models with and without RG to data from a computer-based language test showed parameter differences resembling those in the simulations.","PeriodicalId":48300,"journal":{"name":"Applied Psychological Measurement","volume":"47 1","pages":"19-33"},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679923/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40494726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 3

Efficient Metropolis-Hastings Robbins-Monro Algorithm for High-Dimensional Diagnostic Classification Models. 高维诊断分类模型的高效Metropolis-Hastings-Robbins-Monro算法。

IF 1.2 4区心理学

Applied Psychological Measurement Pub Date : 2022-11-01 Epub Date: 2022-09-08 DOI: 10.1177/01466216221123981

Chen-Wei Liu

{"title":"Efficient Metropolis-Hastings Robbins-Monro Algorithm for High-Dimensional Diagnostic Classification Models.","authors":"Chen-Wei Liu","doi":"10.1177/01466216221123981","DOIUrl":"10.1177/01466216221123981","url":null,"abstract":"The expectation-maximization (EM) algorithm is a commonly used technique for the parameter estimation of the diagnostic classification models (DCMs) with a prespecified Q-matrix; however, it requires O(2 K ) calculations in its expectation-step, which significantly slows down the computation when the number of attributes, K, is large. This study proposes an efficient Metropolis-Hastings Robbins-Monro (eMHRM) algorithm, needing only O(K + 1) calculations in the Monte Carlo expectation step. Furthermore, the item parameters and structural parameters are approximated via the Robbins-Monro algorithm, which does not require time-consuming nonlinear optimization procedures. A series of simulation studies were conducted to compare the eMHRM with the EM and a Metropolis-Hastings (MH) algorithm regarding the parameter recovery and execution time. The outcomes presented in this article reveal that the eMHRM is much more computationally efficient than the EM and MH, and it tends to produce better estimates than the EM when K is large, suggesting that the eMHRM is a promising parameter estimation method for high-dimensional DCMs.","PeriodicalId":48300,"journal":{"name":"Applied Psychological Measurement","volume":"46 8","pages":"662-674"},"PeriodicalIF":1.2,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9574082/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40656644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Attenuation-Corrected Estimators of Reliability. 可靠性的衰减校正估计。

IF 1.2 4区心理学

Applied Psychological Measurement Pub Date : 2022-11-01 Epub Date: 2022-09-15 DOI: 10.1177/01466216221108131

Jari Metsämuuronen

{"title":"Attenuation-Corrected Estimators of Reliability.","authors":"Jari Metsämuuronen","doi":"10.1177/01466216221108131","DOIUrl":"https://doi.org/10.1177/01466216221108131","url":null,"abstract":"The estimates of reliability are usually attenuated and deflated because the item-score correlation ( <math> <mrow><msub><mi>ρ</mi> <mrow><mi>g</mi> <mi>X</mi></mrow> </msub> </mrow> </math> , Rit) embedded in the most widely used estimators is affected by several sources of mechanical error in the estimation. Empirical examples show that, in some types of datasets, the estimates by traditional alpha may be deflated by 0.40-0.60 units of reliability and those by maximal reliability by 0.40 units of reliability. This article proposes a new kind of estimator of correlation: attenuation-corrected correlation (R AC ): the proportion of observed correlation with the maximal possible correlation reachable by the given item and score. By replacing <math> <mrow><msub><mi>ρ</mi> <mrow><mi>g</mi> <mi>X</mi></mrow> </msub> </mrow> </math> with R AC in known formulas of estimators of reliability, we get attenuation-corrected alpha, theta, omega, and maximal reliability which all belong to a family of so-called deflation-corrected estimators of reliability.","PeriodicalId":48300,"journal":{"name":"Applied Psychological Measurement","volume":"46 8","pages":"720-737"},"PeriodicalIF":1.2,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/66/7b/10.1177_01466216221108131.PMC9574086.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40573822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 5