Pub Date : 2024-09-01DOI: 10.1007/s11336-024-09974-5
Chen-Wei Liu, Björn Andersson, Anders Skrondal
{"title":"Erratum: A Constrained Metropolis-Hastings Robbins-Monro Algorithm for Q Matrix Estimation in DINA Models.","authors":"Chen-Wei Liu, Björn Andersson, Anders Skrondal","doi":"10.1007/s11336-024-09974-5","DOIUrl":"10.1007/s11336-024-09974-5","url":null,"abstract":"","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":"1107"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140946581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-06-22DOI: 10.1007/s11336-024-09979-0
Garritt L Page, Ernesto San Martín, David Torres Irribarra, Sébastien Van Bellegem
We aim to estimate school value-added dynamically in time. Our principal motivation for doing so is to establish school effectiveness persistence while taking into account the temporal dependence that typically exists in school performance from one year to the next. We propose two methods of incorporating temporal dependence in value-added models. In the first we model the random school effects that are commonly present in value-added models with an auto-regressive process. In the second approach, we incorporate dependence in value-added estimators by modeling the performance of one cohort based on the previous cohort's performance. An identification analysis allows us to make explicit the meaning of the corresponding value-added indicators: based on these meanings, we show that each model is useful for monitoring specific aspects of school persistence. Furthermore, we carefully detail how value-added can be estimated over time. We show through simulations that ignoring temporal dependence when it exists results in diminished efficiency in value-added estimation while incorporating it results in improved estimation (even when temporal dependence is weak). Finally, we illustrate the methodology by considering two cohorts from Chile's national standardized test in mathematics.
{"title":"Temporally Dynamic, Cohort-Varying Value-Added Models.","authors":"Garritt L Page, Ernesto San Martín, David Torres Irribarra, Sébastien Van Bellegem","doi":"10.1007/s11336-024-09979-0","DOIUrl":"10.1007/s11336-024-09979-0","url":null,"abstract":"<p><p>We aim to estimate school value-added dynamically in time. Our principal motivation for doing so is to establish school effectiveness persistence while taking into account the temporal dependence that typically exists in school performance from one year to the next. We propose two methods of incorporating temporal dependence in value-added models. In the first we model the random school effects that are commonly present in value-added models with an auto-regressive process. In the second approach, we incorporate dependence in value-added estimators by modeling the performance of one cohort based on the previous cohort's performance. An identification analysis allows us to make explicit the meaning of the corresponding value-added indicators: based on these meanings, we show that each model is useful for monitoring specific aspects of school persistence. Furthermore, we carefully detail how value-added can be estimated over time. We show through simulations that ignoring temporal dependence when it exists results in diminished efficiency in value-added estimation while incorporating it results in improved estimation (even when temporal dependence is weak). Finally, we illustrate the methodology by considering two cohorts from Chile's national standardized test in mathematics.</p>","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":"1074-1103"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141441115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-03-01DOI: 10.1007/s11336-024-09955-8
Chengyu Cui, Chun Wang, Gongjun Xu
Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichotomous responses have been developed, but constructing an equally efficient and robust algorithm for polytomous models has received limited attention. To address this gap, this paper presents a novel Gaussian variational estimation algorithm for the multidimensional generalized partial credit model. The proposed algorithm demonstrates both fast and accurate performance, as illustrated through a series of simulation studies and two real data analyses.
{"title":"Variational Estimation for Multidimensional Generalized Partial Credit Model.","authors":"Chengyu Cui, Chun Wang, Gongjun Xu","doi":"10.1007/s11336-024-09955-8","DOIUrl":"10.1007/s11336-024-09955-8","url":null,"abstract":"<p><p>Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichotomous responses have been developed, but constructing an equally efficient and robust algorithm for polytomous models has received limited attention. To address this gap, this paper presents a novel Gaussian variational estimation algorithm for the multidimensional generalized partial credit model. The proposed algorithm demonstrates both fast and accurate performance, as illustrated through a series of simulation studies and two real data analyses.</p>","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":"929-957"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140013759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-14DOI: 10.1007/s11336-024-09987-0
Michael C Edwards
{"title":"Book Review: Subscores : A Practical Guide to Their Production and Consumption by Shelby Haberman, Sandip Sinharay, Richard A. Feinberg, & Howard Wainer.","authors":"Michael C Edwards","doi":"10.1007/s11336-024-09987-0","DOIUrl":"https://doi.org/10.1007/s11336-024-09987-0","url":null,"abstract":"","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141977236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.1007/s11336-024-09986-1
Sun-Joo Cho, Sarah Brown-Schmidt, Sharice Clough, Melissa C Duff
This paper presents a model specification for group comparisons regarding a functional trend over time within a trial and learning across a series of trials in intensive binary longitudinal eye-tracking data. The functional trend and learning effects are modeled using by-variable smooth functions. This model specification is formulated as a generalized additive mixed model, which allowed for the use of the freely available mgcv package (Wood in Package 'mgcv.' https://cran.r-project.org/web/packages/mgcv/mgcv.pdf , 2023) in R. The model specification was applied to intensive binary longitudinal eye-tracking data, where the questions of interest concern differences between individuals with and without brain injury in their real-time language comprehension and how this affects their learning over time. The results of the simulation study show that the model parameters are recovered well and the by-variable smooth functions are adequately predicted in the same condition as those found in the application.
本文介绍了一种模型规范,用于在密集二元纵向眼动跟踪数据中,对一次试验中随时间变化的功能趋势和一系列试验中的学习效果进行分组比较。功能趋势和学习效果是通过变量平滑函数来建模的。该模型规格被表述为广义加性混合模型,因此可以使用 R 中免费提供的 mgcv 软件包(Wood in Package 'mgcv.' https://cran.r-project.org/web/packages/mgcv/mgcv.pdf , 2023)。该模型规格被应用于密集二元纵向眼动跟踪数据,其中感兴趣的问题涉及脑损伤患者和非脑损伤患者在实时语言理解方面的差异,以及这种差异如何影响他们随着时间推移的学习。模拟研究的结果表明,模型参数恢复良好,在与应用中发现的相同条件下,副变量平滑函数得到了充分预测。
{"title":"Comparing Functional Trend and Learning among Groups in Intensive Binary Longitudinal Eye-Tracking Data using By-Variable Smooth Functions of GAMM.","authors":"Sun-Joo Cho, Sarah Brown-Schmidt, Sharice Clough, Melissa C Duff","doi":"10.1007/s11336-024-09986-1","DOIUrl":"https://doi.org/10.1007/s11336-024-09986-1","url":null,"abstract":"<p><p>This paper presents a model specification for group comparisons regarding a functional trend over time within a trial and learning across a series of trials in intensive binary longitudinal eye-tracking data. The functional trend and learning effects are modeled using by-variable smooth functions. This model specification is formulated as a generalized additive mixed model, which allowed for the use of the freely available mgcv package (Wood in Package 'mgcv.' https://cran.r-project.org/web/packages/mgcv/mgcv.pdf , 2023) in R. The model specification was applied to intensive binary longitudinal eye-tracking data, where the questions of interest concern differences between individuals with and without brain injury in their real-time language comprehension and how this affects their learning over time. The results of the simulation study show that the model parameters are recovered well and the by-variable smooth functions are adequately predicted in the same condition as those found in the application.</p>","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141629273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01Epub Date: 2024-03-22DOI: 10.1007/s11336-024-09961-w
Mengqi Lin, Gongjun Xu
Cognitive diagnosis models (CDMs) provide a powerful statistical and psychometric tool for researchers and practitioners to learn fine-grained diagnostic information about respondents' latent attributes. There has been a growing interest in the use of CDMs for polytomous response data, as more and more items with multiple response options become widely used. Similar to many latent variable models, the identifiability of CDMs is critical for accurate parameter estimation and valid statistical inference. However, the existing identifiability results are primarily focused on binary response models and have not adequately addressed the identifiability of CDMs with polytomous responses. This paper addresses this gap by presenting sufficient and necessary conditions for the identifiability of the widely used DINA model with polytomous responses, with the aim to provide a comprehensive understanding of the identifiability of CDMs with polytomous responses and to inform future research in this field.
认知诊断模型(CDMs)为研究人员和从业人员提供了一种强大的统计和心理测量工具,用于了解受访者潜在属性的精细诊断信息。随着越来越多的具有多重响应选项的项目被广泛使用,人们对使用 CDMs 处理多态响应数据的兴趣日益浓厚。与许多潜变量模型类似,CDM 的可识别性对于准确的参数估计和有效的统计推断至关重要。然而,现有的可识别性结果主要集中在二元响应模型上,并没有充分解决多态响应 CDM 的可识别性问题。本文针对这一空白,提出了被广泛使用的具有多态响应的 DINA 模型的可识别性的充分和必要条件,旨在提供对具有多态响应的 CDM 的可识别性的全面理解,并为该领域的未来研究提供参考。
{"title":"Sufficient and Necessary Conditions for the Identifiability of DINA Models with Polytomous Responses.","authors":"Mengqi Lin, Gongjun Xu","doi":"10.1007/s11336-024-09961-w","DOIUrl":"10.1007/s11336-024-09961-w","url":null,"abstract":"<p><p>Cognitive diagnosis models (CDMs) provide a powerful statistical and psychometric tool for researchers and practitioners to learn fine-grained diagnostic information about respondents' latent attributes. There has been a growing interest in the use of CDMs for polytomous response data, as more and more items with multiple response options become widely used. Similar to many latent variable models, the identifiability of CDMs is critical for accurate parameter estimation and valid statistical inference. However, the existing identifiability results are primarily focused on binary response models and have not adequately addressed the identifiability of CDMs with polytomous responses. This paper addresses this gap by presenting sufficient and necessary conditions for the identifiability of the widely used DINA model with polytomous responses, with the aim to provide a comprehensive understanding of the identifiability of CDMs with polytomous responses and to inform future research in this field.</p>","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":"717-740"},"PeriodicalIF":2.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140190424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01Epub Date: 2024-01-08DOI: 10.1007/s11336-023-09945-2
Jonas Moss
Most measures of agreement are chance-corrected. They differ in three dimensions: their definition of chance agreement, their choice of disagreement function, and how they handle multiple raters. Chance agreement is usually defined in a pairwise manner, following either Cohen's kappa or Fleiss's kappa. The disagreement function is usually a nominal, quadratic, or absolute value function. But how to handle multiple raters is contentious, with the main contenders being Fleiss's kappa, Conger's kappa, and Hubert's kappa, the variant of Fleiss's kappa where agreement is said to occur only if every rater agrees. More generally, multi-rater agreement coefficients can be defined in a g-wise way, where the disagreement weighting function uses g raters instead of two. This paper contains two main contributions. (a) We propose using Fréchet variances to handle the case of multiple raters. The Fréchet variances are intuitive disagreement measures and turn out to generalize the nominal, quadratic, and absolute value functions to the case of more than two raters. (b) We derive the limit theory of g-wise weighted agreement coefficients, with chance agreement of the Cohen-type or Fleiss-type, for the case where every item is rated by the same number of raters. Trying out three confidence interval constructions, we end up recommending calculating confidence intervals using the arcsine transform or the Fisher transform.
{"title":"Measures of Agreement with Multiple Raters: Fréchet Variances and Inference.","authors":"Jonas Moss","doi":"10.1007/s11336-023-09945-2","DOIUrl":"10.1007/s11336-023-09945-2","url":null,"abstract":"<p><p>Most measures of agreement are chance-corrected. They differ in three dimensions: their definition of chance agreement, their choice of disagreement function, and how they handle multiple raters. Chance agreement is usually defined in a pairwise manner, following either Cohen's kappa or Fleiss's kappa. The disagreement function is usually a nominal, quadratic, or absolute value function. But how to handle multiple raters is contentious, with the main contenders being Fleiss's kappa, Conger's kappa, and Hubert's kappa, the variant of Fleiss's kappa where agreement is said to occur only if every rater agrees. More generally, multi-rater agreement coefficients can be defined in a g-wise way, where the disagreement weighting function uses g raters instead of two. This paper contains two main contributions. (a) We propose using Fréchet variances to handle the case of multiple raters. The Fréchet variances are intuitive disagreement measures and turn out to generalize the nominal, quadratic, and absolute value functions to the case of more than two raters. (b) We derive the limit theory of g-wise weighted agreement coefficients, with chance agreement of the Cohen-type or Fleiss-type, for the case where every item is rated by the same number of raters. Trying out three confidence interval constructions, we end up recommending calculating confidence intervals using the arcsine transform or the Fisher transform.</p>","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":"517-541"},"PeriodicalIF":2.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11164747/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139378748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01Epub Date: 2024-03-26DOI: 10.1007/s11336-024-09949-6
Kenneth A Bollen, Kathleen M Gates, Lan Luo
Spearman (Am J Psychol 15(1):201-293, 1904. https://doi.org/10.2307/1412107 ) marks the birth of factor analysis. Many articles and books have extended his landmark paper in permitting multiple factors and determining the number of factors, developing ideas about simple structure and factor rotation, and distinguishing between confirmatory and exploratory factor analysis (CFA and EFA). We propose a new model implied instrumental variable (MIIV) approach to EFA that allows intercepts for the measurement equations, correlated common factors, correlated errors, standard errors of factor loadings and measurement intercepts, overidentification tests of equations, and a procedure for determining the number of factors. We also permit simpler structures by removing nonsignificant loadings. Simulations of factor analysis models with and without cross-loadings demonstrate the impressive performance of the MIIV-EFA procedure in recovering the correct number of factors and in recovering the primary and secondary loadings. For example, in nearly all replications MIIV-EFA finds the correct number of factors when N is 100 or more. Even the primary and secondary loadings of the most complex models were recovered when the sample sizes were at least 500. We discuss limitations and future research areas. Two appendices describe alternative MIIV-EFA algorithms and the sensitivity of the algorithm to cross-loadings.
{"title":"A Model Implied Instrumental Variable Approach to Exploratory Factor Analysis (MIIV-EFA).","authors":"Kenneth A Bollen, Kathleen M Gates, Lan Luo","doi":"10.1007/s11336-024-09949-6","DOIUrl":"10.1007/s11336-024-09949-6","url":null,"abstract":"<p><p>Spearman (Am J Psychol 15(1):201-293, 1904. https://doi.org/10.2307/1412107 ) marks the birth of factor analysis. Many articles and books have extended his landmark paper in permitting multiple factors and determining the number of factors, developing ideas about simple structure and factor rotation, and distinguishing between confirmatory and exploratory factor analysis (CFA and EFA). We propose a new model implied instrumental variable (MIIV) approach to EFA that allows intercepts for the measurement equations, correlated common factors, correlated errors, standard errors of factor loadings and measurement intercepts, overidentification tests of equations, and a procedure for determining the number of factors. We also permit simpler structures by removing nonsignificant loadings. Simulations of factor analysis models with and without cross-loadings demonstrate the impressive performance of the MIIV-EFA procedure in recovering the correct number of factors and in recovering the primary and secondary loadings. For example, in nearly all replications MIIV-EFA finds the correct number of factors when N is 100 or more. Even the primary and secondary loadings of the most complex models were recovered when the sample sizes were at least 500. We discuss limitations and future research areas. Two appendices describe alternative MIIV-EFA algorithms and the sensitivity of the algorithm to cross-loadings.</p>","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":"687-716"},"PeriodicalIF":2.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140295346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01DOI: 10.1007/s11336-024-09981-6
Sandip Sinharay
{"title":"Remarks From the Editor-in-Chief.","authors":"Sandip Sinharay","doi":"10.1007/s11336-024-09981-6","DOIUrl":"10.1007/s11336-024-09981-6","url":null,"abstract":"","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":"385"},"PeriodicalIF":3.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141181425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-01Epub Date: 2024-02-20DOI: 10.1007/s11336-024-09953-w
Martin Jann, Martin Spiess
Empirical research usually takes place in a space of available external information, like results from single studies, meta-analyses, official statistics or subjective (expert) knowledge. The available information ranges from simple means and proportions to known relations between a multitude of variables or estimated distributions. In psychological research, external information derived from the named sources may be used to build a theory and derive hypotheses. In addition, techniques do exist that use external information in the estimation process, for example prior distributions in Bayesian statistics. In this paper, we discuss the benefits of adopting generalized method of moments with external moments, as another example for such a technique. Analytical formulas for estimators and their variances in the multiple linear regression case are derived. An R function that implements these formulas is provided in the supplementary material for general applied use. The effects of various practically relevant moments are analyzed and tested in a simulation study. A new approach to robustify the estimators against misspecification of the external moments based on the concept of imprecise probabilities is introduced. Finally, the resulting externally informed model is applied to a dataset to investigate the predictability of the premorbid intelligence quotient based on lexical tasks, leading to a reduction of variances and thus to narrower confidence intervals.
实证研究通常是在可获得的外部信息空间内进行的,如单项研究结果、元分析、官方 统计数据或主观(专家)知识。可用信息的范围从简单的均值和比例到众多变量之间的已知关系或估计分布。在心理学研究中,从上述来源获得的外部信息可用于建立理论和推导假设。此外,确实存在在估计过程中使用外部信息的技术,例如贝叶斯统计中的先验分布。在本文中,我们将以外部矩为例,讨论采用广义矩法的好处。本文推导了多元线性回归情况下估计量及其方差的分析公式。补充材料中提供了一个实现这些公式的 R 函数,供一般应用使用。在模拟研究中分析并测试了各种实际相关矩的影响。此外,还介绍了一种基于不精确概率概念的新方法,用于加强估计器的稳健性,防止外部矩的错误规范。最后,将所得到的外部信息模型应用于一个数据集,以研究基于词汇任务的病前智商的可预测性,从而减少方差,缩小置信区间。
{"title":"Using External Information for More Precise Inferences in General Regression Models.","authors":"Martin Jann, Martin Spiess","doi":"10.1007/s11336-024-09953-w","DOIUrl":"10.1007/s11336-024-09953-w","url":null,"abstract":"<p><p>Empirical research usually takes place in a space of available external information, like results from single studies, meta-analyses, official statistics or subjective (expert) knowledge. The available information ranges from simple means and proportions to known relations between a multitude of variables or estimated distributions. In psychological research, external information derived from the named sources may be used to build a theory and derive hypotheses. In addition, techniques do exist that use external information in the estimation process, for example prior distributions in Bayesian statistics. In this paper, we discuss the benefits of adopting generalized method of moments with external moments, as another example for such a technique. Analytical formulas for estimators and their variances in the multiple linear regression case are derived. An R function that implements these formulas is provided in the supplementary material for general applied use. The effects of various practically relevant moments are analyzed and tested in a simulation study. A new approach to robustify the estimators against misspecification of the external moments based on the concept of imprecise probabilities is introduced. Finally, the resulting externally informed model is applied to a dataset to investigate the predictability of the premorbid intelligence quotient based on lexical tasks, leading to a reduction of variances and thus to narrower confidence intervals.</p>","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":"439-460"},"PeriodicalIF":2.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11164816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139914062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}