Content
September 2024, Volume 89, Issue 3
- 745-746 Remarks from the Editor-in-Chief
by Sandip Sinharay - 747-773 A Diagnostic Facet Status Model (DFSM) for Extracting Instructionally Useful Information from Diagnostic Assessment
by Chun Wang - 774-795 Proof of Reliability Convergence to 1 at Rate of Spearman–Brown Formula for Random Test Forms and Irrespective of Item Pool Dimensionality
by Jules L. Ellis & Klaas Sijtsma - 796-821 Differential Item Functioning via Robust Scaling
by Peter F. Halpin - 822-850 Non-parametric Regression Among Factor Scores: Motivation and Diagnostics for Nonlinear Structural Equation Models
by Steffen Grønneberg & Julien Patrick Irmer - 851-876 Diagnostic Classification Models for Testlets: Methods and Theory
by Xin Xu & Guanhua Fang & Jinxin Guo & Zhiliang Ying & Susu Zhang - 877-902 Polytomous Effectiveness Indicators in Complex Problem-Solving Tasks and Their Applications in Developing Measurement Model
by Pujue Wang & Hongyun Liu - 903-928 Parallel Optimal Calibration of Mixed-Format Items for Achievement Tests
by Frank Miller & Ellinor Fackle-Fornius - 929-957 Variational Estimation for Multidimensional Generalized Partial Credit Model
by Chengyu Cui & Chun Wang & Gongjun Xu - 958-973 Extended Asymptotic Identifiability of Nonparametric Item Response Models
by Yinqiu He - 974-1006 Signal-to-Noise Ratio in Estimating and Testing the Mediation Effect: Structural Equation Modeling versus Path Analysis with Weighted Composites
by Ke-Hai Yuan & Zhiyong Zhang & Lijuan Wang - 1007-1033 The Crosswise Model for Surveys on Sensitive Topics: A General Framework for Item Selection and Statistical Analysis
by Marco Gregori & Martijn G. Jong & Rik Pieters - 1034-1054 The InterModel Vigorish as a Lens for Understanding (and Quantifying) the Value of Item Response Models for Dichotomously Coded Items
by Benjamin W. Domingue & Klint Kanopka & Radhika Kapoor & Steffi Pohl & R. Philip Chalmers & Charles Rahal & Mijke Rhemtulla - 1055-1073 Adventitious Error and Its Implications for Testing Relations Between Variables and for Composite Measurement Outcomes
by Paul Boeck & Michael L. DeKay & Jolynn Pek - 1074-1103 Temporally Dynamic, Cohort-Varying Value-Added Models
by Garritt L. Page & Ernesto San Martín & David Torres Irribarra & Sébastien Van Bellegem - 1104-1106 Book Review: Subscores : A Practical Guide to Their Production and Consumption by Shelby Haberman, Sandip Sinharay, Richard A. Feinberg, & Howard Wainer
by Michael C. Edwards - 1107-1107 Erratum: A Constrained Metropolis–Hastings Robbins–Monro Algorithm for Q Matrix Estimation in DINA Models
by Chen-Wei Liu & Björn Andersson & Anders Skrondal - 1108-1108 Correction: A Diagnostic Facet Status Model (DFSM) for Extracting Instructionally Useful Information from Diagnostic Assessment
by Chun Wang - 1109-1109 Correction: Book Review of Mixture and Hidden Markov Models with R, by Visser & Speekenbrink
by Francesco Bartolucci & Fulvia Pennoni - 1110-1110 Correction: Book Review of Item Response Theory by Bock and Gibbons
by Ji Seung Yang & Yang Liu & Sungyeun Kim - 1111-1111 Correction: Book Review of Longitudinal Structural Equation Modeling with Mplus: A Latent State-Trait Perspective by Geiser
by Ihnwhi Heo & Fan Jia & Sarah Depaoli - 1112-1112 Correction: Book Review of Essays on Contemporary Psychometrics by Van der Ark, Emons & Meijer
by Youn Seon Lim - 1113-1113 Correction: Book Review of Composite-Based Structural Equation Modeling: Analyzing Latent and Emergent Variables by J. Henseler
by Laura Trinchera - 1114-1114 Correction: Book Review of Psychometric Methods: Theory into Practice by Price
by Manqian Liao & Hong Jiao - 1115-1115 Correction: Book Review of Innovative Assessment of Collaboration by Davier, Shu & Kyllonen
by Tyler H. Matta - 1116-1116 Correction: Book Review of Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models by Faraway
by Andreas Rosenblad
June 2024, Volume 89, Issue 2
- 385-385 Remarks From the Editor-in-Chief
by Sandip Sinharay - 386-410 What Can We Learn from a Semiparametric Factor Analysis of Item Responses and Response Time? An Illustration with the PISA 2015 Data
by Yang Liu & Weimeng Wang - 411-438 Exploratory Procedure for Component-Based Structural Equation Modeling for Simple Structure by Simultaneous Rotation
by Naoto Yamashita - 439-460 Using External Information for More Precise Inferences in General Regression Models
by Martin Jann & Martin Spiess - 461-485 Bayesian Semiparametric Longitudinal Inverse-Probit Mixed Models for Category Learning
by Minerva Mukhopadhyay & Jacie R. McHaney & Bharath Chandrasekaran & Abhra Sarkar - 486-516 On the Identifiability of 3- and 4-Parameter Item Response Theory Models From the Perspective of Knowledge Space Theory
by Stefano Noventa & Sangbeak Ye & Augustin Kelava & Andrea Spoto - 517-541 Measures of Agreement with Multiple Raters: Fréchet Variances and Inference
by Jonas Moss - 542-568 Post-selection Inference in Multiverse Analysis (PIMA): An Inferential Framework Based on the Sign Flipping Score Test
by Paolo Girardi & Anna Vesely & Daniël Lakens & Gianmarco Altoè & Massimiliano Pastore & Antonio Calcagnì & Livio Finos - 569-591 Efficient Corrections for Standardized Person-Fit Statistics
by Kylie Gorney & Sandip Sinharay & Carol Eckerly - 592-625 Restricted Latent Class Models for Nominal Response Data: Identifiability and Estimation
by Ying Liu & Steven Andrew Culpepper - 626-657 A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses
by Ling Chen & Yuqi Gu - 658-686 Learning Bayesian Networks: A Copula Approach for Mixed-Type Data
by Federico Castelletti - 687-716 A Model Implied Instrumental Variable Approach to Exploratory Factor Analysis (MIIV-EFA)
by Kenneth A. Bollen & Kathleen M. Gates & Lan Luo - 717-740 Sufficient and Necessary Conditions for the Identifiability of DINA Models with Polytomous Responses
by Mengqi Lin & Gongjun Xu - 741-743 Book Review of Mixture and Hidden Markov Models with R by Visser & Speekenbrink
by Francesco Bartolucci & Fulvia Pennoni
March 2024, Volume 89, Issue 1
- 1-3 Remarks from the New Editor-in-Chief
by Sandip Sinharay - 4-41 Examining Differential Item Functioning from a Multidimensional IRT Perspective
by Terry A. Ackerman & Ye Ma - 42-63 Reducing Attenuation Bias in Regression Analyses Involving Rating Scale Data via Psychometric Modeling
by Cees A. W. Glas & Terrence D. Jorgensen & Debby ten Hove - 64-83 Sociocognitive and Argumentation Perspectives on Psychometric Modeling in Educational Assessment
by Robert J. Mislevy - 84-117 Recognize the Value of the Sum Score, Psychometrics’ Greatest Accomplishment
by Klaas Sijtsma & Jules L. Ellis & Denny Borsboom - 118-150 Going Deep in Diagnostic Modeling: Deep Cognitive Diagnostic Models (DeepCDMs)
by Yuqi Gu - 151-171 Nodal Heterogeneity can Induce Ghost Triadic Effects in Relational Event Models
by Rūta Juozaitienė & Ernst C. Wit - 172-204 A Note on Improving Variational Estimation for Multidimensional Item Response Theory
by Chenchen Ma & Jing Ouyang & Chun Wang & Gongjun Xu - 205-240 A Latent Hidden Markov Model for Process Data
by Xueying Tang - 241-266 Generalized Structured Component Analysis Accommodating Convex Components: A Knowledge-Based Multivariate Method with Interpretable Composite Indexes
by Gyeongcheol Cho & Heungsun Hwang - 267-295 DIF Analysis with Unknown Groups and Anchor Items
by Gabriel Wallin & Yunxiao Chen & Irini Moustaki - 296-316 A Multidimensional Model to Facilitate Within Person Comparison of Attributes
by Mark L. Davison & Seungwon Chung & Nidhi Kohli & Ernest C. Davenport - 317-346 Adjusted Residuals for Evaluating Conditional Independence in IRT Models for Multistage Adaptive Testing
by Peter W. Rijn & Usama S. Ali & Hyo Jeong Shin & Sean-Hwane Joo - 347-375 Regularized Variational Estimation for Exploratory Item Factor Analysis
by April E. Cho & Jiaying Xiao & Chun Wang & Gongjun Xu - 376-380 Book Review Computational Aspects of Psychometric Methods by Martinková & Hladká
by Zhiqing Lin & Huilin Chen
December 2023, Volume 88, Issue 4
- 1097-1122 DIF Statistical Inference Without Knowing Anchoring Items
by Yunxiao Chen & Chengcheng Li & Jing Ouyang & Gongjun Xu - 1123-1143 Diagnosing and Handling Common Violations of Missing at Random
by Feng Ji & Sophia Rabe-Hesketh & Anders Skrondal - 1144-1170 A two-step estimator for multilevel latent class analysis with covariates
by Roberto Mari & Zsuzsa Bakk & Jennifer Oser & Jouni Kuha - 1171-1196 Designing Optimal, Data-Driven Policies from Multisite Randomized Trials
by Youmi Suk & Chan Park - 1197-1227 Joint Latent Space Model for Social Networks with Multivariate Attributes
by Selena Wang & Subhadeep Paul & Paul Boeck - 1228-1248 Maximum Augmented Empirical Likelihood Estimation of Categorical Marginal Models for Large Sparse Contingency Tables
by L. Andries Ark & Wicher P. Bergsma & Letty Koopman - 1249-1298 Power Analysis for the Wald, LR, Score, and Gradient Tests in a Marginal Maximum Likelihood Framework: Applications in IRT
by Felix Zimmer & Clemens Draxler & Rudolf Debelak - 1299-1333 Three Psychometric-Model-Based Option-Scored Multiple Choice Item Design Principles that Enhance Instruction by Improving Quiz Diagnostic Classification of Knowledge Attributes
by William Stout & Robert Henson & Lou DiBello - 1334-1353 A General Theorem and Proof for the Identification of Composed CFA Models
by R. Maximilian Bee & Tobias Koch & Michael Eid - 1354-1380 Dynamic Response Strategies: Accounting for Response Process Heterogeneity in IRTree Decision Nodes
by Viola Merhof & Thorsten Meiser - 1381-1406 Sparse and Simple Structure Estimation via Prenet Penalization
by Kei Hirose & Yoshikazu Terada - 1407-1442 A Mixed Stochastic Approximation EM (MSAEM) Algorithm for the Estimation of the Four-Parameter Normal Ogive Model
by Xiangbin Meng & Gongjun Xu - 1443-1465 The Bradley–Terry Regression Trunk approach for Modeling Preference Data with Small Trees
by Alessio Baldassarre & Elise Dusseldorp & Antonio D’Ambrosio & Mark de Rooij & Claudio Conversano - 1466-1494 Within-Person Variability Score-Based Causal Inference: A Two-Step Estimation for Joint Effects of Time-Varying Treatments
by Satoshi Usami - 1495-1528 A Bayesian Approach Towards Missing Covariate Data in Multilevel Latent Regression Models
by Christian Aßmann & Jean-Christoph Gaasch & Doris Stingl - 1529-1555 How Social Networks Influence Human Behavior: An Integrated Latent Space Approach for Differential Social Influence
by Jina Park & Ick Hoon Jin & Minjeong Jeon - 1556-1589 Estimating and Using Block Information in the Thurstonian IRT Model
by Susanne Frick - 1590-1590 Erratum to: Within-Person Variability Score-Based Causal Inference: A Two-Step Estimation for Joint Effects of Time-Varying Treatments
by Satoshi Usami - 1591-1591 Erratum to: Rejoinder to Commentaries on Lyu, Bolt and Westby’s “Exploring the Effects of Item Specific Factors in Sequential and IRTree Models”
by Weicong Lyu & Daniel M. Bolt - 1592-1592 Erratum to: A Modeling Framework to Examine Psychological Processes Underlying Ordinal Responses and Response Times of Psychometric Data
by Inhan Kang & Dylan Molenaar & Roger Ratcliff
September 2023, Volume 88, Issue 3
- 739-744 Item-Specific Factors in IRTree Models: When They Matter and When They Don’t
by Thorsten Meiser & Fabiola Reiber - 745-775 Exploring the Effects of Item-Specific Factors in Sequential and IRTree Models
by Weicong Lyu & Daniel M. Bolt & Samuel Westby - 776-802 Factor Tree Copula Models for Item Response Data
by Sayed H. Kadhem & Aristidis K. Nikoloulopoulos - 803-808 Commentary: Explore Conditional Dependencies in Item Response Tree Data
by Minjeong Jeon - 809-829 Random Effects Multinomial Processing Tree Models: A Maximum Likelihood Approach
by Steffen Nestler & Edgar Erdfelder - 830-864 A Latent Space Diffusion Item Response Theory Model to Explore Conditional Dependence between Responses and Response Times
by Inhan Kang & Minjeong Jeon & Ivailo Partchev - 865-887 Rotating Factors to Simplify Their Structural Paths
by Guangjian Zhang & Minami Hattori & Lauren A. Trichtinger - 888-916 The Dirichlet Dual Response Model: An Item Response Model for Continuous Bounded Interval Responses
by Matthias Kloft & Raphael Hartmann & Andreas Voss & Daniel W. Heck - 917-939 Fitting and Testing Log-Linear Subpopulation Models with Known Support
by David J. Hessen - 940-974 A Modeling Framework to Examine Psychological Processes Underlying Ordinal Responses and Response Times of Psychometric Data
by Inhan Kang & Dylan Molenaar & Roger Ratcliff - 975-1001 Multinomial Logistic Factor Regression for Multi-source Functional Block-wise Missing Data
by Xiuli Du & Xiaohu Jiang & Jinguan Lin - 1002-1025 Measuring Agreement Using Guessing Models and Knowledge Coefficients
by Jonas Moss - 1026-1031 Rejoinder to Commentaries on Lyu, Bolt and Westby’s “Exploring the Effects of Item Specific Factors in Sequential and IRTree Models”
by Weicong Lyu & Daniel M. Bolt - 1032-1055 Comparing Bayesian Variable Selection to Lasso Approaches for Applications in Psychology
by Sierra A. Bainter & Thomas G. McCauley & Mahmoud M. Fahmy & Zachary T. Goodman & Lauren B. Kupis & J. Sunil Rao - 1056-1086 Incorporating Functional Response Time Effects into a Signal Detection Theory Model
by Sun-Joo Cho & Sarah Brown-Schmidt & Paul De Boeck & Matthew Naveiras & Si On Yoon & Aaron Benjamin - 1087-1091 Book Review of Item Response Theory by Bock & Gibbons
by Ji Seung Yang & Yang Liu & Sungyeun Kim - 1092-1095 Book Review of Essays on Contemporary Psychometrics by Van der Ark, Emons & Meijer
by Youn Seon Lim
June 2023, Volume 88, Issue 2
- 361-386 Identifiability of Hidden Markov Models for Learning Trajectories in Cognitive Diagnosis
by Ying Liu & Steven Andrew Culpepper & Yuguo Chen - 387-412 A Test to Distinguish Monotone Homogeneity from Monotone Multifactor Models
by Jules L. Ellis & Klaas Sijtsma - 413-433 Advantages of Using Unweighted Approximation Error Measures for Model Fit Assessment
by Dirk Lubbe - 434-455 Blind Subgrouping of Task-based fMRI
by Zachary F. Fisher & Jonathan Parsons & Kathleen M. Gates & Joseph B. Hopfinger - 456-486 Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models
by Øystein Sørensen & Anders M. Fjell & Kristine B. Walhovd - 487-526 Dynamical Non-compensatory Multidimensional IRT Model Using Variational Approximation
by Hiroshi Tamano & Daichi Mochihashi - 527-553 Rotation to Sparse Loadings Using $$L^p$$ L p Losses and Related Inference Problems
by Xinyi Liu & Gabriel Wallin & Yunxiao Chen & Irini Moustaki - 554-579 The Dependence of Chance-Corrected Weighted Agreement Coefficients on the Power Parameter of the Weighting Scheme: Analysis and Measurement
by Rutger Oest - 580-612 A Tensor-EM Method for Large-Scale Latent Class Analysis with Binary Responses
by Zhenghao Zeng & Yuqi Gu & Gongjun Xu - 613-635 Bayesian Inference for an Unknown Number of Attributes in Restricted Latent Class Models
by Yinghan Chen & Steven Andrew Culpepper & Yuguo Chen - 636-655 Detecting Changes in Correlation Networks with Application to Functional Connectivity of fMRI Data
by Changryong Baek & Benjamin Leinwand & Kristen A. Lindquist & Seok-Oh Jeong & Joseph Hopfinger & Katheleen M. Gates & Vladas Pipiras - 656-671 Commentary on “Extending the Basic Local Independence Model to Polytomous Data” by Stefanutti, de Chiusole, Anselmi, and Spoto
by Chia-Yi Chiu & Hans Friedrich Köhn & Wenchao Ma - 672-696 Sequential Generalized Likelihood Ratio Tests for Online Item Monitoring
by Hyeon-Ah Kang - 697-729 Modeling Eye Movements During Decision Making: A Review
by Michel Wedel & Rik Pieters & Ralf Lans - 730-732 Book Review of Composite-Based Structural Equation Modeling: Analyzing Latent and Emergent Variables by Henseler
by Laura Trinchera - 733-737 Book Review of Longitudinal Structural Equation Modeling with Mplus: A Latent State-Trait Perspective by Geiser
by Ihnwhi Heo & Fan Jia & Sarah Depaoli
March 2023, Volume 88, Issue 1
- 1-30 Bayesian Dynamic Borrowing of Historical Information with Applications to the Analysis of Large-Scale Assessments
by David Kaplan & Jianshen Chen & Sinan Yavuz & Weicong Lyu - 31-50 Ignoring Non-ignorable Missingness
by Sophia Rabe-Hesketh & Anders Skrondal - 51-75 Bridging Parametric and Nonparametric Methods in Cognitive Diagnosis
by Chenchen Ma & Jimmy Torre & Gongjun Xu - 76-97 Accurate Assessment via Process Data
by Susu Zhang & Zhi Wang & Jitong Qi & Jingchen Liu & Zhiliang Ying - 98-116 A Note on the Connection Between Trek Rules and Separable Nonlinear Least Squares in Linear Structural Equation Models
by Maximilian S. Ernst & Aaron Peikert & Andreas M. Brandmaier & Yves Rosseel - 117-131 Generic Identifiability of the DINA Model and Blessing of Latent Dependence
by Yuqi Gu - 132-157 Bi-factor and Second-Order Copula Models for Item Response Data
by Sayed H. Kadhem & Aristidis K. Nikoloulopoulos - 158-174 A Note on Weaker Conditions for Identifying Restricted Latent Class Models for Binary Responses
by Steven Andrew Culpepper - 175-207 Learning Latent and Hierarchical Structures in Cognitive Diagnosis Models
by Chenchen Ma & Jing Ouyang & Gongjun Xu - 208-240 An Extended GFfit Statistic Defined on Orthogonal Components of Pearson’s Chi-Square
by Mark Reiser & Silvia Cagnone & Junfei Zhu - 241-252 Partial Identification of Latent Correlations with Ordinal Data
by Jonas Moss & Steffen Grønneberg - 253-273 Accurate Confidence and Bayesian Interval Estimation for Non-centrality Parameters and Effect Size Indices
by Kaidi Kang & Megan T. Jones & Kristan Armstrong & Suzanne Avery & Maureen McHugo & Stephan Heckers & Simon Vandekar - 274-301 On Reverse Shrinkage Effects and Shrinkage Overshoot
by Pascal Jordan - 302-331 Scalable Bayesian Approach for the Dina Q-Matrix Estimation Combining Stochastic Optimization and Variational Inference
by Motonori Oka & Kensuke Okada - 332-356 Identifying and Supporting Academically Low-Performing Schools in a Developing Country: An Application of a Specialized Multilevel IRT Model to PISA-D Assessment Data
by Meredith Langi & Minjeong Jeon
December 2022, Volume 87, Issue 4
- 1195-1213 Item Complexity: A Neglected Psychometric Feature of Test Items?
by Daniel M. Bolt & Xiangyi Liao - 1214-1237 Incomplete Tests of Conditional Association for the Assessment of Model Assumptions
by Rudy Ligtvoet - 1238-1269 Item Response Thresholds Models: A General Class of Models for Varying Types of Items
by Gerhard Tutz - 1270-1289 Analysis of the Weighted Kappa and Its Maximum with Markov Moves
by Fabio Rapallo - 1290-1317 Bayesian Model Assessment for Jointly Modeling Multidimensional Response Data with Application to Computerized Testing
by Fang Liu & Xiaojing Wang & Roeland Hancock & Ming-Hui Chen - 1318-1342 The Reliability Factor: Modeling Individual Reliability with Multiple Items from a Single Assessment
by Stephen R. Martin & Philippe Rast - 1343-1360 Identifiability of Latent Class Models with Covariates
by Jing Ouyang & Gongjun Xu - 1361-1389 Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models
by Shi-Fang Qiu & Man-Lai Tang & Ji-Ran Tao & Ricky S. Wong - 1390-1421 Direct Estimation of Diagnostic Classification Model Attribute Mastery Profiles via a Collapsed Gibbs Sampling Algorithm
by Kazuhiro Yamaguchi & Jonathan Templin - 1422-1438 Procrustes Analysis for High-Dimensional Data
by Angela Andreella & Livio Finos - 1439-1472 On the Information Obtainable from Comparative Judgments
by Paul-Christian Bürkner - 1473-1502 Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework
by Siliang Zhang & Yunxiao Chen - 1503-1528 A Unified Neural Network Framework for Extended Redundancy Analysis
by Ranjith Vijayakumar & Ji Yeh Choi & Eun Hwa Jung - 1529-1547 DIAGNOSTIC Classification Analysis of Problem-Solving Competence using Process Data: An Item Expansion Method
by Peida Zhan & Xin Qiao - 1548-1570 A Latent Variable Mixed-Effects Location Scale Model with an Application to Daily Diary Data
by Shelley A. Blozis - 1571-1574 Book Review Computational Psychometrics: New Methodologies for a New Generation of Digital Learning and Assessment
by Esther Ulitzsch - 1575-1578 Roderick J. Little and Donald B. Rubin: Statistical Analysis with Missing Data
by Gerko Vink
September 2022, Volume 87, Issue 3
- 799-834 The Role of Conditional Likelihoods in Latent Variable Modeling
by Anders Skrondal & Sophia Rabe-Hesketh - 835-867 Modeling Not-Reached Items in Timed Tests: A Response Time Censoring Approach
by Jinxin Guo & Xin Xu & Zhiliang Ying & Susu Zhang - 868-901 Beyond the Mean: A Flexible Framework for Studying Causal Effects Using Linear Models
by Christian Gische & Manuel C. Voelkle - 902-902 Erratum to: Beyond the Mean: A Flexible Framework for Studying Causal Effects Using Linear Models
by Christian Gische & Manuel C. Voelkle - 903-945 Exploratory Restricted Latent Class Models with Monotonicity Requirements under PÒLYA–GAMMA Data Augmentation
by James Joseph Balamuta & Steven Andrew Culpepper - 946-966 Bayesian Mixture Model of Extended Redundancy Analysis
by Minjung Kyung & Ju-Hyun Park & Ji Yeh Choi - 967-991 Factor Analysis Procedures Revisited from the Comprehensive Model with Unique Factors Decomposed into Specific Factors and Errors
by Kohei Adachi - 992-1009 Noncompensatory MIRT For Passage-Based Tests
by Nana Kim & Daniel M. Bolt & James Wollack - 1010-1041 Learning Large Q-Matrix by Restricted Boltzmann Machines
by Chengcheng Li & Chenchen Ma & Gongjun Xu - 1042-1044 Obituary: Bruce McArthur Bloxom 1938–2020
by W. Alan Nicewander & Joseph Lee Rodgers - 1045-1063 Rotation in Correspondence Analysis from the Canonical Correlation Perspective
by Naomichi Makino - 1064-1080 A Note on the Structural Change Test in Highly Parameterized Psychometric Models
by K. B. S. Huth & L. J. Waldorp & J. Luigjes & A. E. Goudriaan & R. J. Holst & M. Marsman - 1081-1102 Estimation of Effect Heterogeneity in Rare Events Meta-Analysis
by Heinz Holling & Katrin Jansen & Walailuck Böhning & Dankmar Böhning & Susan Martin & Patarawan Sangnawakij - 1103-1129 A Censored Mixture Model for Modeling Risk Taking
by Nienke F. S. Dijkstra & Henning Tiemeier & Bernd Figner & Patrick J. F. Groenen - 1130-1145 Frequentist Model Averaging in Structure Equation Model With Ordinal Data
by Shaobo Jin - 1146-1172 Asymptotic Posterior Normality of Multivariate Latent Traits in an IRT Model
by Mia J. K. Kornely & Maria Kateri - 1173-1193 Computation and application of generalized linear mixed model derivatives using lme4
by Ting Wang & Benjamin Graves & Yves Rosseel & Edgar C. Merkle
June 2022, Volume 87, Issue 2
- 1-29 Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data
by Zachary F. Fisher & Younghoon Kim & Barbara L. Fredrickson & Vladas Pipiras - 373-375 Guest Editors’ Introduction to the Special Issue on Forecasting with Intensive Longitudinal Data
by Peter F. Halpin & Kathleen Gates & Siwei Liu - 376-402 Bayesian Forecasting with a Regime-Switching Zero-Inflated Multilevel Poisson Regression Model: An Application to Adolescent Alcohol Use with Spatial Covariates
by Yanling Li & Zita Oravecz & Shuai Zhou & Yosef Bodovski & Ian J. Barnett & Guangqing Chi & Yuan Zhou & Naomi P. Friedman & Scott I. Vrieze & Sy-Miin Chow - 432-476 A Systematic Study into the Factors that Affect the Predictive Accuracy of Multilevel VAR(1) Models
by Ginette Lafit & Kristof Meers & Eva Ceulemans - 477-505 Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data
by Michael D. Hunter & Haya Fatimah & Marina A. Bornovalova - 506-532 A Lasso and a Regression Tree Mixed-Effect Model with Random Effects for the Level, the Residual Variance, and the Autocorrelation
by Steffen Nestler & Sarah Humberg - 533-558 Forecasting Intra-individual Changes of Affective States Taking into Account Inter-individual Differences Using Intensive Longitudinal Data from a University Student Dropout Study in Math
by Augustin Kelava & Pascal Kilian & Judith Glaesser & Samuel Merk & Holger Brandt - 559-592 Control Theory Forecasts of Optimal Training Dosage to Facilitate Children’s Arithmetic Learning in a Digital Educational Application
by Sy-Miin Chow & Jungmin Lee & Abe D. Hofman & Han L. J. Maas & Dennis K. Pearl & Peter C. M. Molenaar - 593-619 A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort Responding in Survey Data
by Esther Ulitzsch & Steffi Pohl & Lale Khorramdel & Ulf Kroehne & Matthias Davier - 620-665 Better Information From Survey Data: Filtering Out State Dependence Using Eye-Tracking Data
by Joachim Büschken & Ulf Böckenholt & Thomas Otter & Daniel Stengel - 666-692 Semiparametric Factor Analysis for Item-Level Response Time Data
by Yang Liu & Weimeng Wang - 693-724 An Empirical Q-Matrix Validation Method for the Polytomous G-DINA Model
by Jimmy de la Torre & Xue-Lan Qiu & Kevin Carl Santos - 725-748 Modeling Conditional Dependence of Response Accuracy and Response Time with the Diffusion Item Response Theory Model
by Inhan Kang & Paul Boeck & Roger Ratcliff - 749-772 Transformer-Based Deep Neural Language Modeling for Construct-Specific Automatic Item Generation
by Björn E. Hommel & Franz-Josef M. Wollang & Veronika Kotova & Hannes Zacher & Stefan C. Schmukle - 773-794 Modeling Faking in the Multidimensional Forced-Choice Format: The Faking Mixture Model
by Susanne Frick - 795-796 Book Review of the Handbook of Graphical Models
by Lourens Waldorp - 797-797 Erratum to: Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data
by Michael D. Hunter & Haya Fatimah & Marina A. Bornovalova - 798-798 Erratum to: A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort Responding in Survey Data
by Esther Ulitzsch & Steffi Pohl & Lale Khorramdel & Ulf Kroehne & Matthias Davier
March 2022, Volume 87, Issue 1
- 1-11 Guest Editors’ Introduction to The Special Issue “Network Psychometrics in Action”: Methodological Innovations Inspired by Empirical Problems
by Maarten Marsman & Mijke Rhemtulla - 12-46 Meta-analytic Gaussian Network Aggregation
by Sacha Epskamp & Adela-Maria Isvoranu & Mike W.-L. Cheung - 47-82 Objective Bayesian Edge Screening and Structure Selection for Ising Networks
by M. Marsman & K. Huth & L. J. Waldorp & I. Ntzoufras - 83-106 Estimating Finite Mixtures of Ordinal Graphical Models
by Kevin H. Lee & Qian Chen & Wayne S. DeSarbo & Lingzhou Xue - 107-132 ConNEcT: A Novel Network Approach for Investigating the Co-occurrence of Binary Psychopathological Symptoms Over Time
by Nadja Bodner & Laura Bringmann & Francis Tuerlinckx & Peter Jonge & Eva Ceulemans - 133-155 Disentangling relationships in symptom networks using matrix permutation methods
by Michael J. Brusco & Douglas Steinley & Ashley L. Watts - 156-187 Modeling Latent Topics in Social Media using Dynamic Exploratory Graph Analysis: The Case of the Right-wing and Left-wing Trolls in the 2016 US Elections
by Hudson Golino & Alexander P. Christensen & Robert Moulder & Seohyun Kim & Steven M. Boker - 188-213 On the Control of Psychological Networks
by Teague R. Henry & Donald J. Robinaugh & Eiko I. Fried - 214-252 Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality
by Oisín Ryan & Ellen L. Hamaker - 253-265 Possible Futures for Network Psychometrics
by Denny Borsboom - 266-288 Multidimensional Item Response Theory in the Style of Collaborative Filtering
by Yoav Bergner & Peter Halpin & Jill-Jênn Vie - 289-309 Second-Order Disjoint Factor Analysis
by Carlo Cavicchia & Maurizio Vichi - 310-343 Robust Machine Learning for Treatment Effects in Multilevel Observational Studies Under Cluster-level Unmeasured Confounding
by Youmi Suk & Hyunseung Kang - 344-368 On the Use of Aggregate Survey Data for Estimating Regional Major Depressive Disorder Prevalence
by Domingo Morales & Joscha Krause & Jan Pablo Burgard - 369-371 Book Review: W. H. FINCH, J. E. Bolin and K. Kelley: Multilevel Modeling Using R
by Nivedita Bhaktha - 372-372 Erratum to: Meta-analytic Gaussian Network Aggregation
by Sacha Epskamp & Adela-Maria Isvoranu & Mike W.-L. Cheung
December 2021, Volume 86, Issue 4
- 843-860 Part II: On the Use, the Misuse, and the Very Limited Usefulness of Cronbach’s Alpha: Discussing Lower Bounds and Correlated Errors
by Klaas Sijtsma & Julius M. Pfadt - 861-868 Alpha, FACTT, and Beyond
by Peter M. Bentler - 869-876 A Test Can Have Multiple Reliabilities
by Jules L. Ellis - 877-886 Neither Cronbach’s Alpha nor McDonald’s Omega: A Commentary on Sijtsma and Pfadt
by Eunseong Cho - 887-892 Rejoinder: The Future of Reliability
by Klaas Sijtsma & Julius M. Pfadt - 893-919 A Guide for Sparse PCA: Model Comparison and Applications
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