Psychometrika

Papers
(The TQCC of Psychometrika is 5. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-07-01 to 2025-07-01.)
ArticleCitations
Erratum to: Meta-analytic Gaussian Network Aggregation69
Sparse and Simple Structure Estimation via Prenet Penalization42
Commentary: Explore Conditional Dependencies in Item Response Tree Data41
Correction: Book Review of Item Response Theory by Bock and Gibbons40
Noncompensatory MIRT For Passage-Based Tests37
Adventitious Error and Its Implications for Testing Relations Between Variables and for Composite Measurement Outcomes35
The BLIM, the DINA, and their polytomous extensions. Rejoinder to the Commentary by Chiu, Köhn, and Ma33
On the Control of Psychological Networks30
The Sum Score Model: Specifying and Testing Equally Weighted Composites Using Structural Equation Modeling24
Correction: Book Review of Mixture and Hidden Markov Models with R, by Visser & Speekenbrink23
Consistency Theory of General Nonparametric Classification Methods in Cognitive Diagnosis22
Modeling Conditional Dependence of Response Accuracy and Response Time with the Diffusion Item Response Theory Model21
Disentangling Relationships in Symptom Networks Using Matrix Permutation Methods20
A Note on Ising Network Analysis with Missing Data19
Semiparametric Factor Analysis for Item-Level Response Time Data18
Random Effects Multinomial Processing Tree Models: A Maximum Likelihood Approach18
Linking Scores with Patient-Reported Health Outcome Instruments: A Validation Study and Comparison of Three Linking Methods17
On the Use of Aggregate Survey Data for Estimating Regional Major Depressive Disorder Prevalence17
Comparing Bayesian Variable Selection to Lasso Approaches for Applications in Psychology17
Reliability Theory for Measurements with Variable Test Length, Illustrated with ERN and Pe Collected in the Flanker Task16
Rotating Factors to Simplify Their Structural Paths16
Going Deep in Diagnostic Modeling: Deep Cognitive Diagnostic Models (DeepCDMs)16
Corrigenda to Satorra, A., and Bentler, P.M. (2010), “Ensuring Positiveness of the Scaled Difference Chi-Square Test Statistic,” Psychometrika, 75, pp. 243–24815
PKLM: A Flexible MCAR Test Using Classification13
Infinitesimal Jackknife Estimates of Standard Errors for Rotated Estimates of Redundancy Analysis: Applications to Two Real Examples13
SRMR for Models with Covariates12
Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data12
Assessing the Accuracy of Errors of Measurement. Implications for Assessing Reliable Change in Clinical settings12
Multifaceted Neuroimaging Data Integration via Analysis of Subspaces12
The InterModel Vigorish as a Lens for Understanding (and Quantifying) the Value of Item Response Models for Dichotomously Coded Items12
Erratum to: A Modeling Framework to Examine Psychological Processes Underlying Ordinal Responses and Response Times of Psychometric Data11
Robust Machine Learning for Treatment Effects in Multilevel Observational Studies Under Cluster-level Unmeasured Confounding11
The Bradley–Terry Regression Trunk approach for Modeling Preference Data with Small Trees11
What Can We Learn from a Semiparametric Factor Analysis of Item Responses and Response Time? An Illustration with the PISA 2015 Data11
Analysis of the Weighted Kappa and Its Maximum with Markov Moves11
Psychometric Society Meeting of the Members University of Bologna, Bologna, Italy, July 15, 202210
Accurate Confidence and Bayesian Interval Estimation for Non-centrality Parameters and Effect Size Indices10
Bayesian Analysis of the Ordinal Markov Random Field10
Bayesian Semiparametric Longitudinal Inverse-Probit Mixed Models for Category Learning10
Jörg Henseler (2021). Composite-Based Structural Equation Modeling: Analyzing Latent and Emergent Variables10
Erratum to: Within-Person Variability Score-Based Causal Inference: A Two-Step Estimation for Joint Effects of Time-Varying Treatments9
Identifiability of Hidden Markov Models for Learning Trajectories in Cognitive Diagnosis9
Sociocognitive and Argumentation Perspectives on Psychometric Modeling in Educational Assessment9
Second-Order Disjoint Factor Analysis9
A Modeling Framework to Examine Psychological Processes Underlying Ordinal Responses and Response Times of Psychometric Data9
Bayesian Model Assessment for Jointly Modeling Multidimensional Response Data with Application to Computerized Testing9
A Systematic Study into the Factors that Affect the Predictive Accuracy of Multilevel VAR(1) Models8
Nodal Heterogeneity can Induce Ghost Triadic Effects in Relational Event Models8
Learning Large Q-Matrix by Restricted Boltzmann Machines8
A Note on Weaker Conditions for Identifying Restricted Latent Class Models for Binary Responses8
A Bayesian Generalized Explanatory Item Response Model to Account for Learning During the Test8
A Review of “The Creation of Scientific Psychology” by David J. Murray & Stephen W. Link8
Erratum to: Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data7
Identifying and Supporting Academically Low-Performing Schools in a Developing Country: An Application of a Specialized Multilevel IRT Model to PISA-D Assessment Data7
Remarks from the Editor-in-Chief7
Better Information From Survey Data: Filtering Out State Dependence Using Eye-Tracking Data7
Multinomial Logistic Factor Regression for Multi-source Functional Block-wise Missing Data7
Causal Structural Modeling of Survey Questionnaires via a Bootstrapped Ordinal Bayesian Network Approach7
Neither Cronbach’s Alpha nor McDonald’s Omega: A Commentary on Sijtsma and Pfadt7
Show Me Some ID: A Universal Identification Program for Structural Equation Models6
Modeling Eye Movements During Decision Making: A Review6
Random Item Response Data Generation Using a Limited-Information Approach: Applications to Assessing Model Complexity6
Exploratory Restricted Latent Class Models with Monotonicity Requirements under Pòlya—gamma Data Augmentation6
Efficient and Effective Variational Bayesian Inference Method for Log-Linear Cognitive Diagnostic Model6
Joint Latent Space Model for Social Networks with Multivariate Attributes6
Performance of the Longitudinal Actor–Partner Interdependence Model in Case of Large Amounts of Missing Values: Challenges and Possible Alternatives6
Examining Differential Item Functioning from a Multidimensional IRT Perspective6
The Crosswise Model for Surveys on Sensitive Topics: A General Framework for Item Selection and Statistical Analysis5
Comparing Functional Trend and Learning among Groups in Intensive Binary Longitudinal Eye-Tracking Data using By-Variable Smooth Functions of GAMM5
Identification of Factor Scores by Regression with External Variables in Exploratory Factor Analysis5
Computational Psychometrics: New Methodologies for a New Generation of Digital Learning and Assessment5
Testing of Reverse Causality Using Semi-Supervised Machine Learning5
Scalable Bayesian Approach for the Dina Q-Matrix Estimation Combining Stochastic Optimization and Variational Inference5
Remarks from the New Editor-in-Chief5
Correction: A Diagnostic Facet Status Model (DFSM) for Extracting Instructionally Useful Information from Diagnostic Assessment5
A Two-Step Estimator for Multilevel Latent Class Analysis with Covariates5
Differential Item Functioning Analyses of the Patient-Reported Outcomes Measurement Information System (PROMIS®) Measures: Methods, Challenges, Advances, and Future Directions5
Longitudinal Analysis of Patient-Reported Outcomes in Clinical Trials: Applications of Multilevel and Multidimensional Item Response Theory5
As reported by P. Martinková, & A. Hladká, ((Computational Aspects of Psychometric Methods: With R. Boca Raton, CRC Press, FL, 2023). Computational Aspects of Psychometric Methods: With R.. Boca R5
Exploratory Procedure for Component-Based Structural Equation Modeling for Simple Structure by Simultaneous Rotation5
The Generalized Cognitive Diagnosis Model Framework for Polytomous Attributes5
0.23140597343445