Psychological Methods

Papers
(The H4-Index of Psychological Methods is 30. 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 2020-11-01 to 2024-11-01.)
ArticleCitations
Comparing network structures on three aspects: A permutation test.332
Effect size guidelines for cross-lagged effects.193
Evaluating meta-analytic methods to detect selective reporting in the presence of dependent effect sizes.166
A comparison of full information maximum likelihood and multiple imputation in structural equation modeling with missing data.153
Reporting standards for psychological network analyses in cross-sectional data.140
Dynamic fit index cutoffs for confirmatory factor analysis models.129
Power contours: Optimising sample size and precision in experimental psychology and human neuroscience.118
Which estimation method to choose in network psychometrics? Deriving guidelines for applied researchers.102
Clarifying causal mediation analysis for the applied researcher: Defining effects based on what we want to learn.101
Toward a principled Bayesian workflow in cognitive science.83
A tutorial on assessing statistical power and determining sample size for structural equation models.68
Composite reliability of multilevel data: It’s about observed scores and construct meanings.61
A tutorial on bayesian networks for psychopathology researchers.60
Ten frequently asked questions about latent transition analysis.59
Closed- and open-vocabulary approaches to text analysis: A review, quantitative comparison, and recommendations.57
Centering categorical predictors in multilevel models: Best practices and interpretation.49
What is a Bayes factor?48
Improving the assessment of measurement invariance: Using regularization to select anchor items and identify differential item functioning.46
Robust Bayesian meta-analysis: Addressing publication bias with model-averaging.46
Modeling psychopathology: From data models to formal theories.44
Measurement invariance testing using confirmatory factor analysis and alignment optimization: A tutorial for transparent analysis planning and reporting.42
Summary-statistics-based power analysis: A new and practical method to determine sample size for mixed-effects modeling.40
Do simple slopes follow-up tests lead us astray? Advancements in the visualization and reporting of interactions.39
An approach to structural equation modeling with both factors and components: Integrated generalized structured component analysis.39
The microrandomized trial for developing digital interventions: Experimental design and data analysis considerations.37
Conducting a meta-analysis in the age of open science: Tools, tips, and practical recommendations.37
Using anticlustering to partition data sets into equivalent parts.37
Semantic network analysis (SemNA): A tutorial on preprocessing, estimating, and analyzing semantic networks.33
Workflow techniques for the robust use of bayes factors.31
Partitioning variation in multilevel models for count data.31
A structural after measurement approach to structural equation modeling.30
Investigating the feasibility of idiographic network models.30
One model to rule them all? Using machine learning algorithms to determine the number of factors in exploratory factor analysis.30
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