An Extended Active Learning Approach to Multiverse Analysis: Predictions of Latent Variables from Graph Theory Measures of the Human Connectome and Their Direct Replication

Keyphrases

• Latent Variables 100%
• Graph Theory 100%
• Functional Connectome 100%
• Multiverse Analysis 100%
• Forking Paths 100%
• Active Learning Approach 100%
• Direct Replication 100%
• Active Learning 50%
• Multiverse 50%
• Prediction Accuracy 25%
• Complex Data 25%
• Graph Theoretical 25%
• Data Preprocessing 25%
• Data Combination 25%
• Performance Prediction 25%
• Multidimensional Data 25%
• Common Cause 25%
• Noisy Data 25%
• Number of Degrees of Freedom 25%
• GitHub Repositories 25%
• Theoretical Parameters 25%
• Network Properties 25%
• Low-dimensional Space 25%
• Neurocognitive 25%
• Functional Brain Networks 25%
• Replication Crisis 25%
• Shiny App 25%
• ABCD Study 25%
• Computational Psychiatry 25%
• Imaging Neuroscience 25%
• Crisis in Science 25%
• Extended Method 25%
• Behavioral Symptoms 25%
• Latent Trait 25%
• Methodological Decisions 25%
• General Cognition 25%

Neuroscience

• Neuroscience 100%
• Brain Network 100%
• Computational Psychiatry 100%

Psychology

• Active Learning Approach 100%
• Neurobiology 33%
• Replication Crisis 33%
• Latent Trait 33%