rtmpt

rtmpt fits response-time extended multinomial processing tree (RT-MPT) models in R to estimate process-completion times within multinomial processing tree (MPT) frameworks and characterize temporal dynamics of cognitive processes.

Key Features:

• R implementation: Provided as an R package for fitting RT-MPT models.
• RT-MPT modeling: Implements response-time extended multinomial processing tree (RT-MPT) models that incorporate estimates of process-completion times into multinomial processing tree (MPT) frameworks.
• Syntax compatibility: Supports two established MPT syntaxes.
• Suppression of process-completion times: Allows suppression of process-completion times for specific outcomes.
• Constant process probabilities: Allows holding certain process probabilities constant during model fitting.
• Adjustable priors: Enables modification of prior parameters for Bayesian estimation.
• Computational backend: Uses an altered version of original C++ code for Markov Chain Monte Carlo (MCMC) sampling.
• Hierarchical modeling: Implements a hierarchical Bayesian framework for parameter estimation.

Scientific Applications:

• Cognitive psychology and neuroscience: Applied to investigate the timing and organization of cognitive processes in cognitive psychology and neuroscience research.
• Reaction-time and decision-making analysis: Used to analyze reaction times and decision-making processes by estimating process-completion times.
• Memory retrieval and time-sensitive phenomena: Applied to study memory retrieval and other time-sensitive cognitive phenomena.

Methodology:

Hierarchical Bayesian inference using Markov Chain Monte Carlo (MCMC) sampling implemented via an altered version of original C++ code, validated by simulation-based calibration.