# ssMousetrack: Analysing computerized tracking data via Bayesian state-space models in {R}

## TL;DR

ssMousetrack is an R package that employs Bayesian state-space models to analyze computerized tracking data, offering researchers a comprehensive tool for data preparation, modeling, and diagnostics in behavioral studies.

## Contribution

The paper introduces ssMousetrack, a novel R package that applies Bayesian state-space modeling to computerized tracking data, facilitating dynamic response process analysis.

## Key findings

- Effective data modeling and analysis demonstrated in case study
- Provides diagnostic tools for model assessment
- Enhances understanding of response dynamics in behavioral research

## Abstract

Recent technological advances have provided new settings to enhance individual-based data collection and computerized-tracking data have became common in many behavioral and social research. By adopting instantaneous tracking devices such as computer-mouse, wii, and joysticks, such data provide new insights for analysing the dynamic unfolding of response process. ssMousetrack is a R package for modeling and analysing computerized-tracking data by means of a Bayesian state-space approach. The package provides a set of functions to prepare data, fit the model, and assess results via simple diagnostic checks. This paper describes the package and illustrates how it can be used to model and analyse computerized-tracking data. A case study is also included to show the use of the package in empirical case studies.