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The mtqgam package was created to simplify working with mouse-tracking data in QGAMs.

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mtqgam

mtqgam offers functions

  • to extract t values, and x and y coordinates of time-normalized mouse-tracking data
  • to conveniently plot parametric terms, smooth terms, and their interactions in QGAMs
  • to create multi-panel plots of parametric and smooth terms of QGAMs
  • to summarize mqgam objects

Check out the references for more detailed information.

What's New

Please check the changelog for information on version history and function updates.

How to Install

The preferred way to install this package is through devtools:

# if devtools has not been installed yet, please install it first
# install.packages("devtools")

# then, install the mtqgam package
devtools::install_github("dosc91/mtqgam", upgrade_dependencies = FALSE)

You will be asked to update dependencies during installation; usually, updates can be skipped. Once installation was successfull, there will be a warning message on the usage of ...; this can be ignored.

Please note that in order to use the plot functions of mtqgam, ggplot2 is loaded automatically. Prior version 0.3, ggplot2 had to be loaded via library(ggplot2) first.

References

Please cite the package as follows:

Schmitz, Dominic. (2022). mtqgam: Mouse-Tracking Data in QGAMs. R package version 0.5.3. URL: https://github.com/dosc91/mtqgam

The following packages are made use of in the mtqgam package:

Csárdi, G. (2021). cli: Helpers for Developing Command Line Interfaces. R package version 3.0.0. URL: https://CRAN.R-project.org/package=cli

Fasiolo M., Goude Y., Nedellec R., & Wood S. N. (2017). Fast calibrated additive quantile regression. URL: https://arxiv.org/abs/1707.03307

Hester, J. (2020). glue: Interpreted String Literals. R package version 1.4.1. https://CRAN.R-project.org/package=glue

Kieslich, P. J., Henninger, F., Wulff, D. U., Haslbeck, J. M. B., & Schulte-Mecklenbeck, M. (2019). Mouse-tracking: A practical guide to implementation and analysis. In M. Schulte-Mecklenbeck, A. Kühberger, & J. G. Johnson (Eds.), A Handbook of Process Tracing Methods (pp. 111-130). New York, NY: Routledge.

van Rij J, Wieling M, Baayen R, & van Rijn H (2020). itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs. R package version 2.4.

Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York.

Wickham, H. (2020). tidyr: Tidy Messy Data. R package version 1.1.2. https://CRAN.R-project.org/package=tidyr

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The mtqgam package was created to simplify working with mouse-tracking data in QGAMs.

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LICENSE.md

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