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Releases: jwdink/eyetrackingR

Version 0.1.4 (CRAN Release)

26 Jan 21:30
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This release includes a variety of important bug-fixes for onset-contingent analysis. The rest of the package is unchanged.

Version 0.1.3 (CRAN Release)

09 Jan 15:20
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This is a backwards-compatible update, so we recommend upgrading. As always, please email any problems to jacobwdink@gmail.com.

Changes in 0.1.3:

  • The analyze_time_bins and therefore cluster-analyses have been improved: full support for (g)lm, (g)lmer, wilcox. Support for interaction terms/predictors. Experimental support for using boot-splines within cluster analysis.
  • Warnings and errors are now given in the returned dataframe for analyze_time_bins.
  • P-value adjustment for multiple comparisons is now supported in analyze_time_bins
  • Easier to use AOI as a predictor/covariate in analyze_time_bins and cluster analyses
  • The functions make_boot_splines_data and analyze_boot_splines are now deprecated (with a warning). To perform this type of analysis, use test="boot_splines" in analyze_time_bins.
  • Fixed plotting methods for time-cluster data
  • The analyze_time_clusters function now checks that the extra arguments passed to it are the same as the arguments passed to make_time_cluster_data
  • Fixed small bug in make_onset_data when creating dataframe with NA values in 1+ bins
  • Added simulate_eyetrackingr_data function to generate fake data for simulations.

Version 0.1.1 (CRAN Release)

17 Nov 20:41
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This release includes major bug-fixes from the last release to CRAN. If you haven't updated from github in the past week or so, you should update to this release immediately.

You can update with install.packages('eyetrackingR')

Changes in 0.1.1:

  • Important bug-fix in clean_by_trackloss. Previously did not work for certain column names.
  • Important bug-fix in make_eyetrackingr_data. Previously did not work correctly with treat_non_aoi_as_missing = TRUE.
  • Important bug-fix in analyze_time_clusters: previously did not compute permutation-distribution correctly.
  • Can specify any arbitrary dependent-variable for make_time_window_data or make_time_sequence_data to summarize. This DV can then be plotted and used in downstream functions (like analyze_time_bins or make_time_cluster_data)
  • Bug-fix in error/warning reporting in analyze_time_bins and functions that call this (e.g make_time_cluster_data).
  • Compatible with ggplot2 2.0
  • Small bug fix in cluster analyses functions related to the dots (...) arguments
  • Added support for parallelization in analyze_time_clusters, allowing the user to take advantage of multiple cores to speed up this relatively slow function.
  • Added get_time_clusters for getting information about clusters in a data.frame (rather than a printed summary-- better for programming).
  • Small bug-fixes in make-boot-splines.
  • Changed how cluster-summaries are displayed

Version 0.1.0.9002 (Patched Cluster-Analysis)

15 Nov 05:30
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Changes:

  • Important bug-fix in analyze_time_clusters: previously did not compute permutation-distribution correctly.
  • Compatible with ggplot2 2.0
  • Small bug fix in cluster analyses functions related to the dots (...) arguments
  • Added support for parallelization in analyze_time_clusters, allowing the user to take advantage of multiple cores to speed up this relatively slow function.
  • Added get_time_clusters for getting information about clusters in a data.frame (rather than a printed summary-- better for programming).
  • Small bug-fixes in make-boot-splines.
  • Changed how cluster-summaries are displayed

Patches to CRAN release

11 Nov 15:27
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This release adds some important bug-fixes, and support for new dependent-variables.

You should update to this release from the CRAN release, as there should be no problems with backwards compatibility, and it fixes some major bugs.

We'll be adding this version to CRAN soon.

Changes:

  • Important bug-fix in clean_by_trackloss. Previously did not work for certain column names.
  • Important bug-fix in make_eyetrackingr_data. Previously did not work correctly with treat_non_aoi_as_missing = TRUE.
  • Can specify any arbitrary dependent-variable for make_time_window_data or make_time_sequence_data to summarize. This DV can then be plotted and used in downstream functions (like analyze_time_bins or make_time_cluster_data)
  • Bug-fix in error/warning reporting in analyze_time_bins and functions that call this (e.g make_time_cluster_data).

Initial CRAN Release

11 Nov 15:30
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This is the initial release that was submitted to CRAN.