eyetrackingR 0.2.2
- Added plotting support for glmmTMB betabinomial models
 
- Fixes compatibility with latest changes to how formulas are
read
 
eyetrackingR 0.2.1
- Added a 
NEWS.md file to track changes to the
package. 
- Fixed issue with breaking change to paired t test
 
eyetrackingR 0.2.0
- Repairing for resubmission to CRAN
 
- Adding compatibility with new versions of dplyr, tidyr and
ggplot2
 
- Inbuilt support for binomial, glmmPQL and glmmTMB models
 
eyetrackingR 0.1.8:
- Fixes a bug in make_onset_data.
 
eyetrackingR 0.1.7:
- Compatible with dplyr > 0.5.0.
 
- Fixes issue described in
https://github.com/jwdink/eyetrackingR/issues/57
 
- Fixes bug in add_aoi when only one AOI is added.
 
eyetrackingR 0.1.6:
- Allows for treatment-coded variables in 
lm or
lmer time-bin or cluster analysis, via the
“treatment_level” argument. 
eyetrackingR 0.1.5:
- Fixes compatibility issue with latest version of 
lme4
package. 
eyetrackingR 0.1.4:
- A variety of important bug-fixes for onset-contingent analysis. The
rest of the package is unchanged.
 
eyetrackingR 0.1.3:
- The 
analyze_time_bins and therefore cluster-analyses
have been re-written internally. Full support for (g)lm, (g)lmer,
wilcox. Support for interaction terms/predictors. Experimental support
for using boot-splines within cluster analysis. 
- 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. To perform this
type of analysis, use test="boot_splines" in
analyze_time_bins. 
- Warnings and errors are now given in the returned dataframe for
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 
- Fixed small bug in make_onset_data
 
- Added 
simulate_eyetrackingr_data function to generate
fake data for simulations. 
eyetrackingR 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