NEWS.md
Updated: 1 February, 2023
Minor update
Added support for reading span tasks (e.g, Standard or Oswald)
Added support and functions for toolbox 2.0 tasks (publication forthcoming)
Updated: 12 August, 2022
Major update
Added new functions to assist in processing and cleaning data.
center() to calculate z-score or centered scores for a list of variables
composiste() to calculate a composite score for a group of variables. Composites can be calculated using different methods:
replace_outliers() to replace outlier values with missing or some other method (e.g., mean). There is an option to save the outlier values to a data file to store a log of what rows in the data were removed.
remove_missing() to remove subjects with too much missing data on a group of tasks for any given construct.
Added some extra columns to the output of raw_symspan(), raw_rotspan(), and raw_ospan()
MemoryTargets and Recalled to more easily see and analyze the sequence of memory items and the sequence of recalled items on each trial.
EditDistance.unit and EditDistance.load calculate the trial scores based on the edit distance scoring method. See Gonthier et al. (2022).
Got rid of Recall.correct as it was redundant with Partial.load
Added extra columns to the output of score_symspan(), score_rotspan(), and score_ospan()
Gonthier, C. (2022). An easy way to improve scoring of memory span tasks: The edit distance, beyond “correct recall in the correct serial position.” Behavior Research Methods, 16. https://doi.org/10.3758/s13428-022-01908-2
Updated: 5 May, 2022
Minor update only
Updated score_visualarrays(). Added a taskname = argument for different types of visual arrays tasks
Updated: 12 May, 2021
Minor update only
Adds PartialScore and AbsoluteScore variables to score_ functions output for complex-span tasks
Updated: 24 February, 2021
This is a major update and will break previous versions (my apologies)
This is the first major release and will hopefully be stable after this
The raw_ functions work pretty much the same and might not break from previous versions
The score_ functions will break and have been made to be more flexible, such as using them to calculate alternate span scores and reliability estimates.
The score_ functions need to be used with dplyr::group_by() and so can be thought of as similar to dplyr::summarise()
See new Vignettes explaining this all: