if (!requireNamespace("devtools")) install.packages("devtools")
devtools::install_github("tylin30/NTUCogTask")
library(NTUCogTask)
Note: During the installation, please check the console. It might ask user to update other R packages. Press 'Enter'.
1. cog_tidy
df <- cog_tidy("your_data_path", "Task_Code")
Put all your raw csv(s) in the same folder. cog_tidy will catch all csv(s) from the same task according to your Task_Code. This function will return a dataframe. Row is each subject (participant), Column is all the derived variables(feautures).
2. Create your own pipeline
df <- cog_rbindobs("your_data_path", "Task_Code") %>%
cog_datatype(., "Task_Code") %>%
cog_addnooutlier(., "Task_Code", range='outlier_range') %>%
cog_mutate(., "Task_Code") %>%
cog_unique(., "Task_Code")
You could also create you piple line and decide your inter-person outlier range (sd).
| Task Name | Task Code |
|---|---|
| Simple Reaction Time & Choice Reaction Time | SRT_CRT |
| Delayed Matching to Sample | DMS |
| Memory of Association | MA |
| Memory of Association - Object | MAO |
| Delayed Response Task | DR |
| Spatial Memory Task | SM |
| Running Memory of Symbols | RMS |
| Running Memory of Objects | RMO |
| Running Memory of Locations | RML |
| Rotation Span Task | RS |
| Stop Signal Task | SST |
| Stroop Task | Sp |
| Antisaccade Arrow | As |
| Color Trail Test | CTT |
| Hearts and Flowers | HF |
| Figure Task | Fg |
Enjoy! Comments or feedback are more than welcome.
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