'Careless_modified_scripts' includes:
- original code of contributors Ulrich Schroeders and Timo Gnambs (https://osf.io/mct37/) with some modifications.
- Study: Schroeders U, Schmidt C, Gnambs T. Detecting Careless Responding in Survey Data Using Stochastic Gradient Boosting. Educ Psychol Meas 2022; 82: 29–56.
'Careless_Shap_results_graphs' includes:
- datasets:
- train and test sets (all_extracted, seed 1) [.rds files]
- train and test sets (all, seed 1) [.rds files]
- figures:
- all figures that are included in the manuscript
- model:
- pre-trained model (all_extracted, seed 1) [.rds files]
- pre-trained model (all, seed 1) [.rds files]
- results:
- Variables' Contributions for all Careless and Regular respondents (all_extracted) [.csv file]
- scripts:
- generate figures and results [.r files]
'Careless_Shap_RShinyApp' includes:
- Dalex explainers:
- Regular and Careless explainers [.rds files]
- datasets:
- train and test set (all_extracted, seed 1) [.rds file]
- model:
- pretrained GBM model (seed 1) [.rds file]
- other:
- Descriptions of methods and questions [.csv files]
- Supplementary Web Application [script app.R]