#### **Associations between aversive learning processes and transdiagnostic psychiatric symptoms revealed by large-scale phenotyping**
---
Data for this project is provided here, as is the preregistration.
Code for this project is located at https://github.com/tobywise/online-aversive-learning
The data structure is as follows:
```
.
+-- code // available on github
+-- data // the data provided here
| +-- behavioural_measures.csv // Model-free measures for each subject
| +-- full_df.csv // Dataset containing every variable
| +-- modelling_data // Data that has been processed for model fitting
| +-- combined_modelling_data.csv // All subjects data combined
| +-- data_sub000.csv // A single subject's data for model fitting
| +-- ...
| +-- models // Behavioural model objects
| +-- example_model.pklz // An unfitted model
| +-- example_model_fit.pklz // A fitted model
| +-- questionnaire_model // The model used to predict factor scores
| +-- three_factor_classifier.pkl // The SKLearn model
| +-- three_factor_classifier_weights.csv // The model weights
| +-- questionnaire_info.csv // Information about questionnaire items
| +-- qns_full.csv // Sum scores and factor scores
| +-- raw_data // Raw data
+-- avoidance_test_scores.txt // Scores on the control task
| +-- questionnaires // Questionnaire data
| +-- questionnaire_data_sub_000_7112018.csv
| +-- ...
| +-- task // Task data
| +-- game_data_sub_000_7112018.csv
| +-- ...
| +-- raw_qns.csv // Item-level responses for each subject
| +-- reduced_qns.csv // Reduced dataset from Rouault et al (2018)
| +-- regression_models // Regression model objects
| +-- models // Unfitted regression models
| +-- outcome_predictors_covariates.pkl // Model filename
| +-- ...
| +-- results // Fitted models
| +-- outcome_predictors_covariates.pkl // Model filename
| +-- ...
| +-- rouault_et_al // Data from Rouault et al (2018)
| +-- qns.csv // Item responses
| +-- scores.csv // Scores on the three factors
| +-- simulated_data.csv // Simulated data from the winning model
| +-- subject_param_values.csv // Parameter estimates for subjects
+-- notebooks // available on github
```
