# Cognate beginnings to bilingual lexical acquisition
| Link | Contents |
|------------------------------------------------------------------|----------------------------------------------------------------|
| [Website](https://gongcastro.github.io/cognate-beginnings) | Instructions for reproducibility, data dictionaries, lab notes |
| [PsyArxiv](https://psyarxiv.com/dxsmz/) | Preprint and figures |
| [GitHub](https://github.com/gongcastro/cognate-beginnings) | Code, preprint and figures |
| [OSF](https://osf.io/hy984/) | Code, preprint, and results (model outputs) |
| [Docker](https://hub.docker.com/r/gongcastro/cognate-beginnings) | Docker image with reproducible RStudio session |
# Repository structure and files 📂
This repository is organised as follows:
- **data**: processed data in CSV format
- [items.csv](data/items.csv): information about words included in
the analyses
- [participants.csv](data/participants.csv): information about
participants
- [responses.csv](data/responses.csv): participant responses to
the items. The model was fit on this dataset.
- **data-raw**: raw data from the [Barcelona Vocabulary Questionnaire,
BVQ](https://gongcastro.github.io/bvq). This is a RDS file
containing a list of data frames with all the information necessary
to generate the datasets in the data/ directory.
- **docs**: source code to generate the documentation site of the
project
([cognate-beginnings](https://gongcastro.github.com/cognate-beginnings)).
- **manuscript**: Quarto document with the source code of the
manuscript and appendix
- **R**: R functions used in the targets to process and analyse the
data.
- [items.R](R/items.R): to generate `items.csv`
- [models.R](R/items.R): to fit the Bayesian model and extract
posterior draws
- [participants.R](R/participants.R): to generate
`participants.csv`
- [predictions.R](R/predictions.R): to generate posterior
predictions from the model
- [utils.R](R/utils.R): helper functions and wrappers used across
the project
- **renv**: internal settings to ensure reproducibility of the
computing environment.
- **results**: model outputs. You will need to run the code to
generate the files that will be contained in this directoty.
- fits: RDS files with the brmsfit of the Bayesian models
- posterior: CSV files with the posterior draws of the
population-level and group-level coefficients
- predictions: CSV files with the posterior predictions
- **src**: R functions to make programming tasks easier, not needed to
reproduce the project.
- **Stan**: Stan code of the models, as generated by
`brms::stancode()`.
- **tests**: testthat scripts used to unit test the functions used
across the project.
