This is the page for the project **No effect of different types of media on well-being**. Link to the preprint: <> Link to rendered analysis report: <https://digital-wellbeing.github.io/cultural-consumption/> ## Components The `Github` component holds the source code, hosted on Github. The code details all steps from raw data to final analysis. The `data` component holds the raw data. These data were processed before uploading to remove other variables that we aren't allowed to share. You can see those processing steps in the processing section of the rendered [analysis report](https://digital-wellbeing.github.io/cultural-consumption/). For an explanation of the data structure and processing, see the report and the `codebook.xlsx` file in the `data` component. The component contains the following objects: - `wave1.csv`: The (preprocessed) raw data for the first wave. - `waves_2_to_6.csv`: The (preprocessed) raw data for waves two through six. - `example_id.csv`: Merely a (made up) example of how the ID variables are used across all waves. See [this section](https://digital-wellbeing.github.io/cultural-consumption/data-processing.html#read-waves-2-6) for an explanation. This data file wasn't used in the analysis. - `processed_data.rds`: The final data set after raw data processing, on which summary stats and analyses are based. The file gets written at the end of [this section](https://digital-wellbeing.github.io/cultural-consumption/analysis.html#data-preparation). If you just want to do your own checks/analyses, it's probably easiest to load the `processed_data.rds` file straight into R. Another component holds brms model objects (`models`). We ran 28 total models, and each one is about one GB large. We only ran those models once and stored them as external files. You’ll see in the analysis section that we downloaded those models and loaded them into R for model inspection and diagnostics. The `figures` component holds the figures we report in the paper. You can reproduce them with the source code. The `materials` component holds the questionnaires used at each wave for all items. ## How to reproduce processing and analyses All processing, analysis, description, and modelling steps organized into separate [R Markdown](https://rmarkdown.rstudio.com/) files. The source code is on GitHub: <https://github.com/digital-wellbeing/cultural-consumption>. Those source files are organized as an R [bookdown](https://bookdown.org/yihui/bookdown/) project. That project was knitted to an online book, whose results are at <https://digital-wellbeing.github.io/cultural-consumption/>. The project used a local library to make sure package versions are stable for anyone who wants reproduce the analysis. We used [renv](https://rstudio.github.io/renv/articles/renv.html) for that. If you want to reproduce the entire book, it's best to download the entire R project from the Github repo: <https://github.com/digital-wellbeing/cultural-consumption>. As a first step, open the project and make sure you have all packages installed in the right version by calling `renv::restore()`. For an explanation of `renv`, see here: <https://rstudio.github.io/renv/articles/renv.html>. That'll install all packages in the version that are saved in the lockfile of the project (`renv.lock`). For that, it's best if you are on R 4.0.1 or higher. Once all packages are installed, you should be able to build the book and reproduce all files that are displayed at <https://digital-wellbeing.github.io/cultural-consumption/>. To do that, either run `bookdown::render_book("index.Rmd")` or click the "Build Book" button under the `Build` tab in RStudio. Each `.Rmd` source file will be knitted and stored in a `docs` folder. You can double click on `docs/index.html` and view the results in a web browser. Note that before running the entire book, that you either need to set chunk options or download the data and the models (see below). You'll see that the source code doesn't run the models anymore. In total, running each chunk would take the good part of a week on a modern 4-core laptop. I ran them once and then stored them on the OSF. In the source code, you can download those files (note: downloading the models will take some time, they're 34GB in total). To download the models, make sure the chunk option for chunk `download-models` in the analysis chapter is set to `eval=TRUE`. If you want to run the models rather than downloading them and loading them into R, you can either set chunk options for each model to `eval=TRUE` or run each of the five `.Rmd` files separately. I set this book up so that it runs in one go, meaning you need to run the source files in their order, and can't run source files independently. The same goes for the data: You'll need to set the chunk `download-data` to `eval=TRUE`. If that doesn't work (but it should, even with an anonymized link), you'll need to manually download the data files from the OSF into a `data/` folder in the main directory of the project.