https://github.com/codecheckers/sample-size-codecheck

Codecheck corresponding to issue #100, https://github.com/codecheckers/register/issues/100

https://github.com/codecheckers/sample-size-codecheck

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Codecheck corresponding to issue #100, https://github.com/codecheckers/register/issues/100

https://github.com/codecheckers/sample-size-codecheck/blob/main/

# Sample size estimation for task-related functional MRI studies using Bayesian updating

## Code Checking materials

This repository contains the code and instructions for reproducing the following paper:

Klapwijk, E. T., Jongerling, J., Hoijtink, H., & Crone, E. (2024, July 9). Sample size estimation for task-related functional MRI studies using Bayesian updating. 

## Contents

### Main files

The following two [Quarto](https://quarto.org/) Markdown files (`*.qmd`) are the main files containing the code to reproduce the figures and tables:

-   `figures-cohens_d.qmd` (Figure 1 and 2; Table 2)

-   `figures-correlation.qmd` (Figure 3 and 4; Table 2)

### HTML output

These files are rendered as hmtl pages containing all the individual and collected figures:

-   `figures-cohens_d.html`

-   `figures-correlation.html`

### PNG output

The individual .png files are saved in the following directories:

-   `figures-cohens_d_files/figure-html/`

-   `figures-correlation_files/figure-html/`

## Workflow

The analysis for this paper is implemented in the statistical programming language R. To reproduce the results, you will need installed on your computer the [R software](https://cloud.r-project.org/) itself, optionally (but recommended) [RStudio Desktop](https://posit.co/download/rstudio-desktop/), and [Quarto](https://quarto.org/docs/get-started/).

-   You can download this repository as a zip from from this URL: [main.zip](https://github.com/eduardklap/sample-size-codecheck/archive/refs/heads/main.zip)

-   Or you can clone the repository: `git clone git@github.com:eduardklap/sample-size-codecheck.git`

Then:

-   open the `sample-size-codecheck.Rproj` file in RStudio

-   make sure you have the following packages installed:

    -   [`neuroUp`](https://eduardklap.github.io/neuroUp/), you can run `install.packages("neuroUp")` to install it

        -   this is the main package that was specifically developed for this paper

        -   It also contains the 4 datasets used in the paper: You can run `?feedback` , `?gambling` , `?self_eval` , and `?vicar_char` for more information about the data source

    -   [`patchwork`](https://patchwork.data-imaginist.com/), you can run `install.packages("patchwork")` to install it

        -   this package is used to combine the different plots into the figures as presented in the manuscript

-   Finally, open `figures-cohens_d.qmd` and click **Render** to produce the html file and the individual png files (`figures-cohens_d_files/`), or run `quarto render figures-cohens_d.qmd` in the RStudio Terminal.

    -   **Runtime note**: due to the number of permutations (1000) used in the paper, it might take some time to run the whole document (e.g., on a 4 core 32GB CPU virtual machine, it took 2.5 hrs to render `figures-cohens_d.qmd` and 1 hr to render `figures-correlations.qmd`)

-   Do the same for the correlational analysis: open `figures-correlations.qmd` and click **Render** to produce the html file and the individual png files (`figures-correlations_files/`), or run `quarto render figures-correlations.qmd` in the RStudio Terminal.

-   If you do not have Quarto (or RStudio) installed, another (much less convenient) way to reproduce the analyses would be to run the individual code blocks as displayed in the .qmd (and .html) files subsequently in R.

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