update paper for revision 1

_freeze/figures-box-cases/execute-results/html.json

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+    "markdown": "---\ntitle: \"Code for use cases box 2\"\nauthor: \"Eduard Klapwijk\"\n---\n\n\n\n\n\nLoad libraries to produce figures:\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n#| eval: TRUE\n#| echo: TRUE\n#| message: FALSE\n#| error: FALSE\n#| warning: FALSE\n# load libraries\nlibrary(dplyr)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n\nAttaching package: 'dplyr'\n```\n\n\n:::\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nThe following objects are masked from 'package:stats':\n\n    filter, lag\n```\n\n\n:::\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nThe following objects are masked from 'package:base':\n\n    intersect, setdiff, setequal, union\n```\n\n\n:::\n\n```{.r .cell-code}\n#| eval: TRUE\n#| echo: TRUE\n#| message: FALSE\n#| error: FALSE\n#| warning: FALSE\nlibrary(patchwork)\nlibrary(readr)\nlibrary(neuroUp)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nWarning: package 'neuroUp' was built under R version 4.3.3\n```\n\n\n:::\n:::\n\n\n\n\n\n\nRead data from file and select complete cases: \n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\n# read data & select complete cases only (ignore NA)\ndata_luna <- read_csv(\"data/luna_reward-learn_dev_BOLD.csv\")\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nNew names:\nRows: 275 Columns: 8\n── Column specification\n──────────────────────────────────────────────────────── Delimiter: \",\" chr\n(1): sex dbl (7): ...1, lunaid, visitnum, age, beta, null, posrpe\nℹ Use `spec()` to retrieve the full column specification for this data. ℹ\nSpecify the column types or set `show_col_types = FALSE` to quiet this message.\n• `` -> `...1`\n```\n\n\n:::\n\n```{.r .cell-code .hidden}\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\ndata_luna <- data_luna[complete.cases(data_luna), ]\n```\n:::\n\n\n\n\n\n\nSet seed and create figure with Cohens' d for the box:\n\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\n#| label: fig1-box\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n#| fig-height: 3\n#| fig-width: 9\n# set seed\nset.seed(1234)\n\n# Estimate Cohen's d\nluna_cohen_fig <- estim_diff(data = data_luna,\n                           vars_of_interest = c(\"beta\", \"null\"),\n                           sample_size = 20:232, \n                           k = 100, \n                           name = \"Reward learning caudate\")\n# plot figure 3a\nluna_cohen_fig$fig_cohens_d | luna_cohen_fig$fig_d_nozero \n```\n\n::: {.cell-output-display}\n![](figures-box-cases_files/figure-html/fig1-box-1.png){width=864}\n:::\n:::\n\n\n\n\n\n\nSet seed and create figure with correlations for the box:\n\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\n#| label: fig2-box\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n#| fig-height: 3\n#| fig-width: 9\n# set seed\nset.seed(1234)\n\n# Estimate correlations between posrpe (parametric association between BOLD and reward prediction error) and age\nluna_corr_fig <- estim_corr(data = data_luna,\n                           vars_of_interest = c(\"posrpe\", \"age\"),\n                           sample_size = 20:232, \n                           k = 100, \n                           name = \"Reward learning caudate corr. with age\")\n# plot figure 3a\nluna_corr_fig$fig_corr | luna_corr_fig$fig_corr_nozero\n```\n\n::: {.cell-output-display}\n![](figures-box-cases_files/figure-html/fig2-box-1.png){width=864}\n:::\n:::",
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_freeze/figures-box-cases/execute-results/ipynb.json

@@ -0,0 +1,17 @@
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+    "markdown": "---\ntitle: \"Code for use cases box 2\"\nauthor: \"Eduard Klapwijk\"\n---\n\n\nLoad libraries to produce figures:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n#| eval: TRUE\n#| echo: TRUE\n#| message: FALSE\n#| error: FALSE\n#| warning: FALSE\n# load libraries\nlibrary(dplyr)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n\nAttaching package: 'dplyr'\n```\n\n\n:::\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nThe following objects are masked from 'package:stats':\n\n    filter, lag\n```\n\n\n:::\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nThe following objects are masked from 'package:base':\n\n    intersect, setdiff, setequal, union\n```\n\n\n:::\n\n```{.r .cell-code}\n#| eval: TRUE\n#| echo: TRUE\n#| message: FALSE\n#| error: FALSE\n#| warning: FALSE\nlibrary(patchwork)\nlibrary(readr)\nlibrary(neuroUp)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nWarning: package 'neuroUp' was built under R version 4.3.3\n```\n\n\n:::\n:::\n\n\n\nRead data from file and select complete cases: \n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\n# read data & select complete cases only (ignore NA)\ndata_luna <- read_csv(\"data/luna_reward-learn_dev_BOLD.csv\")\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nNew names:\nRows: 275 Columns: 7\n── Column specification\n──────────────────────────────────────────────────────── Delimiter: \",\" chr\n(1): sex dbl (6): ...1, visitnum, age, beta, null, posrpe\nℹ Use `spec()` to retrieve the full column specification for this data. ℹ\nSpecify the column types or set `show_col_types = FALSE` to quiet this message.\n• `` -> `...1`\n```\n\n\n:::\n\n```{.r .cell-code .hidden}\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\ndata_luna <- data_luna[complete.cases(data_luna), ]\n```\n:::\n\n\n\nSet seed and create figure with Cohens' d for the box:\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\n#| label: fig1-box\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n#| fig-height: 3\n#| fig-width: 9\n# set seed\nset.seed(1234)\n\n# Estimate Cohen's d\nluna_cohen_fig <- estim_diff(data = data_luna,\n                           vars_of_interest = c(\"beta\", \"null\"),\n                           sample_size = 20:232, \n                           k = 100, \n                           name = \"Reward learning caudate\")\n# plot figure 3a\nluna_cohen_fig$fig_cohens_d | luna_cohen_fig$fig_d_nozero \n```\n\n::: {.cell-output-display}\n![](figures-box-cases_files/figure-ipynb/fig1-box-1.png)\n:::\n:::\n\n\n\nSet seed and create figure with correlations for the box:\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\n#| label: fig2-box\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n#| fig-height: 3\n#| fig-width: 10\n# set seed\nset.seed(1234)\n\n# Estimate correlations between posrpe (parametric association between BOLD and reward prediction error) and age\nluna_corr_fig <- estim_corr(data = data_luna,\n                           vars_of_interest = c(\"posrpe\", \"age\"),\n                           sample_size = 20:232, \n                           k = 100, \n                           name = \"Reward learning caudate corr. with age\")\n# plot figure 3a\nluna_corr_fig$fig_corr | luna_corr_fig$fig_corr_nozero\n```\n\n::: {.cell-output-display}\n![](figures-box-cases_files/figure-ipynb/fig2-box-1.png)\n:::\n:::",
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_freeze/figures-box-cases/execute-results/xml.json

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+    "markdown": "---\ntitle: \"Code for use cases box 2\"\nauthor: \"Eduard Klapwijk\"\n---\n\n\n\n\n\nLoad libraries to produce figures:\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n#| eval: TRUE\n#| echo: TRUE\n#| message: FALSE\n#| error: FALSE\n#| warning: FALSE\n\n# load libraries\nlibrary(dplyr)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n\nAttaching package: 'dplyr'\n```\n\n\n:::\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nThe following objects are masked from 'package:stats':\n\n    filter, lag\n```\n\n\n:::\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nThe following objects are masked from 'package:base':\n\n    intersect, setdiff, setequal, union\n```\n\n\n:::\n\n```{.r .cell-code}\n#| eval: TRUE\n#| echo: TRUE\n#| message: FALSE\n#| error: FALSE\n#| warning: FALSE\n\nlibrary(patchwork)\nlibrary(readr)\nlibrary(neuroUp)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nWarning: package 'neuroUp' was built under R version 4.3.3\n```\n\n\n:::\n:::\n\n\n\n\n\n\nRead data from file and select complete cases: \n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\n# read data & select complete cases only (ignore NA)\ndata_luna <- read_csv(\"data/luna_reward-learn_dev_BOLD.csv\")\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\nNew names:\nRows: 275 Columns: 8\n── Column specification\n──────────────────────────────────────────────────────── Delimiter: \",\" chr\n(1): sex dbl (7): ...1, lunaid, visitnum, age, beta, null, posrpe\nℹ Use `spec()` to retrieve the full column specification for this data. ℹ\nSpecify the column types or set `show_col_types = FALSE` to quiet this message.\n• `` -> `...1`\n```\n\n\n:::\n\n```{.r .cell-code .hidden}\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\ndata_luna <- data_luna[complete.cases(data_luna), ]\n```\n:::\n\n\n\n\n\n\nSet seed and create figure with Cohens' d for the box:\n\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\n#| label: fig1-box\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\n# set seed\nset.seed(1234)\n\n# Estimate Cohen's d\nluna_cohen_fig <- estim_diff(data = data_luna,\n                           vars_of_interest = c(\"beta\", \"null\"),\n                           sample_size = 20:232, \n                           k = 100, \n                           name = \"Reward learning caudate\")\n# plot figure 3a\nluna_cohen_fig$fig_cohens_d\n```\n\n::: {.cell-output-display}\n![](figures-box-cases_files/figure-jats/fig1-box-1.png)\n:::\n\n```{.r .cell-code .hidden}\n#| label: fig1-box\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\nluna_cohen_fig$fig_d_nozero\n```\n\n::: {.cell-output-display}\n![](figures-box-cases_files/figure-jats/fig1-box-2.png)\n:::\n:::\n\n\n\n\n\n\nSet seed and create figure with correlations for the box:\n\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\n#| label: fig2-box\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\n# set seed\nset.seed(1234)\n\n# Estimate correlations between posrpe (parametric association between BOLD and reward prediction error) and age\nluna_corr_fig <- estim_corr(data = data_luna,\n                           vars_of_interest = c(\"posrpe\", \"age\"),\n                           sample_size = 20:232, \n                           k = 100, \n                           name = \"Reward learning caudate corr. with age\")\n# plot figure 3a\nluna_corr_fig$fig_corr\n```\n\n::: {.cell-output-display}\n![](figures-box-cases_files/figure-jats/fig2-box-1.png)\n:::\n\n```{.r .cell-code .hidden}\n#| label: fig2-box\n#| eval: TRUE\n#| echo: FALSE\n#| message: FALSE\n#| warning: FALSE\n\nluna_corr_fig$fig_corr_nozero\n```\n\n::: {.cell-output-display}\n![](figures-box-cases_files/figure-jats/fig2-box-2.png)\n:::\n:::",
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