Read in data.

statistical_analysis/scale_reliability.rmd

@@ -1,22 +1,49 @@
 ---
-title: "R Notebook"
+title: "Reliability of SAM threat and challenge and COPE"
 output: html_notebook
 ---
 
-The [R plugin](https://www.jetbrains.com/help/pycharm/r-plugin-support.html) for IntelliJ-based IDEs provides
-handy capabilities to work with the [R Markdown](https://www.jetbrains.com/help/pycharm/r-markdown.html) files.
-To [add](https://www.jetbrains.com/help/pycharm/r-markdown.html#add-code-chunk) a new R chunk,
-position the caret at any line or the code chunk, then click "+".
 
-The code chunk appears:
-```{r}
+```{r libraries, message=FALSE, warning=FALSE, include=FALSE, cache=FALSE}
+library(conflicted)
+library(here)
+library(tidyverse)
+library(magrittr)
+library(kableExtra)
+
+conflicts_prefer(
+    readr::col_factor,
+    purrr::discard,
+    dplyr::filter,
+    dplyr::lag,
+    purrr::set_names,
+    tidyr::extract,
+    kableExtra::group_rows
+)
 ```
 
-Type any R code in the chunk, for example:
-```{r}
-mycars <- within(mtcars, { cyl <- ordered(cyl) })
-mycars
+```{r style, include=FALSE, cache=FALSE}
+styler::style_file(
+    here("statistical_analysis", "scale_reliability.Rmd"),
+    scope = "tokens",
+    indent_by = 4L
+)
 ```
 
-Now, click the **Run** button on the chunk toolbar to [execute](https://www.jetbrains.com/help/pycharm/r-markdown.html#run-r-code) the chunk code. The result should be placed under the chunk.
-Click the **Knit and Open Document** to build and preview an output.
+
+```{r read_data}
+COL_TYPES <- cols(
+    .default = col_double(),
+    participant_id = col_factor(),
+    username = col_factor(),
+    device_id = col_factor(),
+    esm_trigger = col_factor(),
+    double_esm_user_answer_timestamp = col_double(),
+    datetime_lj = col_datetime(format = ""),
+    date_lj = col_date(format = ""),
+    time = col_factor(),
+    esm_user_answer = col_factor()
+)
+df_SAM <- read_csv(here("data", "raw", "df_esm_SAM_threat_challenge.csv"), col_types = COL_TYPES)
+df_COPE <- read_csv(here("data", "raw", "df_esm_COPE.csv"), col_types = COL_TYPES)
+```