Brad's review of data_02_consent_import.qmd

Part of #33
- Use the `here` package to facilitate file import and export.
- Made headings more consistent.
- Checked for overlap with qaqc/check_consenting_participants.qmd. There was nothing in the QAQC file that wasn't also in the data import file. Deleted the QAQC file.
- Added two carriage returns before level one headings.

data_management/data_02_consent_import.qmd

@@ -2,33 +2,48 @@
 title: "Import Data from FileMaker Pro: Consent"
 ---
 
+# Overview
+
+In this file, we import and do some initial cleaning of the consent form data collected and stored in FileMaker Pro.
+
+
+# Load packages
 
 ```{r, message= FALSE}
 library(readr)
-library(dplyr)
-library(janitor)
+library(dplyr, warn.conflicts = FALSE)
+library(janitor, warn.conflicts = FALSE)
 ```
+
+
 # Load the data
 
-Load the data table into the global environment as a data frame using the raw csv file. We will create categorical variables with numerical values that match the codebook and also create a factor variable for each categorical variable in the data frame to be used for analysis.
+Load the data table into the global environment as a data frame using the raw csv file. See this Wiki page for more information about the location of the data: https://github.com/brad-cannell/detect_fu_interviews_public/wiki. 
 
 ```{r}
-consent <- read_csv("../data/filemaker_pro_exports/consent_import.csv")
+consent_path <- here::here("data", "filemaker_pro_exports", "consent_import.csv")
 ```
 
-# Clean the data
-
-Here we will convert all variable names to snake case so that everything is uniform.
-
 ```{r}
-consent <- clean_names(consent)
+consent <- read_csv(consent_path)
 ```
 
 ```{r}
 # Data check
 dim(consent) # 1013 16
 ```
 
+
+# Data cleaning
+
+We will create categorical variables with numerical values that match the codebook and also create a factor variable for each categorical variable in the data frame to be used for analysis.
+
+## Convert all variable names to snake case
+
+```{r}
+consent <- clean_names(consent)
+```
+
 ## Coerce categorical variables to factor variables
 
 ```{r}
@@ -41,14 +56,25 @@ consent <- consent %>%
   )
 ```
 
-
 ```{r}
 # Data check
 dim(consent) # 1013 17
 ```
 
+
 # Save as rds file
 
 ```{r}
-write_rds(consent, "../data/cleaned_rds_files/consent_import.rds")
+consent_path <- here::here("data", "cleaned_rds_files", "consent_import.rds")
+```
+
+```{r}
+write_rds(consent, consent_path)
 ```
+
+
+# Clean up
+
+```{r}
+rm(list = ls())
+```

data_management/qaqc/check_consenting_participants.qmd

@@ -3,17 +3,54 @@ title: "Check consent"
 ---
 
 # Purpose
-The consent dataset does not contain all the Medstar IDs seen in the other datasets. The purpose of the code in this file is to double check the Medstar IDs not found in the consent dataset to make sure they shouldn't be included in the count of DETECT follow up interviews completed.
+
+The consent data set does not contain all of the Medstar IDs that are contained in the other data sets downloaded from FileMaker Pro. The purpose of the code in this file is to inventory the Medstar IDs that are not found in the consent data set and make sure they shouldn't be included in the count of DETECT follow up interviews completed.
+
 
 # Load Packages
 
 ```{r}
-library(dplyr)
+library(dplyr, warn.conflicts = FALSE)
 library(readr)
 library(purrr)
 ```
 
-# Load DETECT F/U Data
+# Load data
+
+Load the data table into the global environment as a data frame using the raw csv file. See this Wiki page for more information about the location of the data: https://github.com/brad-cannell/detect_fu_interviews_public/wiki. 
+
+```{r}
+rds_files <- c(
+  "aps_investigations_import.rds", "consent_import.rds"
+)
+
+df_names <- c("aps", "con")
+
+rds_paths <- purrr::map(
+  rds_files,
+  ~ here::here("data", "cleaned_rds_files", .x)
+)
+
+purrr::walk2(
+  df_names,
+  rds_paths,
+  
+)
+```
+
+
+```{r}
+# Check function to import files
+```
+
+
+```{r}
+aps_inv_path <- here::here("data", "filemaker_pro_exports", "aps_investigations_import.csv")
+```
+
+```{r}
+consent_path <- here::here("data", "filemaker_pro_exports", "consent_import.csv")
+```
 
 ```{r}
 aps <- read_rds("../data/cleaned_rds_files/aps_investigations_import.rds")