integrity.Rmd

---
title: "Data integrity and quality assurance"
date: "`r Sys.Date()`"
output: distill::distill_article
---

```{r}
library(tidyverse)
library(sperm)
library(targets)
library(gt)

```


# Cleaned data

The cleaned data can be accessed using targets:

```{r}
tar_read(model_dat)
```

## Modelling variables

We're interested in assessing 

> `outcome = intervention_class + type of infertility`

Currently `class` is set to `major_intervention_grouping` and `intervention` is set to `grouped_intervention`. The `moderator` is `type_of_infertility`.

> Kerry, is this correct? Very easy to update if not :) 


## Cleaning class labels

There are 10 interventions with more than one class label. 

```{r}
tar_read(qa_class) %>% 
  gt()
```

There needs to be at most one class label per intervention or the model will complain. Charles has set the class to be the most-used class label for each intervention.

> Kerry please check you're happy with the class labels :)

```{r}
tar_read(model_dat) %>% 
  count(intervention, class) %>% 
  select(-n) %>% 
  gt() 

```


## Modelling input

Here's a random sample of ten observations:

```{r, layout="l-page"}
tar_read(wide_obs) %>% 
  sample_n(10) %>% 
  gt() %>% 
  tab_header("Modelling data",
             subtitle = "10 randomly-selected observations") %>% 
  tab_options(
  )

```