In softloud/sperm: Analysis

library(tidyverse)
library(sperm)
library(targets)
library(gt)

Cleaned data

The cleaned data can be accessed using targets:

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.

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 :)

tar_read(model_dat) %>% 
  count(intervention, class) %>% 
  select(-n) %>% 
  gt()

Modelling input

Here's a random sample of ten observations:

tar_read(wide_obs) %>% 
  sample_n(10) %>% 
  gt() %>% 
  tab_header("Modelling data",
             subtitle = "10 randomly-selected observations") %>% 
  tab_options(
  )