nestauk / asf_boiler_optimisation_rct_loop Goto Github PK

userid_df = data |>
  distinct(user_id) |>
  as.data.frame()

userid_T_df <- data |>
  filter(treatment_num == 0 | treatment_num == 1)

data <- data |>
  mutate(
    rand = sample(4, nrow(data), replace=TRUE),
    email = case_when(
      treatment == "C" ~ "Control",
      rand == 1 ~ "Standard",
      rand == 2 ~ "Thermostat",
      rand == 3 ~ "TRV",
      rand == 4 ~ "Social norm"
    )
  )

data = data |>
  mutate(
    assignment = simple_ra(nrow(data), conditions = c("Standard", "Thermostat", "TRV", "Social norm")),
    email = case_when(
      treatment == "C" ~ "Control",
      TRUE ~ as.character(assignment)
    )
  )

data <- data |>
  group_by(user_id) |>
  mutate(allocation = runif(1))

library(randomizr)

## Remove duplicate users
data <- data[!duplicated(data$user_id),]

data <- data |>
  mutate(
	## Stratify by region and assign treatments
    treatment = block_ra(blocks = data$region_id, conditions = c("T1", "T2", "C")),
	## Temporarily assign email to all users using simple randomisation
    temp.assignment = simple_ra(nrow(data), conditions = c("Standard", "Thermostat", "TRV", "Social norm")),
	## For Control group, replace with "Control"
    email = case_when(
      treatment == "C" ~ "Control",
      TRUE ~ as.character(temp.assignment)
    )
  ) |>
  ## Remove temporary assignment column
  select(-temp.assignment)