Formalize Table 1 process/functions

[mbcann01]

You have a fair amount of loose code floating around related to creating tables for presentation/dissemination. Need to formalize and refine the processes and code. A good example comes from STEP:

# Create the table shell
# ---------------------
table <- tibble(
  variable   = "",
  class      = "",
  no_readmit = step_clean_03 %>% bfuncs::get_group_n(readmit_30_day == 0),
  readmit    = step_clean_03 %>% bfuncs::get_group_n(readmit_30_day == 1)
)

# Select data frame
# -----------------
df <- step_clean_03

# Select group variable (columns)
# -------------------------------
group <- quo(readmit_30_day)

# Select variables (in order of appearance)
# -----------------------------------------
vars <- quos(age, gender, race_eth, insurance, any_trans_limitations, pt_support_score, 
             health_lit_score, high_risk, appts_total, any_sw, any_pt, any_diet, pharmacist, 
             mental_health_concerns, falls_3_months, falls_12_months,chapters_7cat_short)


# Build table
# -----------

for (i in seq_along(vars)) {
  
  # Figure out what type of variable it is
  class_var_i <- df %>% 
    pull(!!vars[[i]]) %>% 
    class()
  
  # If it's a categorical (character/factor) variable:
  # Calculate percent and 95% CI
  # Then, add that row to the table
  if (class_var_i == "character" || class_var_i == "factor") {
    
    row <- df %>% 
      filter(!(is.na(!!vars[[i]]))) %>% # filter out missing
      group_by(!!group, !!vars[[i]]) %>% 
      freq_table() %>% 
      format_table() %>% 
      spread(key = !!group, value = percent_row_95) %>% 
      mutate(variable = colnames(.)[1]) %>% 
      rename("class" = !!vars[[i]], "no_readmit" = `FALSE`, "readmit" = `TRUE`) %>% 
      mutate(class = as.character(class)) # Need for bind_rows below

    # Append to bottom of table
    table <- bind_rows(table, row)
    
  # If it's a continuous variable:
  # Calculate mean and 95% CI
  # Then, add that row to the table 
  } else {
    
    row <- df %>% 
      group_by(!!group) %>% 
      bfuncs::mean_table(!!vars[[i]]) %>% 
      bfuncs::format_table() %>% 
      spread(key = !!group, value = mean_95) %>% 
      rename("variable" = var, "no_readmit" = `FALSE`, "readmit" = `TRUE`)

    # Append to bottom of table
    table <- bind_rows(table, row)
  }
}

• Make dplyr-friendly functions
• When complete, update vignette as discussed in Improve Presenting and Disseminating Results Vignette #23