```{r clean_data} posture_clean_df = posture_df |> # Fill missing age_group based on age thresholds mutate( age_group = case_when( !is.na(age_group) ~ age_group, age >= 18 & age <= 30 ~ "18-30", age >= 31 & age <= 40 ~ "31-40", age >= 41 & age <= 50 ~ "41-50", age >= 51 & age <= 60 ~ "51-60", age > 60 ~ ">60", TRUE ~ NA_character_ ) ) |> # Fill missing fhp_category based on fhp_size_mm thresholds mutate( fhp_category = case_when( !is.na(fhp_category) ~ fhp_category, fhp_size_mm >= 0 & fhp_size_mm < 10 ~ "0-10mm", fhp_size_mm >= 10 & fhp_size_mm < 20 ~ "10-20mm", fhp_size_mm >= 20 & fhp_size_mm < 30 ~ "20-30mm", fhp_size_mm >= 30 ~ ">=30mm", TRUE ~ NA_character_ ) ) |> # Fill missing eeop_category based on eeop_size_mm thresholds mutate( eeop_category = case_when( !is.na(eeop_category) ~ eeop_category, eeop_size_mm >= 0 & eeop_size_mm < 5 ~ "0-5mm", eeop_size_mm >= 5 & eeop_size_mm < 10 ~ "5-10mm", eeop_size_mm >= 10 & eeop_size_mm < 15 ~ "10-15mm", eeop_size_mm >= 15 & eeop_size_mm < 20 ~ "15-20mm", eeop_size_mm >= 20 & eeop_size_mm < 25 ~ "20-25mm", eeop_size_mm >= 25 ~ ">=25mm", TRUE ~ NA_character_ ) ) |> # Convert sex to factor mutate( sex = factor(sex, levels = c("male", "female")) ) |> # Convert age_group to ordered factor mutate( age_group = factor( age_group, levels = c