The data are in this folder:
onedrive <- "~/Library/CloudStorage/OneDrive-OxfordUniversityClinicalResearchUnit/"
library(readr)
hist2 <- function(..., col = 4, n = 100, alpha = .2, main = NA) {
hist(..., n = n, main = main, col = adjustcolor(col, alpha), border = col,
ylab = "frequency")
}
st <- read_csv(paste0(onedrive, "GitHub/OUCRU-Modelling/scrub-typhus/Rickettsia_ELISA.csv"))
The data look like this:
st
## # A tibble: 1,037 × 14
## No. SAMPLE_ID AGE_MIN AGE_MAX GENDER DAY MONTH YEAR WARD E_Day E_Month
## <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 HC040033 1.5 1.5 1 23 2 2010 11 11 12
## 2 2 HC040048 0.5 0.5 0 26 2 2010 11 11 12
## 3 3 HC040078 27 28.0 0 3 2 2010 11 11 12
## 4 4 HC040144 45 46.0 0 4 2 2010 11 11 12
## 5 5 HC040146 47 48.0 0 4 2 2010 11 11 12
## 6 6 HC050055 29 30.0 0 3 3 2010 11 11 12
## 7 7 HC050074 22 23.0 0 18 3 2010 11 11 12
## 8 8 HC050086 28.2 29.2 1 25 3 2010 11 11 12
## 9 9 HC050151 53 54.0 1 16 3 2010 11 11 12
## 10 10 HC050157 56 57.0 0 17 3 2010 11 11 12
## # ℹ 1,027 more rows
## # ℹ 3 more variables: E_Year <dbl>, Scrub_Typhus <dbl>, Typhus <dbl>
The last 3 variables:
st[, 12:14]
## # A tibble: 1,037 × 3
## E_Year Scrub_Typhus Typhus
## <dbl> <dbl> <dbl>
## 1 2017 0.011 0.215
## 2 2017 0.006 0.21
## 3 2017 0.097 0.163
## 4 2017 0.081 0.18
## 5 2017 0.053 0.504
## 6 2017 -0.033 0.132
## 7 2017 0.473 0.152
## 8 2017 0.058 0.261
## 9 2017 -0.002 0.016
## 10 2017 0.033 0.432
## # ℹ 1,027 more rows
hist2(st$Scrub_Typhus, xlab = "value", main = "scrub typhus")
hist2(st$Typhus, xlab = "value", main = "typhus")