OR.qmd

---
title: "Calculate OR"
format: html
editor: visual
---

```{r}
pacman::p_load(epiR, tidyverse)
library(epiR)
library(tidyverse)

ae01 <- tibble::tibble(
 aebodsys = c("Cardiovascular", "Cardiovascular", "Respiratory", "Respiratory"),
 trt = c("Drug A", "Placebo", "Drug A", "Placebo"),
 No_Event = c(90, 95, 85, 90),
 Event = c(10, 5, 15, 10)
)

listoflsit <- ae01 %>% group_split(aebodsys) %>% setNames(unique(ae01$aebodsys))

or <- purrr::map2(1:length(listoflsit), names(listoflsit) ,.f= function(x,y) {
 # browser()
a <- listoflsit[[x]][4]$Event[1]
b <- listoflsit[[x]][3]$No_Event[1]
c <- listoflsit[[x]][4]$Event[2]
d <- listoflsit[[x]][3]$No_Event[2]


mat <- matrix(c(a, b, c, d), nrow = 2, byrow = TRUE,
 dimnames = list(Treatment = c("Drug", "Placebo"),
 Outcome = c("Event", "No Event")))


lst <- epi.2by2(mat, method = "cohort.count", conf.level = 0.95)

df <- tibble::tibble(aebodsys=y,
 estimate=lst$massoc.detail$OR.strata.wald$est,
 lower=lst$massoc.detail$OR.strata.wald$lower,
 upper=lst$massoc.detail$OR.strata.wald$upper,
 pvalue=lst$massoc.detail$chi2.strata.fisher$p.value.2s)

return(df)

})

finaldf <- do.call(bind_rows, or)
finaldf
```