If we can assume that there is only 1 "Yes" value across the types, I think you can use the case_when function to help. There are some other solutions I can think of that involve pivoting the data as well. In the example below, I show how to do this for Examinator1 but it will be similar for Examinator2.
df <- structure(list(Examinator1_General = c("Yes", "No", "No", "No", "No", "No", "No", "Yes"),Examinator1_Focal = c("No", "Yes", "No", "No", "No", "No", "Yes", "No"),Examinator1_Local = c ("No", "No", "No", "Yes", "No", "No", "No", "No"),Examinator2_General = c("No","No","No","No","No","No","No","No"),Examinator2_Focal = c("Yes","No","No","No","No","No","Yes","No"),Examinator2_Local = c("No","No","No","Yes","No","No","No","Yes")),.Names=c("Examinator1_General","Examinator1_Focal", "Examinator1_Local","Examinator2_General","Examinator2_Focal", "Examinator2_Local"), row.names = c(NA,8L),class = "data.frame")
df2 <- structure(list (Examinator1_General = c("Yes", "No", "No", "No", "No", "No", "No", "Yes"),Examinator1_Focal = c("No", "Yes", "No", "No", "No", "No", "Yes", "No"),Examinator1_Local = c ("No", "No", "No", "Yes", "No", "No", "No", "No"),Examinator2_General = c("No","No","No","No","No","No","No","No"),Examinator2_Focal = c("Yes","No","No","No","No","No","Yes","No"),Examinator2_Local = c("No","No","No","Yes","No","No","No","Yes"),Examinator1 = c("General","Focal","None","Local","None","None","Focal","General"),Examinator2 = c("Focal","None","None","Local","None","None","Focal","Local")),.Names=c("Examinator1_General","Examinator1_Focal", "Examinator1_Local","Examinator2_General","Examinator2_Focal","Examinator2_Local","Examinator1","Examinator2"), row.names = c(NA,8L),class = "data.frame")
library(tidyverse)
df
#> Examinator1_General Examinator1_Focal Examinator1_Local Examinator2_General
#> 1 Yes No No No
#> 2 No Yes No No
#> 3 No No No No
#> 4 No No Yes No
#> 5 No No No No
#> 6 No No No No
#> 7 No Yes No No
#> 8 Yes No No No
#> Examinator2_Focal Examinator2_Local
#> 1 Yes No
#> 2 No No
#> 3 No No
#> 4 No Yes
#> 5 No No
#> 6 No No
#> 7 Yes No
#> 8 No Yes
df2
#> Examinator1_General Examinator1_Focal Examinator1_Local Examinator2_General
#> 1 Yes No No No
#> 2 No Yes No No
#> 3 No No No No
#> 4 No No Yes No
#> 5 No No No No
#> 6 No No No No
#> 7 No Yes No No
#> 8 Yes No No No
#> Examinator2_Focal Examinator2_Local Examinator1 Examinator2
#> 1 Yes No General Focal
#> 2 No No Focal None
#> 3 No No None None
#> 4 No Yes Local Local
#> 5 No No None None
#> 6 No No None None
#> 7 Yes No Focal Focal
#> 8 No Yes General Local
df %>%
mutate(Examinator1=case_when(
Examinator1_General == "Yes"~"General",
Examinator1_Focal == "Yes"~"Focal",
Examinator1_Local == "Yes" ~ "Local",
TRUE ~ "None"
))
#> Examinator1_General Examinator1_Focal Examinator1_Local Examinator2_General
#> 1 Yes No No No
#> 2 No Yes No No
#> 3 No No No No
#> 4 No No Yes No
#> 5 No No No No
#> 6 No No No No
#> 7 No Yes No No
#> 8 Yes No No No
#> Examinator2_Focal Examinator2_Local Examinator1
#> 1 Yes No General
#> 2 No No Focal
#> 3 No No None
#> 4 No Yes Local
#> 5 No No None
#> 6 No No None
#> 7 Yes No Focal
#> 8 No Yes General
Created on 2020-09-23 by the reprex package (v0.3.0)