7.2 Expected cases

  • indirected standardization
  • strata: 2 races X 2 genders = 2X2 = 4
library(SpatialEpi)
n.strata = 4
dohio <- dohio%>%
  arrange(county,year,gender,race)
  
E <- expected(population = dohio$n,
              cases = dohio$y,
              n.strata = n.strata)
nyears <- length(unique(dohio$year))
countiesE <- rep(unique(dohio$NAME),
                 each = nyears)
ncounties <- length(unique(dohio$NAME))
yearsE <- rep(unique(dohio$year),
              times = ncounties)

dE <- data.frame(county = countiesE, year = yearsE, E = E)

head(dE)
##   county year         E
## 1  Adams 1968  8.278660
## 2  Adams 1969  8.501767
## 3  Adams 1970  8.779313
## 4  Adams 1971  9.175276
## 5  Adams 1972  9.548736
## 6  Adams 1973 10.099777
d <- merge(d, dE, by = c("county", "year"))
head(d)
##   county year  Y         E
## 1  Adams 1968  6  8.278660
## 2  Adams 1969  5  8.501767
## 3  Adams 1970  9  8.779313
## 4  Adams 1971  6  9.175276
## 5  Adams 1972 10  9.548736
## 6  Adams 1973  7 10.099777