raceOR <- subset(races, races$t %% 14 == 0)

raceOR$oddsratio = 0

for(i in 0:12)
{
  for(j in 1:6)
  {
    a = raceOR$survived[(i*6)+4]
    c = raceOR$evdeath[(i*6)+4]
    
    if(j == 4)
    {
      raceOR$oddsratio[(i*6)+j] = 1.00
      next
    }
    
    b = raceOR$survived[(i*6)+j]
    d = raceOR$evdeath[(i*6)+j]
    
    raceOR$oddsratio[(i*6)+j] = (a * d) / (b * c)
  }
}

ggplot(data = raceOR, aes(x = DATE, y = oddsratio)) + geom_line(aes(color=RACE), size = 1)

raceOR2 <- subset(raceOR, raceOR$t > 0 & raceOR$t < 160)

ggplot(data = raceOR2, aes(x = DATE, y = survrate)) + geom_line(aes(color=RACE), size = 1)


ageOR <- subset(ages, ages$t %% 14 == 0)

ageOR$oddsratio = 0

for(i in 0:12)
{
  for(j in 1:10)
  {
    a = ageOR$survived[(i*10)+5]
    c = ageOR$evdeath[(i*20)+5]
  
    if(j == 5)
    {
      ageOR$oddsratio[(i*10)+j] = 1.00
      next
    }
  
    b = ageOR$survived[(i*10)+j]
    d = ageOR$evdeath[(i*10)+j]
  
    ageOR$oddsratio[(i*10)+j] = (a * d) / (b * c)
  }
}

ggplot(data = ageOR, aes(x = DATE, y = oddsratio)) + geom_line(aes(color=AGE), size = 1)

ageOR2 <- subset(ageOR, ageOR$t > 0 & ageOR$t < 160)

ggplot(data = ageOR2, aes(x = DATE, y = survrate)) + geom_line(aes(color=AGE), size = 1)

sexOR <- subset(sexes, sexes$t %% 14 == 0)

sexOR$oddsratio = 0

for(i in 0:12)
{
  for(j in 1:3)
  {
    a = sexOR$survived[(i*3)+2]
    c = sexOR$evdeath[(i*3)+2]
    
    if(j == 2)
    {
      sexOR$oddsratio[(i*3)+j] = 1.00
      next
    }
    b = sexOR$survived[(i*3)+j]
    d = sexOR$evdeath[(i*3)+j]
    
    sexOR$oddsratio[(i*3)+j] = (a * d) / (b * c)
  }
}

ggplot(data = sexOR, aes(x = t, y = oddsratio)) + geom_line(aes(color=SEX), size = 1)







agepie <- subset(ages, )