In n8thangreen/STIecoPredict: Multilevel Regression With Post-Stratification Using Natsal Data

load(file="data/CTADGUM_pred-with-LA.RData")
# load(file="data/CTADGUM_pred-no-place-effects.RData")

SCALE <- 10

CTADGUM_age1524_2012$LA.Name <- toupper(CTADGUM_age1524_2012$LA.Name)
CTADGUM_age1524_2012$Coverage2012.nongum <- with(CTADGUM_age1524_2012, Chlamydia.Tests.nongum/X15.24.Year.Old.Population.Estimates)
CTADGUM_age1524_2012$Coverage2012.nongum <- CTADGUM_age1524_2012$Coverage2012.nongum*(1-0.0767)   #remove proportion estimated to be 15 year olds
CTADGUM_pred <- merge(CTADGUM_pred, CTADGUM_age1524_2012[ ,c("LA.Name", "Coverage2012.nongum")], by.x="LA Name", by.y="LA.Name")

CTADGUM_age1524_2013$LA.Name <- toupper(CTADGUM_age1524_2013$LA.Name)
CTADGUM_age1524_2013$Coverage2013.nongum <- with(CTADGUM_age1524_2013, Chlamydia.Tests.nongum/X15.24.Year.Old.Population.Estimates)
CTADGUM_age1524_2013$Coverage2013.nongum <- CTADGUM_age1524_2013$Coverage2013.nongum*(1-0.0767)   #remove proportion estimated to be 15 year olds
CTADGUM_pred <- merge(CTADGUM_pred, CTADGUM_age1524_2013[ ,c("LA.Name", "Coverage2013.nongum")], by.x="LA Name", by.y="LA.Name")

plot(CTADGUM_pred$nonGUMwtmean, CTADGUM_pred$LApred,
     xlim=c(0,0.7), ylim=c(0,0.7),
     cex=CTADGUM_pred$NatsalLAsize/SCALE, main="(b)",
     xlab="Direct LA estimates using Natsal-3", ylab="MRP estimates")
abline(a=0, b=1)

par(mfrow=c(1,1))
plot(CTADGUM_pred$LApred, CTADGUM_pred$Coverage2012.nongum,
     cex=CTADGUM_pred$NatsalLAsize/SCALE,
          xlab="MRP estimates", ylab="Surveillance data",
     # col=1+as.numeric(CTADGUM_pred$NatsalLAsize!=1.5),
     xlim=c(0,0.7), ylim=c(0,0.7))
abline(a=0, b=1, lty=2, lwd=2)
abline(a=mean.surveil-mean.Natsal, b=1, lty=3, lwd=2)
abline(h=mean.Natsal, lty=2)
abline(h=mean.surveil, lty=3)
text(x = c(0.25, 0.5, 0.25, 0.45), y = c(0.2, 0.3, 0.34, 0.4), labels = c("A","B","C","D"), cex=1.8)


par(mfrow=c(1,1))
plot(CTADGUM_pred$LApred, CTADGUM_pred$Coverage2012.nongum,
          xlab="MRP estimates", ylab="Surveillance data",
          cex=CTADGUM_pred$NatsalLAsize/SCALE,
     col=rgb(0, 0, 0, 0.3), pch=16,
     # col=1+as.numeric(CTADGUM_pred$NatsalLAsize!=1.5),
     xlim=c(0,0.7), ylim=c(0,0.7))
abline(a=0, b=1)

par(mfrow=c(1,1))
plot(CTADGUM_pred$LApred, CTADGUM_pred$Coverage2012.nongum,
          xlab="MRP estimates", ylab="Surveillance data",
     col=rgb(0, 0, 0, 0.3), pch=16,
     # col=1+as.numeric(CTADGUM_pred$NatsalLAsize!=1.5),
     xlim=c(0,0.7), ylim=c(0,0.7))
abline(a=0, b=1, lty=2, lwd=2)
abline(a=mean.surveil-mean.Natsal, b=1, lty=3, lwd=2)
abline(h=mean.Natsal, lty=2)
abline(h=mean.surveil, lty=3)
text(x = c(0.25, 0.5, 0.25, 0.45), y = c(0.2, 0.3, 0.34, 0.4), labels = c("A","B","C","D"))

par(mfrow=c(1,1))
plot(CTADGUM_pred$LApred, CTADGUM_pred$Coverage2013.nongum,
     cex=CTADGUM_pred$NatsalLAsize/SCALE,
          xlab="MRP estimates", ylab="Surveillance data",
     # col=1+as.numeric(CTADGUM_pred$NatsalLAsize!=1.5),
     xlim=c(0,0.7), ylim=c(0,0.7))
abline(a=0, b=1, lty=2, lwd=2)
abline(a=mean.surveil-mean.Natsal, b=1, lty=3, lwd=2)
abline(h=mean.Natsal, lty=2)
abline(h=mean.surveil, lty=3)
text(x = c(0.25, 0.5, 0.25, 0.45), y = c(0.2, 0.3, 0.34, 0.4), labels = c("A","B","C","D"), cex=1.8)


par(mfrow=c(1,1))
plot(CTADGUM_pred$LApred, CTADGUM_pred$Coverage2013.nongum,
          xlab="MRP estimates", ylab="Surveillance data",
          cex=CTADGUM_pred$NatsalLAsize/SCALE,
     col=rgb(0, 0, 0, 0.3), pch=16,
     # col=1+as.numeric(CTADGUM_pred$NatsalLAsize!=1.5),
     xlim=c(0,0.7), ylim=c(0,0.7))
abline(a=0, b=1)

par(mfrow=c(1,1))
plot(CTADGUM_pred$LApred, CTADGUM_pred$Coverage2013.nongum,
          xlab="MRP estimates", ylab="Surveillance data",
     col=rgb(0, 0, 0, 0.3), pch=16,
     # col=1+as.numeric(CTADGUM_pred$NatsalLAsize!=1.5),
     xlim=c(0,0.7), ylim=c(0,0.7))
abline(a=0, b=1, lty=2, lwd=2)
abline(a=mean.surveil-mean.Natsal, b=1, lty=3, lwd=2)
abline(h=mean.Natsal, lty=2)
abline(h=mean.surveil, lty=3)
text(x = c(0.25, 0.5, 0.25, 0.45), y = c(0.2, 0.3, 0.34, 0.4), labels = c("A","B","C","D"))

n8thangreen/STIecoPredict documentation built on June 7, 2020, 12:50 p.m.