Nothing
## ----import, include = FALSE--------------------------------------------------
library(ggplot2)
library(testassay)
d <- gia
tab<-table(d$sample,d$assay)
rowNames<-dimnames(tab)[[1]]
n.ones<-function(x){
length(x[x==1])
}
nOnes<-apply(tab,1,n.ones)
sample4<-names(nOnes[nOnes==4])
td7samp<- sample4[grep("3D7",sample4)]
fvosamp<- sample4[grep("FVO",sample4)]
## check that each sample is repeated on 4 assays
J<- d$sample %in% td7samp
tab3d7<-table(d$sample[J],d$assay[J])
## now fvo
J<- d$sample %in% fvosamp
tabfvo<-table(d$sample[J],d$assay[J])
## ----ex-----------------------------------------------------------------------
summary(gia)
## ----pl1, echo = FALSE, message = FALSE---------------------------------------
ggplot(d, aes(x = gia, y = meanAAgia, color = parasite)) +
geom_abline(slope = 1, intercept = 0, color = "gray", size = 1.5) + geom_point() +
scale_x_continuous("GIA", limits = c(-5, 100), breaks = seq(0, 100, by = 20)) +
scale_y_continuous("mean GIA (per sample)", limits = c(-5, 100), breaks = seq(0, 100, by = 20)) + theme_bw() +
theme(legend.position = c(.85, .2))
## ----giatest1-----------------------------------------------------------------
treD7.test <- testassay(x = gia,
m = sample, n = assay, q = .9,
model = "normal", constant = "variance",
data = subset(gia, parasite == "3D7" & meanAAgia < 80))
treD7.test
## ----giapredict---------------------------------------------------------------
obsD7 <- rnorm(5, mean = 50, sd = 18)
predict(treD7.test, newdata = obsD7)
## ----giatest2-----------------------------------------------------------------
FVO.test <- testassay(x = gia,
m = sample, n = assay, q = .9,
model = "normal", constant = "variance",
data = subset(gia, parasite == "FVO" & meanAAgia < 80))
FVO.test
predict(FVO.test)
## ----predplot-----------------------------------------------------------------
predat <- cbind(subset(gia, parasite == "FVO" & meanAAgia < 80), predict(FVO.test))
ggplot(predat,
aes(x = assay, y = obs, ymin = lower, ymax = upper)) +
geom_pointrange() + facet_wrap(~ sample) + ylab("GIA")
## ----giacv--------------------------------------------------------------------
newobs <- c(25, 40, 65)
predict(treD7.test, newobs)
cvn <- testassay(x = gia,
m = sample, n = assay, q = .9,
model = "normal", constant = "cv",
data = subset(gia, parasite == "3D7" & meanAAgia < 80))
predict(cvn, newobs)
cvln <- testassay(x = gia,
m = sample, n = assay, q = .9,
model = "lognormal", constant = "cv",
data = subset(gia, parasite == "3D7" & meanAAgia < 80))
predict(cvln, newobs)
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