Strength of a chemical paste product; its quality
depending on the delivery batch, and the cask within the
delivery.
Format
A data frame with 60 observations on the following 4 variables.
strength
paste strength.
batch
delivery batch from which the sample was
sample. A factor with 10 levels: ‘A’ to ‘J’.
cask
cask within the delivery batch from which the
sample was chosen. A factor with 3 levels: ‘a’ to
‘c’.
sample
the sample of paste whose strength was assayed,
two assays per sample. A factor with 30 levels: ‘A:a’ to
‘J:c’.
Details
The data are described in Davies and Goldsmith (1972) as
coming from “ deliveries of a chemical paste
product contained in casks where, in addition to sampling
and testing errors, there are variations in quality
between deliveries ... As a routine, three casks
selected at random from each delivery were sampled and
the samples were kept for reference. ... Ten of the
delivery batches were sampled at random and two
analytical tests carried out on each of the 30 samples”.
Source
O.L. Davies and P.L. Goldsmith (eds), Statistical
Methods in Research and Production, 4th ed., Oliver and
Boyd, (1972), section 6.5
Examples
str(Pastes)
require(lattice)
dotplot(cask ~ strength | reorder(batch, strength), Pastes,
strip = FALSE, strip.left = TRUE, layout = c(1, 10),
ylab = "Cask within batch",
xlab = "Paste strength", jitter.y = TRUE)
## Modifying the factors to enhance the plot
Pastes <- within(Pastes, batch <- reorder(batch, strength))
Pastes <- within(Pastes, sample <- reorder(reorder(sample, strength),
as.numeric(batch)))
dotplot(sample ~ strength | batch, Pastes,
strip = FALSE, strip.left = TRUE, layout = c(1, 10),
scales = list(y = list(relation = "free")),
ylab = "Sample within batch",
xlab = "Paste strength", jitter.y = TRUE)
## Four equivalent models differing only in specification
(fm1 <- lmer(strength ~ (1|batch) + (1|sample), Pastes))
(fm2 <- lmer(strength ~ (1|batch/cask), Pastes))
(fm3 <- lmer(strength ~ (1|batch) + (1|batch:cask), Pastes))
(fm4 <- lmer(strength ~ (1|batch/sample), Pastes))
## fm4 results in redundant labels on the sample:batch interaction
head(ranef(fm4)[[1]])
## compare to fm1
head(ranef(fm1)[[1]])
## This model is different and NOT appropriate for these data
(fm5 <- lmer(strength ~ (1|batch) + (1|cask), Pastes))
L <- getME(fm1, "L")
Matrix::image(L, sub = "Structure of random effects interaction in pastes model")