#Dear All,
#I'm having a bit of a trouble here, please help me...
#I have this data
set.seed(4)
mydata <- data.frame(var = rnorm(100),
temp = rnorm(100),
subj = as.factor(rep(c(1:10),5)),
trt = rep(c("A","B"), 50))
#and this model that fits them
lm <- lm(var ~ temp * subj, data = mydata)
#i want to plot the results with lattice anf fit the regression line, predicted
with my model, trough them
#to do so, I'm using this approach, outlined "Lattice Tricks for the power
useR" by D. Sarkar
temp_rng <- range(mydata$temp, finite = TRUE)
grid <- expand.grid(temp = do.breaks(temp_rng, 30),
subj = unique(mydata$subj),
trt = unique(mydata$trt))
model <- cbind(grid, var = predict(lm, newdata = grid))
orig <- mydata[c("var","temp","subj","trt")]
combined <- make.groups(original = orig, model = model)
xyplot(var ~ temp | subj,
data = combined,
groups = which,
type = c("p", "l"),
distribute.type = TRUE
)
# so far every thing is fine, but, i also whant assign a filling to the data
points for the two treatments trt=1 and trt=2
# so I have written this piece of code, that works fine, but when it comes to
plot the regression line, it seems that type is not recognized by the panel
function...
my.fill <- c("black", "grey")
plot <- with(combined,
xyplot(var ~ temp | subj,
data = combined,
group = combined$which,
type = c("p", "l"),
distribute.type = TRUE,
panel = function(x, y, ..., subscripts){
fill <- my.fill[combined$trt[subscripts]]
panel.xyplot(x, y, pch = 21, fill = my.fill, col =
"black")
},
key = list(space = "right",
text = list(c("trt1", "trt2"), cex = 0.8),
points = list(pch = c(21), fill = c("black", "grey")),
rep = FALSE)
)
)
plot
#I've also tried to move type and distribute type within panel.xyplot, as well
as subsseting the data in it panel.xyplot like this
plot <- with(combined,
xyplot(var ~ temp | subj,
data = combined,
panel = function(x, y, ..., subscripts){
fill <- my.fill[combined$trt[subscripts]]
panel.xyplot(x[combined$which=="original"],
y[combined$which=="original"], pch = 21, fill = my.fill, col = "black")
panel.xyplot(x[combined$which=="model"],
y[combined$which=="model"], type = "l", col = "black")
},
key = list(space = "right",
text = list(c("trt1", "trt2"), cex = 0.8),
points = list(pch = c(21), fill = c("black", "grey")),
rep = FALSE)
)
)
plot
#but no success with that either...
#can anyone help me to get the predicted values plotted as a line instead of
being points?
#really appricieate
#matteo
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