my ggplot R-code works perfectly ok with my other datasets but I'm stumbled with why it's not working for one particular data set. See image below where the filled confidence interval stops at 0.10:
For reproducing the problem:
library(nlme)
library(ggeffects)
library(ggplot2)
SurfaceCoverage <- c(0.02,0.04,0.06,0.08,0.1,0.12,0.02,0.04,0.06,0.08,0.1,0.12)
SpecificSurfaceEnergy <- c(18.0052997,15.9636971,14.2951057,13.0263081,13.0816591,13.3825573,2.9267577,2.2889628,1.8909175,1.0083036,0.5683574,0.1681063)
sample <- c(1,1,1,1,1,1,2,2,2,2,2,2)
highW <- data.frame(sample,SurfaceCoverage,SpecificSurfaceEnergy)
highW$sample <- sub("^", "Wettable", highW$sample)
highW$RelativeHumidity <- "High relative humidity"; highW$group <- "Wettable"
highW$sR <- paste(highW$sample,highW$RelativeHumidity)
dfhighW <- data.frame(
"y"=c(highW$SpecificSurfaceEnergy),
"x"=c(highW$SurfaceCoverage),
"b"=c(highW$sample),
"sR"=c(highW$sR)
)
mixed.lme <- lme(y~log(x),random=~1|b,data=dfhighW)
pred.mmhighW <- ggpredict(mixed.lme, terms = c("x"))
(ggplot(pred.mmhighW) +
geom_line(aes(x = x, y = predicted)) + # slope
geom_ribbon(aes(x = x, ymin = predicted - std.error, ymax = predicted + std.error),
fill = "lightgrey", alpha = 0.5) + # error band
geom_point(data = dfhighW, # adding the raw data (scaled values)
aes(x = x, y = y, shape = b)) +
xlim(0.01,0.2) +
ylim(0,30) +
labs(title = "") +
ylab(bquote('Specific Surface Energy ' (mJ/m^2))) +
xlab(bquote('Surface Coverage ' (n/n[m]) )) +
theme_minimal()
)
Can someone advise me how to fix this? Thanks.