ggplot 置信区间未填充我的线性混合模型的整个数据集

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:

为了重现问题：

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()
)

有人可以告诉我如何解决这个问题吗？谢谢。

丝带的最后一部分已经消失，因为您已将其从绘图中排除。功能区的下边缘是以下向量：

pred.mmhighW$predicted - pred.mmhighW$std.error
#> [1]  3.91264018  2.37386628  1.47061258  0.82834206  0.32935718 -0.07886245

请注意，最终值是一个小负数，但您已使用以下命令设置 y 轴限制：

ylim(0, 30)

所以任何负面的东西都会被切断。如果你更改为

ylim(-2, 30)

You get