如何用ggplot2绘制三组不同的非线性回归曲线

Let's break down and fix the styling problems you're facing with your ggplot2 plot:

Key Issues in Your Current Code #

1. Putting linetype=group in the global aes() makes all geoms (including errorbars) inherit this mapping, which is why your errorbars turned dashed.
2. The fill=group in stat_smooth() is unnecessary (since you set se=F) and creates an extra legend.
3. The legend for linetype is separate from color/shape, leading to redundant legends.

Corrected Code #

ggplot(datapoidsmono, aes(x = time, y = weight, group = group, color = group)) +
  # Error bars (keep solid, inherit color from group)
  stat_summary(fun.data = "mean_sdl", fun.args = list(mult=1), 
               geom = "errorbar", position = "identity", 
               size = 0.5, width = 0.2, linetype = 1) +
  # Mean points (shape mapped to group)
  stat_summary(fun.y = "mean", geom = "point", size = 3, 
               aes(shape = group)) +
  # LOESS fit lines: dashed, mapped to group, no confidence band
  stat_smooth(method = "loess", se = F, 
              aes(linetype = group), size = 0.8) +
  # Scales: align labels and values across color/shape/linetype
  scale_x_discrete(name = "Days after injection") +
  scale_y_continuous(name = "Weight (g)", limits = c(0, 4000), breaks = seq(0, 4000, 500)) +
  scale_color_manual(values = c("green", "blue", "red"), 
                     name = "Treatment", labels = c("A", "B", "C")) +
  scale_shape_manual(values = c(15, 16, 17), 
                     name = "Treatment", labels = c("A", "B", "C")) +
  scale_linetype_manual(values = c("dotted", "dotted", "dotted"), 
                        name = "Treatment", labels = c("A", "B", "C")) +
  # Theme and title settings
  ggtitle("Weight variation over time") +
  theme(
    plot.title = element_text(hjust = 0.5, size = 20, face = "bold"),
    legend.position = "right",
    legend.background = element_rect(size = 0.5, linetype = "solid", color = "black", fill = "white"),
    axis.line.x = element_line(size = 0.5, color = "black"),
    axis.text.x = element_text(color = "black", size = 12),
    axis.line.y = element_line(size = 0.5, color = "black"),
    axis.text.y = element_text(color = "black", size = 12),
    axis.title = element_text(size = 15, face = "bold"),
    panel.grid.major = element_line(color = "#F1F1F1"),
    panel.grid.minor = element_blank(),
    panel.background = element_blank()
  ) +
  # Merge legends: ensure color/shape/linetype share one legend
  guides(color = guide_legend(override.aes = list(shape = c(15,16,17), linetype = c("dotted","dotted","dotted"))),
         shape = "none",
         linetype = "none")

Key Adjustments Explained #

1. Moved linetype=group to stat_smooth() only: This ensures only the fit lines use dashed styles, while errorbars remain solid (we explicitly set linetype=1 for errorbars to be safe).
2. Removed unnecessary fill=group from stat_smooth(): Since se=F, there's no fill to map, so this was creating an extra legend we don't need.
3. Aligned scale names/labels: All scale_*_manual() functions use the same name and labels to ensure legend consistency.
4. Merged legends: The guides() call combines color, shape, and linetype into a single "Treatment" legend, hiding the redundant shape/linetype legends.
5. Explicitly set method="loess": While ggplot2 uses LOESS by default for small datasets, making it explicit makes your code more readable.

This should give you:

• Solid error bars matching group colors
• Mean points with unique shapes and group colors
• Dotted LOESS fit lines matching each group's color
• A single, clean legend for all treatment groups

内容的提问来源于stack exchange，提问作者B_slash_