【发布时间】:2018-05-27 03:32:55
【问题描述】:
我的数据 (dtf.long) 如下所示:
nutrition fertilizer season seedlingdensity plandensity fitted
nitrogen none wet 5 19 6
nitrogen none dry 5 19 8
nitrogen phos wet 4 23 16
nitrogen phos dry 5 19 10
iron none wet 5 29 21
iron none dry 5 19 14
iron phos wet 4 23 12
iron phos dry 5 20 14
....
...
总共有 16 个重复。我想用 y 轴上的 log(seedlingdensity) 和 x 轴上的 log(plandensity) 绘制回归,由食物分面。这两种肥料可以一种颜色和不同的季节。
我试着写了一段代码,但我仍然不知道如何为赛季的 pch 编写代码
回归的模型拟合存储在拟合列中
summary_dat = dtf.long %>%
group_by(nutrition, fertilizer, season) %>%
summarise(mean_predict=mean(fitted),
sd_predict = sd(fitted),
n_predict = n()) %>%
mutate(se_predict = sd_predict / sqrt(n_predict),
lower_ci = mean_predict - qt(1 - (0.05 / 2), n_predict - 1) * se_predict,
upper_ci = mean_predict + qt(1 - (0.05 / 2), n_predict - 1) * se_predict)
ggplot() +
geom_point(data=dtf.long, aes(x=log(plantdensity), y=log(seedlingdensity), group=fertilizer, color = fertilizer), position=position_dodge(width=0.5)) +
geom_errorbar(data=summary_dat, aes(x=log(plantdensity), ymax=upper_ci, ymin=lower_ci, group=fertilizer, color=fertilizer), position=position_dodge(width=0.5), width=0.2) +
geom_point(data=summary_dat, aes(log(plantdensity), y=mean_predict, group=fertilizer, color=fertilizer), size=3, position=position_dodge(width=0.5)) +
facet_grid(nutrition ~ .) + xlab("log(Plant Density") + ylab("log(Seedling Density)")
【问题讨论】:
标签: r ggplot2 regression mixed-models