ggplot2 中覆盖的单独回归线答案

【问题标题】：Separate regression lines overlaid in ggplot2ggplot2 中覆盖的单独回归线
【发布时间】：2021-03-14 17:39:39
【问题描述】：

我正在尝试复制我在下面显示的情节，但没有成功。粗红色回归线应该来自int3 data.frame。细灰色回归线应该来自int2data.frame。

是否有解决方案来实现我想要的情节？

library(lme4)
library(tidyverse)

dd <- read.csv('https://raw.githubusercontent.com/rnorouzian/e/master/3.csv')

m31 <- lmer(math~year+(1|schoolid/childid), data = dd)

co <- coef(m31)

int2 = co$`childid:schoolid`
int2$ch_id <- substr(rownames(int2), 11, 14)
  
int3 = co$schoolid
int3$sch_id <- rownames(int3)


ggplot(data = dd, aes(x = year, y = math, group = factor(childid)))+ geom_point()+ facet_wrap(~schoolid)+
geom_abline(data = int2, aes(intercept=`(Intercept)`, slope=year)) +  
  geom_abline(data = int3, aes(intercept=`(Intercept)`, slope=year), color=2)

【问题讨论】：

标签： r dataframe ggplot2 plot tidyverse

【解决方案1】：

您需要将与group 变量和构面变量对应的列添加到数据框int2 和int3 中，以便回归线仅出现在相应的面板上，并按组进行适当的拆分。

您的示例中似乎部分完成了此操作，但由于 ID 列被赋予了不同的名称，因此不正确。它们应该与dd 中的变量同名。

int2 = co$`childid:schoolid`
int2$childid <- substr(rownames(int2), 1, 9)
int2$schoolid <- substr(rownames(int2), 11, 14)

int3 = co$schoolid
int3$schoolid <- rownames(int3)


ggplot(data = dd, aes(x = year, y = math, group = factor(childid)))+ geom_point()+ facet_wrap(~schoolid)+
  geom_abline(data = int2, aes(intercept=`(Intercept)`, slope=year)) +  
  geom_abline(data = int3, aes(intercept=`(Intercept)`, slope=year), color=2)

到目前为止一切顺利。但看起来在您的示例图中，回归线的 x 值范围与数据相同。要解决此问题，您需要将 geom_abline 替换为 geom_segment。我计算了每个schoolid 和childid 所需的x 值范围，并以这种方式找到了段的端点。

# Calculate range of values for schoolid and childid.
year_range_by_schoolid <- dd %>% group_by(schoolid) %>% summarize(min_year = min(year), max_year = max(year))
year_range_by_childid <- dd %>% group_by(schoolid, childid) %>% summarize(min_year = min(year), max_year = max(year))

# Find min and max points for each line.
int2 <- int2 %>% 
  mutate(schoolid = as.integer(schoolid),
         childid = as.integer(childid)) %>%
  left_join(year_range_by_childid) %>%
  mutate(min_y = `(Intercept)` + year * min_year,
         max_y = `(Intercept)` + year * max_year)

int3 <- int3 %>% 
  mutate(schoolid = as.integer(schoolid)) %>%
  left_join(year_range_by_schoolid) %>%
  mutate(min_y = `(Intercept)` + year * min_year,
         max_y = `(Intercept)` + year * max_year)


ggplot(data = dd, aes(x = year, y = math, group = factor(childid)))+ geom_point()+ facet_wrap(~schoolid)+
  geom_segment(data = int2, aes(x = min_year, y = min_y, xend = max_year, yend = max_y)) +  
  geom_segment(data = int3, aes(x = min_year, y = min_y, xend = max_year, yend = max_y, group = factor(schoolid)), color=2)

【讨论】：