基于 P 值显示回归线
Displaying regression lines based on P-value
我使用 ggpmisc 包在绘图中显示线性回归模型。如果 p 值小于 0.2，我只希望在图中显示回归线、p 值和 r2 值。 @Ricardo Semião e Castro 用很棒的代码帮助了我（谢谢！），但它只是有时有效。它是否有效取决于满足 P<0.2 标准的回归模型的数量。关于如何编写代码以使其在 0、1 或 2 个模型的 P 值低于 P 时都有效的想法？
代码如下：
library(ggpmisc)
library(ggplot2)
# Below code is to ensure that only LM with p < 0.2 is displayed in the graph
names = c(0,0) #Create a starting point of a matrix for the group names
#For each group, run a lm to find if pvalue < 0.2
for(i in unique(df$days)){
lm = summary(lm(acetone~bacteria, df[df$days==i,]))
p = pf(lm$fstatistic[1], lm$fstatistic[2], lm$fstatistic[3], lower.tail=FALSE)
if(p < 0.2){names = rbind(names, c(i))} #Get the groups that pass
}
#names = names[-1,] #Remove starting point
#Create subset of df with groups where p < 0.2; looping in order to check pair by pair
df_P0.2 = numeric()
for(i in 1:nrow(names)){
df_P0.2 = rbind(df_P0.2,df[df$days%in%names[i,1],])
}
formula <- y~x
(plot <- ggplot(df,
aes(bacteria,
acetone)) +
geom_smooth(method = "lm",
formula = y~x, color="black", data = df_P0.2) +
geom_point(aes(shape=soil_type, color=soil_type, size=soil_type,
fill=soil_type)) +
scale_fill_manual(values=c("#00AFBB", "brown")) +
scale_color_manual(values=c("black", "black")) +
scale_shape_manual(values=c(21, 24))+
scale_size_manual(values=c(2.4, 1.7))+
labs(shape="Soil type", color="Soil type", size="Soil type", fill="Soil type") +
theme_bw() +
facet_wrap(~days,
ncol = 4, scales = "free")+
stat_poly_eq(data=df_P0.2,
aes(label = paste(stat(adj.rr.label),
stat(p.value.label),
sep = "*\", \"*")),
formula = formula,
rr.digits = 1,
p.digits = 1,
parse = TRUE,size=3.5))
这是数据：
df <- structure(list(bacteria = c(0.301, 1.079, 0, 0.301, 0.301, 0,
0, 0.477, 0.301, 0, 0.477, 0, 0.477, 0.477, 0, 0.778, 0, 0.477,
0.477, 0, 0, 0, 0.477, 0.477, 0, 0.477, 0, 0, 0, 0, 0.477, 0.477,
0, 0, 0.477, 0.477, 0, 0, 0, 0, 0.477, 0, 0.477, 0, 0.477, 1.204,
1.176, 0, 0.301, 0.778, 0.301, 0.477, 0.477, 0, 0, 0.301, 0,
0, 0.602, 0.301, 0.602, 0.477, 0, 0.699, 0, 0.602, 0.602, 0,
0.699, 0, 0.602, 0.602, 0, 0.602, 0, 0.301, 0.845, 0, 0.602,
0.845, 0, 0.903, 0.602, 0.602, 0.954, 0, 0, 0.602, 0.602, 0.903,
0.602, 0.602, 0.602, 1.462, 0.954, 0.602, 0.778, 0.301, 0.477,
0.477, 0, 0, 0.301, 0, 0, 0.602, 0.301, 0.602, 0.477, 0, 0.301,
0.699, 0, 0.602, 0.602, 0, 0.699, 0, 0.602, 0.602, 0, 0.602,
0, 0.301, 0.845, 0, 0.602, 0.845, 0, 0.903, 0.602, 0.602, 0.954,
0, 0, 0.602, 0.602, 0.903, 0.602, 0.602, 0.602, 1.462, 0.954,
0.602, 0.699, 1.23, 0.477, 0.477, 0.477, 0, 0, 0.301, 0.602,
0.301, 0.602, 0.602, 0, 0.778, 0, 0, 0.602, 0, 0.477, 0.477,
0.602, 0.602, 0, 0.602, 0, 0, 1.114, 0, 0.699, 0.602, 0, 0, 0.602,
0.602, 0.699, 0.602, 0.301, 0.699, 0.602, 0.845, 0.699, 1, 1.146,
0.699), acetone = c(0.002, 0, 0.002, 0.003, 0.014, 0.002, 0.024,
0.006, 0.001, 0.041, 0.035, 0.014, 0.01, 0.005, 0.017, 0.002,
0.004, 0.002, 0.011, 0.019, 0, 0.01, 0.004, 0.002, 0.007, 0.004,
0.021, 0.022, 0.002, 0.005, 0.032, 0.003, 0.002, 0.004, 0.007,
0.091, 0.005, 0.002, 0.004, 0.001, 0.003, 0.005, 0.019, 0, 0.049,
0, 0.001, 0.001, 0, 0, 0, 0.095, 0.023, 0, 0.024, 0.031, 0, 0.058,
0.059, 0, 0.017, 0.008, 0, 0, 0.002, 0.007, 0.083, 0.011, 0,
0, 0.001, 0.057, 0, 0.059, 0.142, 0.01, 0, 0, 0.052, 0, 0, 0.041,
0, 0, 0, 0.002, 0, 0, 0.016, 0.016, 0.042, 0, 0.005, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0.007, 0, 0.001, 0.061, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0.015, 0, 0.025, 0, 0, 0, 0, 0.02, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.001, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0.001, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0.004, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.002, 0, 0, 0.002,
0, 0), days = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 94, 94, 94, 94, 94, 94, 94,
94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94,
94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94,
94, 94, 94, 94, 94), soil = c(31, 6, 12, 18, 2, 39, 1, 14, 4,
9, 16, 10, 28, 33, 8, 92, 25, 23, 20, 83, 66, 19, 27, 22, 95,
26, 21, 69, 30, 113, 15, 100, 38, 24, 110, 102, 34, 37, 7, 36,
17, 13, 29, 32, 90, 5, 3, 35, 31, 6, 12, 18, 2, 39, 1, 14, 4,
9, 16, 10, 28, 33, 8, 92, 25, 23, 20, 83, 66, 19, 27, 22, 95,
26, 21, 69, 30, 113, 15, 100, 38, 24, 110, 102, 34, 37, 7, 36,
17, 13, 29, 32, 90, 5, 3, 35, 6, 12, 18, 2, 39, 1, 14, 4, 9,
16, 10, 28, 33, 8, 31, 92, 25, 23, 20, 83, 66, 19, 27, 22, 95,
26, 21, 69, 30, 113, 15, 100, 38, 24, 110, 102, 34, 37, 7, 36,
17, 13, 29, 32, 90, 5, 3, 35, 31, 6, 12, 18, 2, 39, 4, 9, 16,
10, 28, 33, 8, 92, 25, 23, 20, 83, 66, 19, 27, 22, 95, 26, 21,
69, 30, 113, 15, 100, 38, 24, 110, 102, 34, 37, 7, 36, 17, 13,
29, 5, 3, 35), soil_type = c("org", "min", "org", "min", "min",
"min", "min", "org", "min", "org", "min", "min", "min", "min",
"min", "min", "min", "min", "min", "min", "org", "min", "min",
"min", "min", "min", "min", "min", "org", "min", "min", "org",
"min", "min", "min", "min", "org", "min", "min", "org", "min",
"org", "min", "min", "min", "org", "min", "min", "org", "min",
"org", "min", "min", "min", "min", "org", "min", "org", "min",
"min", "min", "min", "min", "min", "min", "min", "min", "min",
"org", "min", "min", "min", "min", "min", "min", "min", "org",
"min", "min", "org", "min", "min", "min", "min", "org", "min",
"min", "org", "min", "org", "min", "min", "min", "org", "min",
"min", "min", "org", "min", "min", "min", "min", "org", "min",
"org", "min", "min", "min", "min", "min", "org", "min", "min",
"min", "min", "min", "org", "min", "min", "min", "min", "min",
"min", "min", "org", "min", "min", "org", "min", "min", "min",
"min", "org", "min", "min", "org", "min", "org", "min", "min",
"min", "org", "min", "min", "org", "min", "org", "min", "min",
"min", "min", "org", "min", "min", "min", "min", "min", "min",
"min", "min", "min", "min", "org", "min", "min", "min", "min",
"min", "min", "min", "org", "min", "min", "org", "min", "min",
"min", "min", "org", "min", "min", "org", "min", "org", "min",
"org", "min", "min")), row.names = c(NA, -188L), class = "data.frame")
你可以试试 tidyverse
library(tidyverse)
library(ggpmisc)
library(broom)
想法是使用tidyr的nest、purrr的map以及boom的[预先计算p值=18=]函数。生成的 pvalue 被添加到数据框中。
df %>%
as_tibble() %>% # optional
nest(data =-days) %>% # calculate p values
mutate(p=map(data, ~lm(acetone~bacteria, data= .) %>%
broom::tidy() %>%
slice(2) %>%
pull(p.value))) %>%
unnest(p) # to show the pvalue output
# A tibble: 4 x 3
days data p
<dbl> <list> <dbl>
1 0 <tibble [48 x 4]> 0.955
2 10 <tibble [48 x 4]> 0.746
3 24 <tibble [48 x 4]> 0.475
4 94 <tibble [44 x 4]> 0.0152
最后，剧情。数据在各自的 geoms 中被过滤为 p<0.2。
df %>%
as_tibble() %>% # optional
nest(data =-days) %>% # calculate p values
mutate(p=map(data, ~lm(acetone~bacteria, data= .) %>%
broom::tidy() %>%
slice(2) %>%
pull(p.value))) %>%
unnest(cols = c(data, p)) %>%
ggplot(aes(bacteria, acetone)) +
geom_point(aes(shape=soil_type, color=soil_type, size=soil_type, fill=soil_type)) +
facet_wrap(~days, ncol = 4, scales = "free") +
geom_smooth(data = . %>% group_by(days) %>% filter(any(p<0.2)), method = "lm", formula = y~x, color="black") +
stat_poly_eq(data = . %>% group_by(days) %>% filter(any(p<0.2)),
aes(label = paste(stat(adj.rr.label),
stat(p.value.label),
sep = "*\", \"*")),
formula = formula,
rr.digits = 1,
p.digits = 1,
parse = TRUE,size=3.5) +
scale_fill_manual(values=c("#00AFBB", "brown")) +
scale_color_manual(values=c("black", "black")) +
scale_shape_manual(values=c(21, 24))+
scale_size_manual(values=c(2.4, 1.7))+
labs(shape="Soil type", color="Soil type", size="Soil type", fill="Soil type") +
theme_bw()
我简化了代码以展示如何轻松完成 stat_poly_eq() 的测试。为了能够测试 p-value，我们需要 stat return 数值而不是现成的格式化标签。使用手头的数值，我们可以将不需要的标签设置为 "" 并设置格式，然后手动格式化。所以这是部分答案...
ggplot(df,
aes(bacteria,
acetone)) +
geom_point(aes(shape=soil_type, color=soil_type,
fill=soil_type)) +
stat_poly_eq(aes(label = ifelse(stat(p.value) <= 0.2,
sprintf("R^2~`=`~%.2f*\", \"*P~`=`~%.2g",
stat(r.squared), stat(p.value)),
"")),
formula = formula,
output.type = "numeric",
size = 3.5,
parse = TRUE) +
theme_bw() +
facet_wrap(~days,
ncol = 4, scales = "free")
我使用 ggpmisc 包在绘图中显示线性回归模型。如果 p 值小于 0.2，我只希望在图中显示回归线、p 值和 r2 值。 @Ricardo Semião e Castro 用很棒的代码帮助了我（谢谢！），但它只是有时有效。它是否有效取决于满足 P<0.2 标准的回归模型的数量。关于如何编写代码以使其在 0、1 或 2 个模型的 P 值低于 P 时都有效的想法？
代码如下：
library(ggpmisc)
library(ggplot2)
# Below code is to ensure that only LM with p < 0.2 is displayed in the graph
names = c(0,0) #Create a starting point of a matrix for the group names
#For each group, run a lm to find if pvalue < 0.2
for(i in unique(df$days)){
lm = summary(lm(acetone~bacteria, df[df$days==i,]))
p = pf(lm$fstatistic[1], lm$fstatistic[2], lm$fstatistic[3], lower.tail=FALSE)
if(p < 0.2){names = rbind(names, c(i))} #Get the groups that pass
}
#names = names[-1,] #Remove starting point
#Create subset of df with groups where p < 0.2; looping in order to check pair by pair
df_P0.2 = numeric()
for(i in 1:nrow(names)){
df_P0.2 = rbind(df_P0.2,df[df$days%in%names[i,1],])
}
formula <- y~x
(plot <- ggplot(df,
aes(bacteria,
acetone)) +
geom_smooth(method = "lm",
formula = y~x, color="black", data = df_P0.2) +
geom_point(aes(shape=soil_type, color=soil_type, size=soil_type,
fill=soil_type)) +
scale_fill_manual(values=c("#00AFBB", "brown")) +
scale_color_manual(values=c("black", "black")) +
scale_shape_manual(values=c(21, 24))+
scale_size_manual(values=c(2.4, 1.7))+
labs(shape="Soil type", color="Soil type", size="Soil type", fill="Soil type") +
theme_bw() +
facet_wrap(~days,
ncol = 4, scales = "free")+
stat_poly_eq(data=df_P0.2,
aes(label = paste(stat(adj.rr.label),
stat(p.value.label),
sep = "*\", \"*")),
formula = formula,
rr.digits = 1,
p.digits = 1,
parse = TRUE,size=3.5))
这是数据：
df <- structure(list(bacteria = c(0.301, 1.079, 0, 0.301, 0.301, 0,
0, 0.477, 0.301, 0, 0.477, 0, 0.477, 0.477, 0, 0.778, 0, 0.477,
0.477, 0, 0, 0, 0.477, 0.477, 0, 0.477, 0, 0, 0, 0, 0.477, 0.477,
0, 0, 0.477, 0.477, 0, 0, 0, 0, 0.477, 0, 0.477, 0, 0.477, 1.204,
1.176, 0, 0.301, 0.778, 0.301, 0.477, 0.477, 0, 0, 0.301, 0,
0, 0.602, 0.301, 0.602, 0.477, 0, 0.699, 0, 0.602, 0.602, 0,
0.699, 0, 0.602, 0.602, 0, 0.602, 0, 0.301, 0.845, 0, 0.602,
0.845, 0, 0.903, 0.602, 0.602, 0.954, 0, 0, 0.602, 0.602, 0.903,
0.602, 0.602, 0.602, 1.462, 0.954, 0.602, 0.778, 0.301, 0.477,
0.477, 0, 0, 0.301, 0, 0, 0.602, 0.301, 0.602, 0.477, 0, 0.301,
0.699, 0, 0.602, 0.602, 0, 0.699, 0, 0.602, 0.602, 0, 0.602,
0, 0.301, 0.845, 0, 0.602, 0.845, 0, 0.903, 0.602, 0.602, 0.954,
0, 0, 0.602, 0.602, 0.903, 0.602, 0.602, 0.602, 1.462, 0.954,
0.602, 0.699, 1.23, 0.477, 0.477, 0.477, 0, 0, 0.301, 0.602,
0.301, 0.602, 0.602, 0, 0.778, 0, 0, 0.602, 0, 0.477, 0.477,
0.602, 0.602, 0, 0.602, 0, 0, 1.114, 0, 0.699, 0.602, 0, 0, 0.602,
0.602, 0.699, 0.602, 0.301, 0.699, 0.602, 0.845, 0.699, 1, 1.146,
0.699), acetone = c(0.002, 0, 0.002, 0.003, 0.014, 0.002, 0.024,
0.006, 0.001, 0.041, 0.035, 0.014, 0.01, 0.005, 0.017, 0.002,
0.004, 0.002, 0.011, 0.019, 0, 0.01, 0.004, 0.002, 0.007, 0.004,
0.021, 0.022, 0.002, 0.005, 0.032, 0.003, 0.002, 0.004, 0.007,
0.091, 0.005, 0.002, 0.004, 0.001, 0.003, 0.005, 0.019, 0, 0.049,
0, 0.001, 0.001, 0, 0, 0, 0.095, 0.023, 0, 0.024, 0.031, 0, 0.058,
0.059, 0, 0.017, 0.008, 0, 0, 0.002, 0.007, 0.083, 0.011, 0,
0, 0.001, 0.057, 0, 0.059, 0.142, 0.01, 0, 0, 0.052, 0, 0, 0.041,
0, 0, 0, 0.002, 0, 0, 0.016, 0.016, 0.042, 0, 0.005, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0.007, 0, 0.001, 0.061, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0.015, 0, 0.025, 0, 0, 0, 0, 0.02, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.001, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0.001, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0.004, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.002, 0, 0, 0.002,
0, 0), days = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 94, 94, 94, 94, 94, 94, 94,
94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94,
94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94,
94, 94, 94, 94, 94), soil = c(31, 6, 12, 18, 2, 39, 1, 14, 4,
9, 16, 10, 28, 33, 8, 92, 25, 23, 20, 83, 66, 19, 27, 22, 95,
26, 21, 69, 30, 113, 15, 100, 38, 24, 110, 102, 34, 37, 7, 36,
17, 13, 29, 32, 90, 5, 3, 35, 31, 6, 12, 18, 2, 39, 1, 14, 4,
9, 16, 10, 28, 33, 8, 92, 25, 23, 20, 83, 66, 19, 27, 22, 95,
26, 21, 69, 30, 113, 15, 100, 38, 24, 110, 102, 34, 37, 7, 36,
17, 13, 29, 32, 90, 5, 3, 35, 6, 12, 18, 2, 39, 1, 14, 4, 9,
16, 10, 28, 33, 8, 31, 92, 25, 23, 20, 83, 66, 19, 27, 22, 95,
26, 21, 69, 30, 113, 15, 100, 38, 24, 110, 102, 34, 37, 7, 36,
17, 13, 29, 32, 90, 5, 3, 35, 31, 6, 12, 18, 2, 39, 4, 9, 16,
10, 28, 33, 8, 92, 25, 23, 20, 83, 66, 19, 27, 22, 95, 26, 21,
69, 30, 113, 15, 100, 38, 24, 110, 102, 34, 37, 7, 36, 17, 13,
29, 5, 3, 35), soil_type = c("org", "min", "org", "min", "min",
"min", "min", "org", "min", "org", "min", "min", "min", "min",
"min", "min", "min", "min", "min", "min", "org", "min", "min",
"min", "min", "min", "min", "min", "org", "min", "min", "org",
"min", "min", "min", "min", "org", "min", "min", "org", "min",
"org", "min", "min", "min", "org", "min", "min", "org", "min",
"org", "min", "min", "min", "min", "org", "min", "org", "min",
"min", "min", "min", "min", "min", "min", "min", "min", "min",
"org", "min", "min", "min", "min", "min", "min", "min", "org",
"min", "min", "org", "min", "min", "min", "min", "org", "min",
"min", "org", "min", "org", "min", "min", "min", "org", "min",
"min", "min", "org", "min", "min", "min", "min", "org", "min",
"org", "min", "min", "min", "min", "min", "org", "min", "min",
"min", "min", "min", "org", "min", "min", "min", "min", "min",
"min", "min", "org", "min", "min", "org", "min", "min", "min",
"min", "org", "min", "min", "org", "min", "org", "min", "min",
"min", "org", "min", "min", "org", "min", "org", "min", "min",
"min", "min", "org", "min", "min", "min", "min", "min", "min",
"min", "min", "min", "min", "org", "min", "min", "min", "min",
"min", "min", "min", "org", "min", "min", "org", "min", "min",
"min", "min", "org", "min", "min", "org", "min", "org", "min",
"org", "min", "min")), row.names = c(NA, -188L), class = "data.frame")
你可以试试 tidyverse
library(tidyverse)
library(ggpmisc)
library(broom)
想法是使用tidyr的nest、purrr的map以及boom的[预先计算p值=18=]函数。生成的 pvalue 被添加到数据框中。
df %>%
as_tibble() %>% # optional
nest(data =-days) %>% # calculate p values
mutate(p=map(data, ~lm(acetone~bacteria, data= .) %>%
broom::tidy() %>%
slice(2) %>%
pull(p.value))) %>%
unnest(p) # to show the pvalue output
# A tibble: 4 x 3
days data p
<dbl> <list> <dbl>
1 0 <tibble [48 x 4]> 0.955
2 10 <tibble [48 x 4]> 0.746
3 24 <tibble [48 x 4]> 0.475
4 94 <tibble [44 x 4]> 0.0152
最后，剧情。数据在各自的 geoms 中被过滤为 p<0.2。
df %>%
as_tibble() %>% # optional
nest(data =-days) %>% # calculate p values
mutate(p=map(data, ~lm(acetone~bacteria, data= .) %>%
broom::tidy() %>%
slice(2) %>%
pull(p.value))) %>%
unnest(cols = c(data, p)) %>%
ggplot(aes(bacteria, acetone)) +
geom_point(aes(shape=soil_type, color=soil_type, size=soil_type, fill=soil_type)) +
facet_wrap(~days, ncol = 4, scales = "free") +
geom_smooth(data = . %>% group_by(days) %>% filter(any(p<0.2)), method = "lm", formula = y~x, color="black") +
stat_poly_eq(data = . %>% group_by(days) %>% filter(any(p<0.2)),
aes(label = paste(stat(adj.rr.label),
stat(p.value.label),
sep = "*\", \"*")),
formula = formula,
rr.digits = 1,
p.digits = 1,
parse = TRUE,size=3.5) +
scale_fill_manual(values=c("#00AFBB", "brown")) +
scale_color_manual(values=c("black", "black")) +
scale_shape_manual(values=c(21, 24))+
scale_size_manual(values=c(2.4, 1.7))+
labs(shape="Soil type", color="Soil type", size="Soil type", fill="Soil type") +
theme_bw()
我简化了代码以展示如何轻松完成 stat_poly_eq() 的测试。为了能够测试 p-value，我们需要 stat return 数值而不是现成的格式化标签。使用手头的数值，我们可以将不需要的标签设置为 "" 并设置格式，然后手动格式化。所以这是部分答案...
ggplot(df,
aes(bacteria,
acetone)) +
geom_point(aes(shape=soil_type, color=soil_type,
fill=soil_type)) +
stat_poly_eq(aes(label = ifelse(stat(p.value) <= 0.2,
sprintf("R^2~`=`~%.2f*\", \"*P~`=`~%.2g",
stat(r.squared), stat(p.value)),
"")),
formula = formula,
output.type = "numeric",
size = 3.5,
parse = TRUE) +
theme_bw() +
facet_wrap(~days,
ncol = 4, scales = "free")