Identifying data points above fixed effects regression using data.table - r

Question

I want to identify the data points above a regression line. I have a panel data set which I have fit a fixed effects model:
data <- data.frame(ID = c(1,1,1,1,2,2,3,3,3),
year = c(1,2,3,4,1,2,1,2,3),
progenyMean = c(90,78,92,69,86,73,82,85,91),
damMean = c(89,89,72,98,95,92,94,87,89)
ID, year, progenyMean, damMean
1, 1, 70, 69
1, 2, 68, 69
1, 3, 72, 72
1, 4, 69, 68
2, 1, 76, 75
2, 2, 73, 80
3, 1, 72, 74
3, 2, 75, 67
3, 3, 71, 69
# Fixed Effects Model in plm
fixed <- plm(progenyMean ~ damMean, data, model= "within", index = c("ID","year"))
I have plotted progenyMean vs damMean with the fixed effects regression line:
I want to identify the ID's above this regression line.
I have computed the predicted values of the fixed effects model using the following code (based off code from this post)
fitted <- as.numeric(fixed$model[[1]] - fixed$residuals)
> fitted
[1] 71.24338 79.03766 74.86613 71.34263 70.83020 71.56797 72.17324 74.54755 71.16720 73.37487
[11] 70.58863 69.27203 71.05852 59.72911 63.43947 68.69871 67.25271 75.68397 76.30475 81.12128
Is it possible to identify the ID's above the fixed effects regression line using the predicted values above and data.table in R?

Answer 1

Use residuals function. Positive residual = points above the line, negative = points below the line.
library(plm)
library(tidyverse)
library(ggplot2)
data <- data.frame(ID = c(1,1,1,1,2,2,3,3,3),
year = c(1,2,3,4,1,2,1,2,3),
progenyMean = c(90,78,92,69,86,73,82,85,91),
damMean = c(89,89,72,98,95,92,94,87,89))
fixed <- plm(progenyMean ~ damMean, data, model= "within", index = c("ID","year"))
residuals(fixed)
data %>% ggplot(aes(damMean, progenyMean)) +
geom_point(data=data %>% filter(residuals(fixed)>0), col="red")+
geom_point(data=data %>% filter(residuals(fixed)<0), col="blue")
data %>% mutate(
test = ifelse(residuals(fixed)>0, "up", "down") %>% factor()
) %>% group_by(test) %>% summarise(
n = n()
)