Integrate a new lm into an existing lm plot

Question

[amandinelecerfdefer]

Hello,

I use an R code to create linear regression plots of one of my variables for each of my files.

My code works very well but I would like to add a new model (in other words, I would like to show a second curve in blue for example).

here is the code used to form my simple single curve regression plot:

work<- '/Volumes/les_3-cohortes/Paris/global'  #faire 1dossier par score 
    graphe<- '/Volumes/les_3-cohortes/Paris/global/graphe'

    library(devtools)
    library(ggplot2)
    library(easyGgplot2)

    ggplotRegression <- function (fit) {

      require(ggplot2)

      ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) + 
        geom_point() +
        stat_smooth(method = "lm", col = "red") +
        labs(title = paste("R2 = ",signif(summary(fit)$adj.r.squared, 5),
                           " P =",signif(summary(fit)$coef[2,4], 5)))
    }


    setwd(work)
    files <- list.files(path = "data", pattern = (".csv$"))


    for (k in 1:length(files)) {
      fname <- files[k]
      cat(paste0("Now analyse data/", fname, "...\n"))
      fichier <- read.csv2(paste0("data/", fname), header = T, stringsAsFactors = F, dec = ",")
      setwd(graphe)  #faire 1dossier par fichier 
      a<- gsub(pattern = "\\.csv$", "", fname)

      fit1 <- lm(EGFR_12 ~ score, data = fichier, na.action=na.omit)
      p1<-ggplotRegression(fit1)

      fit2 <- lm(EGFR_24 ~ score, data = fichier, na.action=na.omit)
      p2<-ggplotRegression(fit2)

      fit3 <- lm(EGFR_36 ~ score, data = fichier, na.action=na.omit)
      p3<-ggplotRegression(fit3)

      jpeg(paste0(a, ".jpeg"), width = 40, height =12, units="cm", quality=100, res=300)
      p<- ggplot2.multiplot(p1,p2,p3, cols=3)
      print(p)
      dev.off()


      setwd(work)
    }

Here is an example of a file:

score;AMS;EGFR_12;EGFR_24;EGFR_36;Age_donneur;Paire
483;483;67,56217938;53,61312383;52,93430604;68;1
454;454;53,28459074;57,23583761;43,94840102;58;2
751;751;23,0301249;30,99633423;21,9535767;58;3

plot obtained :

I have therefore performed for each EGFR variable an lm with score but now I would like to add on the same plot a blue lm representing the regression of AMS with each EGFR variable. I tried for each variable to create a model1 of lm(model1 <- lm(EGFR_12 ~ AMS, data = file, na.action=na.omit) and add it via the ggplotRegression function:

ggplotRegression <- function (fit) {
  require(ggplot2)


  ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) + 
    geom_point() +
    stat_smooth(method = "lm", col = "red") +
    labs(title = paste("R2 = ",signif(summary(fit)$adj.r.squared, 5),
                       #"Intercept =",signif(fit$coef[[1]],5 ),
                       #" Slope =",signif(fit$coef[[2]], 5),
                       " P =",signif(summary(fit)$coef[2,4], 5)))

  + geom_line(data=pred(model1), color="blue") 
}

Will you be able to help me?

Thank you. Thank you.

Answer 1

[Kevin Blighe]

You should be able to do this by following the solution here:

• https://stackoverflow.com/questions/40600824/how-to-apply-geom-smooth-for-every-group

Kevin