Probit Regression modelling in R

Question

[1769mkc]

I have already made a post in stack, wont; make a duplicate here, so Im giving the link here probit modelling question

I would be really glad if I get input about it since im not sure if im doing it correctly or not ..

so df is my original data frame so ,im making d2 to change my sample into factors
  

  conc<- c(6 , 5, 4,3,2,1,0,-1,-2)
    IMRS <- c(1,1,0.23,1,1,0.8,0.4,0.5,0.0)
    S18S <- c(1,1,.69,1,1,0.33,0.4,0.0,0.0)
     df <- data.frame(conc,IMRS,S18S)

head(df)
  conc IMRS S18S
1    6 1.00 1.00
2    5 1.00 1.00
3    4 0.23 0.69
4    3 1.00 1.00
5    2 1.00 1.00
6    1 0.80 0.33



     library(tidyr)
     d2=gather(df,SAMPLE,y,IMRS,S18S,factor_key=T)
    head(d2)

conc SAMPLE    y
1    6   IMRS 1.00
2    5   IMRS 1.00
3    4   IMRS 0.23
4    3   IMRS 1.00
5    2   IMRS 1.00
6    1   IMRS 0.80

    glm.out=glm(SAMPLE~conc+y,d2,family = binomial(link = "probit"))
    summary(glm.out) 


     library(ggplot2)
     lr_data <- data.frame(predictor=glm.out$linear.predictors,
                           prob=glm.out$fitted.values, SAMPLE=d2$SAMPLE)


     ggplot(lr_data, aes(x=predictor, y=prob, color=SAMPLE)) + geom_point(size=10)+
       geom_line(linetype = "dashed",lwd = 0.5)+geom_hline(yintercept = 0.65)

Build a model that predicts the level of your dependent variable (x) based on concentration (y)

So am i doing it in opposite manner ? or it wont matter .let me know

"Predict values from the model using predict()"

Can you plug that into my code how do i use or do that? because I been through the tutorials im not sure/cofident about using the

predict()

[Kevin Blighe]

Hi Krushnach, there is not enough information provided - perhaps not even you is sure of the experiment? It is also confusing (looking at the post on StackExchange) because you produce an object called df and then one called d2. From where did you obtain the figure that you posted?

The standard procedure would be:

1. Build a model that predicts the level of your dependent variable (x) based on concentration (y)
2. Predict values from the model using predict()
3. Plot the original values and also the predicted values to see how they fit (visually)

[1769mkc]

updated my question with code..the figure i got from a paper where they did this probit analysis

[Kevin Blighe]

Okay, can you share the paper? I am interested to see it

[1769mkc]

hi kevin I don;t have acess to that figure i followed your procedure and I get something similar to that

 curve(plogis( 0.1792 + 0.8259*x), min(df$A), 
      max(df$A), add=TRUE, lwd=2, lty=3)

Since i took the example from stack I wanted to ask what is the equivalent of this plogis for probit ?

---

[GenoMax]

Whoever up-voted @Kevin's comment above should consider the following.

Upvoting posts/comments is meant to be used in cases where the content of the post/comment contributes to solving original question/adds useful information. Upvoting "can you share the paper?" above does not help anyone and is a misuse of the voting system.

[1769mkc]

okay im sorry i hit it, my apology now i reversed it