Hello, I am running a model with four categories and want predicted
probabilities in each category. Now for this example I wont give a
counterfactual just the training data is fine but is there anyway to get a
confidence interval around the predicted probabilities in each group? I have
tried but it gives me probabilities and I have used interval="confidence",
level=.095 and then interval = "prediction". Below is a sample of my data
and my code I am trying to run (its from an open access public data set; I
tried to make the size as small as possible, sorry for its length).

 

polr.result<-polr(ordered(tvwatch)~ses+testscores,method="probit",Hess =
T,data=testdata)

polr.predict<-predict(polr.result,type="probs",interval="confidence",level=.
95)

 

structure(list(tvwatch = c(2L, 2L, 1L, 4L, 2L, 4L, 3L, 2L, 3L, 

2L, 3L, 4L, 4L, 3L, 4L, 3L, 2L, 1L, 3L, 1L, 2L, 3L, 4L, 4L, 1L, 

1L, 2L, 2L, 4L, 4L, 2L, 1L, 3L, 3L, 3L, 2L, 4L, 2L, 1L, 1L, 1L, 

1L, 2L, 3L, 4L, 4L, 2L, 1L, 2L, 2L), ses = c(-0.529, -0.377, 

-0.859, -0.191, -0.319, -0.292, -0.601, -0.07, 0.198, 0.096, 

0.136, -0.101, 0.11, -0.182, -0.323, 0.205, 0.21, 0.749, -0.273, 

0.66, 0.009, -0.374, -0.094, -0.427, 1.369, -1.306, 0.611, 0.392, 

-0.371, 1.059, 1.308, -0.89, -1.741, -0.169, 0.13, -0.698, 0.385, 

-0.067, -0.386, 0.813, 0.997, 1.46, 1.196, -0.723, -0.612, 0.119, 

1.421, -1.02, -0.807, 1.33), testscores = c(53.38, 57.91, 54.64, 

45.67, 58.74, 57.55, 63.78, 59.97, 51.41, 49.54, 65.82, 44.04, 

45.8, 56.67, 35.6, 50.41, 45.18, 61.22, 61.24, 66.58, 64.91, 

40.79, 41.77, 46.51, 59.83, 49.95, 58.1, 54.53, 58.31, 69.92, 

66.4, 50.94, 51.23, 47.45, 37.93, 59.66, 60.59, 55.11, 40.65, 

67.89, 52.54, 61.76, 69.71, 44.37, 43.53, 45.89, 75.81, 53.18, 

51.85, 58.03)), .Names = c("tvwatch", "ses", "testscores"), row.names =
c(1L, 

2L, 3L, 4L, 5L, 6L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 18L, 

19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 28L, 29L, 30L, 31L, 32L, 

34L, 35L, 38L, 39L, 40L, 41L, 42L, 44L, 45L, 46L, 47L, 48L, 49L, 

50L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L), class = "data.frame")

 

 

-------------------------------------------

Joe King, M.A.

Ph.D. Student 

University of Washington - Seattle

206-913-2912  

 <mailto:jp@joepking.com> jp@joepking.com

-------------------------------------------

Ad astra per aspera  - "Through hardships to the stars"

 


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