On this R-data statistics page, you will find information about the polyps data set which pertains to Familial Andenomatous Polyposis . The polyps data set is found in the HSAUR R package. You can load the polyps data set in R by issuing the following command at the console data("polyps"). This will load the data into a variable called polyps. If R says the polyps data set is not found, you can try installing the package by issuing this command install.packages("HSAUR") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the polyps R data set. The size of this file is about 309 bytes.

Familial Andenomatous Polyposis

Description

Data from a placebo-controlled trial of a non-steroidal anti-inflammatory drug in the treatment of familial andenomatous polyposis (FAP).

Usage

data("polyps")

Format

A data frame with 20 observations on the following 3 variables.

number

number of colonic polyps at 12 months.

treat

treatment arms of the trail, a factor with levels placebo and drug.

age

the age of the patient.

Details

Giardiello et al. (1993) and Piantadosi (1997) describe the results of a placebo-controlled trial of a non-steroidal anti-inflammatory drug in the treatment of familial andenomatous polyposis (FAP). The trial was halted after a planned interim analysis had suggested compelling evidence in favour of the treatment. Here we are interested in assessing whether the number of colonic polyps at 12 months is related to treatment and age of patient.

Source

F. M. Giardiello, S. R. Hamilton, A. J. Krush, S. Piantadosi, L. M. Hylind, P. Celano, S. V. Booker, C. R. Robinson and G. J. A. Offerhaus (1993), Treatment of colonic and rectal adenomas with sulindac in familial adenomatous polyposis. New England Journal of Medicine, 328(18), 1313–1316.

S. Piantadosi (1997), Clinical Trials: A Methodologic Perspective. John Wiley \& Sons, New York.

Examples

  data("polyps", package = "HSAUR")
  plot(number ~ age, data = polyps, pch = as.numeric(polyps$treat))
  legend(40, 40, legend = levels(polyps$treat), pch = 1:2, bty = "n")

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Dataset imported from https://www.r-project.org.