Kolmogorov smirnov in r - cannot compute correct p-values with ties

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SUMMARY

The discussion centers on the challenges of computing p-values using the Kolmogorov-Smirnov test in R when dealing with datasets that contain ties. The user encounters an error indicating that correct p-values cannot be computed due to the presence of duplicate values in their datasets, which consist of 2000 and 50000 observations, respectively. A suggestion is made to empirically test the sensitivity of the p-value by adding small random perturbations to the data, allowing for a better understanding of the p-value's validity in the presence of ties.

PREREQUISITES
  • Understanding of the Kolmogorov-Smirnov test
  • Familiarity with R programming language
  • Knowledge of statistical significance and p-values
  • Experience with data manipulation in R
NEXT STEPS
  • Explore the R documentation for the ks.test function
  • Learn about handling ties in statistical tests
  • Investigate methods for perturbing data to assess p-value sensitivity
  • Research alternative statistical tests for comparing distributions with ties
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Statisticians, data analysts, and R programmers who are working with distribution comparisons and need to understand the implications of ties on p-value calculations.

joanne34567
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Hi,
I'm trying to use the kolmogorov smirnov test in in R to compare one distribution with another. I'm getting the following error: cannot compute correct p-values with ties
I think this is because the dataset that I am using has in the first instance around 2000 values, and the second, 50000 values. A number of these are inherently going to be replicates of another number in the series (i.e. "ties"). I'm just wondering if this has implcations for the p value I have? Is the p value valid?
Cheers all
 
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Did you read the R documentation for the ks.test function?

You could test the sensitivity of the p-value empirically. Add small random perturbations to your data to generate new data sets that have more digits. See how much the p value changes.
 

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