Hi R Users, I have two vectors, x and y, of equal length representing two types of data from two studies. I would like to test if they are similar enough to use them interchangeably. No assumptions about distributions can be made (initial tests clearly show that they are not normal). Here some result:
Two-sample Kolmogorov-Smirnov test data: x and y D = 0.1091, p-value < 2.2e-16 alternative hypothesis: two-sided Warning message: In ks.test(x[1:nx], y[1:nx], exact = FALSE) : cannot compute correct p-values with ties Here some questions: a) What does the error message means and what does it imply? b) The data is very noisy and the initial result shows that there is no relation between x and y. Is there a way to calculate and effect size? c) Can the p-value be used, when running tests over a large amount of different data sets, as a metric for ranking similarity between x and y data sets? Best R. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.