MergeGUI (version 0.2-1)

scale_kstest: Compute the p-values of the Kolmogorov-Smirnov tests between different sources for each variable. This function is used to detect whether the matched variables from different files have different distributions. For each variable, it will compute the pairwise KS-test p-values among the sources, then report the lowest p-value as the indice for this variable.

Description

Compute the p-values of the Kolmogorov-Smirnov tests between different sources for each variable. This function is used to detect whether the matched variables from different files have different distributions. For each variable, it will compute the pairwise KS-test p-values among the sources, then report the lowest p-value as the indice for this variable.

Usage

scale_kstest(nametable.class, dataset.class, name.class, varclass = NULL)

Arguments

nametable.class

A matrix of the matched variable names. The number of columns is equal to the number of files. Each row represents a variable that is going to be merged. Any elements except NA in nametable.class must be the variable names in dataset.class.

dataset.class

The dataset list. The length of the list is equal to the number of files, and the order of the list is the same as the order of columns in nametable.class.

name.class

A character vector of variable names. The length of the vector must be equal to the number of rows in nametable.class. Since the variable names in nametable.class may not be consistent, name.class is needed to name the variables.

varclass

A character vector of variable classes. The length of the vector must be equal to the number of rows in nametable.class. All the classes should be in "numeric", "integer", "factor", and "character". Default to be null, then it will be determined by var.class.

Value

A vector of p-values from the KS-test for each variable.The p-values are between 0 and 1, or equal to 9 if one of more groups only have NA's.

Examples

a = data.frame(aa = 1:5, ab = LETTERS[6:2], ac = as.logical(c(0, 1, 0, NA, 0)))
b = data.frame(b1 = letters[12:14], b2 = 3:1)
dat = list(a, b)
name = matrix(c("ab", "aa", "ac", "b1", "b2", NA), ncol = 2)
colnames(name) = c("a", "b")
newname = c("letter", "int", "logic")
scale_kstest(name, dat, newname)