Description Usage Arguments Value Author(s) Examples
Compute the pvalues of the KolmogorovSmirnov 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 KStest pvalues among the sources, then report the lowest pvalue as the indice for this variable.
1  scale_kstest(nametable.class, dataset.class, name.class, varclass = NULL)

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

A vector of pvalues from the KStest for each variable.The pvalues are between 0 and 1, or equal to 9 if one of more groups only have NA's.
Xiaoyue Cheng <[email protected]>
1 2 3 4 5 6 7  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)

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