ds.cor: Computes correlation between two or more vectors

Description Usage Arguments Details Value Author(s) Examples

Description

This is similar to the R base function 'cor'.

Usage

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ds.cor(x = NULL, y = NULL, naAction = "pairwise.complete.obs",
  datasources = NULL)

Arguments

x

a character, the name of a numerical vector, matrix or dataframe

y

NULL (default) or the name of a vector, matrix or data frame with compatible dimensions to x.

naAction

a character string giving a method for computing covariances in the presence of missing values. This must be one of the strings: "everything", "all.obs", "complete.obs", "na.or.complete", or "pairwise.complete.obs". The default value is set to "pairwise.complete.obs"

datasources

a list of opal object(s) obtained after login in to opal servers; these objects hold also the data assign to R, as dataframe, from opal datasources.

Details

In addition to computing correlations this function, unlike the R base function 'cor', produces a table outlining the number of complete cases to allow for the user to make a decision about the 'relevance' of the correlation based on the number of complete cases included in the correlation calculations.

Value

a list containing the results of the test

Author(s)

Gaye, A.

Examples

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{

  # load that contains the login details
  data(logindata)

  # login and assign specific variable(s)
  # (by default the assigned dataset is a dataframe named 'D')
  myvar <- list('LAB_HDL', 'LAB_TSC', 'GENDER')
  opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)

  # Example 1: generate the correlation matrix for the assigned dataset 'D'
  # which contains 4 vectors (2 continuous and 1 categorical)
  ds.cor(x='D')

  # Example 2: calculate the correlation between two vectors (first assign some vectors from the dataframe 'D')
  ds.assign(newobj='labhdl', toAssign='D$LAB_HDL')
  ds.assign(newobj='labtsc', toAssign='D$LAB_TSC')
  ds.assign(newobj='gender', toAssign='D$GENDER')
  ds.cor(x='labhdl', y='labtsc')
  ds.cor(x='labhdl', y='gender')

  # clear the Datashield R sessions and logout
  datashield.logout(opals)

}

datashield/dsStatsClient documentation built on May 14, 2019, 7:52 p.m.