ds.skewness: Calculates the skewness of a server-side numeric variable

In datashield/dsBaseClient: DataSHIELD Client Functions

Calculates the skewness of a server-side numeric variable

Description

This function calculates the skewness of a numeric variable that is stored on the server-side (Opal server).

Usage

ds.skewness(x = NULL, method = 1, type = "both", datasources = NULL)

Arguments

x	a character string specifying the name of a numeric variable.
method	an integer value between 1 and 3 selecting one of the algorithms for computing skewness. For more information see Details. The default value is set to 1.
type	a character string which represents the type of analysis to carry out. type can be set as: 'combine', 'split' or 'both'. For more information see Details. The default value is set to 'both'.
datasources	a list of DSConnection-class objects obtained after login. If the datasources argument is not specified the default set of connections will be used: see datashield.connections_default.

Details

This function is similar to the function skewness in R package e1071.

The function calculates the skewness of an input variable x with three different methods:
(1) If method is set to 1 the following formula is used skewness= \frac{\sum_{i=1}^{N} (x_i - \bar(x))^3 /N}{(\sum_{i=1}^{N} ((x_i - \bar(x))^2) /N)^(3/2) }, where \bar{x} is the mean of x and N is the number of observations.
(2) If method is set to 2 the following formula is used skewness= \frac{\sum_{i=1}^{N} (x_i - \bar(x))^3 /N}{(\sum_{i=1}^{N} ((x_i - \bar(x))^2) /N)^(3/2) } * \frac{\sqrt(N(N-1)}{n-2}.
(3) If method is set to 3 the following formula is used skewness= \frac{\sum_{i=1}^{N} (x_i - \bar(x))^3 /N}{(\sum_{i=1}^{N} ((x_i - \bar(x))^2) /N)^(3/2) } * (\frac{N-1}{N})^(3/2).

The type argument can be set as follows:
(1) If type is set to 'combine', 'combined', 'combines' or 'c', the global skewness is returned.
(2) If type is set to 'split', 'splits' or 's', the skewness is returned separately for each study.
(3) If type is set to 'both' or 'b', both sets of outputs are produced.

If x contains any missing value, the function removes those before the calculation of the skewness.

Server functions called: skewnessDS1 and skewnessDS2

Value

ds.skewness returns a matrix showing the skewness of the input numeric variable, the number of valid observations and the validity message.

Author(s)

Demetris Avraam, for DataSHIELD Development Team

Examples

## Not run: 
  ## Version 6, for version 5 see the Wiki
  
  # connecting to the Opal servers

  require('DSI')
  require('DSOpal')
  require('dsBaseClient')

  builder <- DSI::newDSLoginBuilder()
  builder$append(server = "study1", 
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "CNSIM.CNSIM1", driver = "OpalDriver")
  builder$append(server = "study2", 
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "CNSIM.CNSIM2", driver = "OpalDriver")
  builder$append(server = "study3",
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "CNSIM.CNSIM3", driver = "OpalDriver")
  logindata <- builder$build()
  
  connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D") 
  
  #Calculate the skewness of LAB_TSC numeric variable for each study separately and combined
  
  ds.skewness(x = "D$LAB_TSC",
              method = 1, 
              type = "both",
             datasources = connections)
  
  # Clear the Datashield R sessions and logout                 
  DSI::datashield.logout(connections) 
  

## End(Not run) 

datashield/dsBaseClient documentation built on Nov. 16, 2024, 2:07 p.m.