covDS {dsBase}

R Documentation

Computes the sum of each variable and the sum of products for each pair of variables

Description

This function computes the sum of each vector of variable and the sum of the products of each two variables (i.e. the scalar product of each two vectors).

Usage

covDS(x = NULL, y = NULL, use = NULL)

Arguments

x	a character, the name of a vector, matrix or dataframe of variable(s) for which the covariance(s) and the correlation(s) is (are) going to calculated for.
y	NULL (default) or the name of a vector, matrix or dataframe with compatible dimensions to x.
use	a character string giving a method for computing covariances in the presence of missing values. This must be one of the strings "casewise.complete" or "pairwise.complete". If use is set to 'casewise.complete' then any rows with missing values are omitted from the vector, matrix or dataframe before the calculations of the sums. If use is set to 'pairwise.complete' (which is the default case set on the client-side), then the sums of products are computed for each two variables using only the complete pairs of observations on the two variables.

Details

computes the sum of each vector of variable and the sum of the products of each two variables

Value

a list that includes a matrix with elements the sum of products between each two variables, a matrix with elements the sum of the values of each variable, a matrix with elements the number of complete cases in each pair of variables, a list with the number of missing values in each variable separately (columnwise) and the number of missing values casewise or pairwise depending on the arqument use, and an error message which indicates whether or not the input variables pass the disclosure controls. The first disclosure control checks that the number of variables is not bigger than a percentage of the individual-level records (the allowed percentage is pre-specified by the 'nfilter.glm'). The second disclosure control checks that none of them is dichotomous with a level having fewer counts than the pre-specified 'nfilter.tab' threshold. If any of the input variables do not pass the disclosure controls then all the output values are replaced with NAs.

Author(s)

Amadou Gaye, Paul Burton, and Demetris Avraam for DataSHIELD Development Team

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