spcor {ppcor}

Semi-partial (part) correlation

Description

The function spcor can calculate the pairwise semi-partial (part) correlations for each pair of variables given others. In addition, it gives us the p value as well as statistic for each pair of variables.

Usage

spcor(x, method = c("pearson", "kendall", "spearman"))

Arguments

x

a matrix or data fram.

method

a character string indicating which semi-partial (part) correlation coefficient is to be computed. One of "pearson" (default), "kendall", or "spearman" can be abbreviated.

Details

Semi-partial correlation is the correlation of two variables with variation from a third or more other variables removed only from the second variable. When the determinant of variance-covariance matrix is numerically zero, Moore-Penrose generalized matrix inverse is used. In this case, no p-value and statistic will be provided if the number of variables are greater than or equal to the sample size.

Value

estimate

a matrix of the semi-partial (part) correlation coefficient between two variables

p.value

a matrix of the p value of the test

statistic

a matrix of the value of the test statistic

n

the number of samples

gn

the number of given variables

method

the correlation method used

Note

Missing values are not allowed.

Author(s)

Seongho Kim <[e-mail]>

References

Kim, S. (2015) ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients. Communications for Statistical Applications and Methods, 22(6), 665-674.

See Also

spcor.test, pcor, pcor.test

Examples

# data
y.data <- data.frame(
				hl=c(7,15,19,15,21,22,57,15,20,18),
				disp=c(0.000,0.964,0.000,0.000,0.921,0.000,0.000,1.006,0.000,1.011),
				deg=c(9,2,3,4,1,3,1,3,6,1),
				BC=c(1.78e-02,1.05e-06,1.37e-05,7.18e-03,0.00e+00,0.00e+00,0.00e+00
              ,4.48e-03,2.10e-06,0.00e+00)
			)

# semi-partial (part) correlation
spcor(y.data)