
PARTIAL CORRELATION MATRIXName:
The algorithm for computing the partial correlations is:
Alternatively, you can compute the CDF or the pvalue for the partial correlation coefficients (i.e., to see if the partial correlation coefficient is significantly different than zero). The CDF value is
where FCDF is the F cumulative distribution function with 1 and N  NC degrees of freedom (N is the number of observations and NC is the number of columns in the input matrix) and
with r denoting the computed partial correlation. The pvalue is 1  CDF.
<SUBSET/EXCEPT/FOR qualification> where <mat1> is a matrix for which the partial correlations are to be computed; <mat2> is a matrix where the resulting partial correlations are saved; and where the <SUBSET/EXCEPT/FOR qualification> is optional and rarely used in this context.
<SUBSET/EXCEPT/FOR qualification> where <mat1> is a matrix for which the partial correlation CDF's are to be computed; <mat2> is a matrix where the resulting partial correlation CDF's are saved; and where the <SUBSET/EXCEPT/FOR qualification> is optional and rarely used in this context. This syntax computes the CDF's of the partial correlation coefficients.
<SUBSET/EXCEPT/FOR qualification> where <mat1> is a matrix for which the partial correlation pvalue's are to be computed; <mat2> is a matrix where the resulting partial correlation pvalues's are saved; and where the <SUBSET/EXCEPT/FOR qualification> is optional and rarely used in this context. This syntax computes the pvalues of the partial correlation coefficients.
To specify a partial correlation matrix based on rows rather than columns, enter the command
To reset column based partial correlations, enter
BIWEIGHT MIDCORRELATION/PERCENTAGE BEND/ KENDALL TAU> To see the definitions for these, enter
. This data is from page 202 of . . Peavy, Bremer, Varner, Hogben (1986), "OMNITAB 80: . An Interpretive System for Statistical and Numerical . Data Analysis," NBS Special Publication 701. . . Original source of the data is from . Draper and Smith (1981), "Applied Regression Analysis", . Wiley, p. 373. . dimension 40 columns . read matrix m 42.2 11.2 31.9 167.1 48.6 10.6 13.2 174.4 42.6 10.6 28.7 160.8 39.0 10.4 26.1 162.0 34.7 9.3 30.1 140.8 44.5 10.8 8.5 174.6 39.1 10.7 24.3 163.7 40.1 10.0 18.6 174.5 45.9 12.0 20.4 185.7 end of data . set write decimals 4 let pcorr = partial correlation matrix m print pcorrThe following output is generated. MATRIX PCORR  4 ROWS  4 COLUMNS VARIABLESPCORR1 PCORR2 PCORR3 PCORR4 1.0000 0.4317 0.4566 0.1054 0.4317 1.0000 0.6972 0.7268 0.4566 0.6972 1.0000 0.6478 0.1054 0.7268 0.6478 1.0000
Date created: 01/23/2013 