Description Usage Arguments Details Value Author(s) References See Also Examples

A straightforward application of matrix algebra to remove the effect of the variables in the y set from the x set. Input may be either a data matrix or a correlation matrix. Variables in x and y are specified by location.

1 | ```
partial.r(m, x, y)
``` |

`m` |
A data or correlation matrix |

`x` |
The variable numbers associated with the X set. |

`y` |
The variable numbers associated with the Y set |

It is sometimes convenient to partial the effect of a number of variables (e.g., sex, age, education) out of the correlations of another set of variables. This could be done laboriously by finding the residuals of various multiple correlations, and then correlating these residuals. The matrix algebra alternative is to do it directly.
To find the confidence intervals and "significance" of the correlations, use the `corr.p`

function with n = n - s where s is the numer of covariates.

The matrix of partial correlations.

William Revelle

Revelle, W. (in prep) An introduction to psychometric theory with applications in R. To be published by Springer. (working draft available at http://personality-project.org/r/book/

`mat.regress`

for a similar application for regression

1 2 3 4 5 |

```
V1 V2 V3 V4 V5
V1 1.00 0.56 0.48 0.40 0.35
V2 0.56 1.00 0.42 0.35 0.30
V3 0.48 0.42 1.00 0.30 0.26
V4 0.40 0.35 0.30 1.00 0.42
V5 0.35 0.30 0.26 0.42 1.00
Call:corr.p(r = par.r, n = 98)
Correlation matrix
partial correlations
V1 V3 V5
V1 1.00 0.29 0.14
V3 0.29 1.00 0.10
V5 0.14 0.10 1.00
Sample Size
[1] 98
Probability values (Entries above the diagonal are adjusted for multiple tests.)
partial correlations
V1 V3 V5
V1 0.00 0.01 0.31
V3 0.00 0.00 0.34
V5 0.16 0.34 0.00
To see confidence intervals of the correlations, print with the short=FALSE option
Confidence intervals based upon normal theory. To get bootstrapped values, try cor.ci
lower r upper p
V1-V3 0.10 0.29 0.46 0.00
V1-V5 -0.06 0.14 0.33 0.16
V3-V5 -0.10 0.10 0.29 0.34
```

psych documentation built on May 29, 2017, 8:25 p.m.

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