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

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.

1 |

`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. |

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.

`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 |

Missing values are not allowed.

Seongho Kim <biostatistician.kim@gmail.com>

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.

1 2 3 4 5 6 7 8 9 10 11 | ```
# 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)
``` |

```
Loading required package: MASS
$estimate
hl disp deg BC
hl 1.0000000 -0.5791734 -0.4991364 0.07377194
disp -0.5505041 1.0000000 -0.6320921 0.18071040
deg -0.3180603 -0.4237587 1.0000000 0.39204867
BC 0.0669124 0.1724434 0.5580398 1.00000000
$p.value
hl disp deg BC
hl 0.0000000 0.1324601 0.2079431 0.8621787
disp 0.1573861 0.0000000 0.0926718 0.6684724
deg 0.4426360 0.2954469 0.0000000 0.3367589
BC 0.8749132 0.6830213 0.1506047 0.0000000
$statistic
hl disp deg BC
hl 0.0000000 -1.7402746 -1.410960 0.1811974
disp -1.6152392 0.0000000 -1.998086 0.4500579
deg -0.8217590 -1.1459717 0.000000 1.0438882
BC 0.1642694 0.4288224 1.647252 0.0000000
$n
[1] 10
$gp
[1] 2
$method
[1] "pearson"
```

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