# print.par.cor: Print par.cor In miscor: Miscellaneous Functions for the Correlation Coefficient

## Description

This function prints the `par.cor` object

## Usage

 ```1 2``` ```## S3 method for class 'par.cor' print(x, ...) ```

## Arguments

 `x` `par.cor` object. `...` further arguments passed to or from other methods.

## Author(s)

Takuya Yanagida takuya.yanagida@univie.ac.at

## References

Rasch, D., Kubinger, K. D., & Yanagida, T. (2011). Statistics in psychology - Using R and SPSS. New York: John Wiley & Sons.

`par.cor`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39``` ```dat <- data.frame(x = c(4, 6, 8, 8, 9, 4), y = c(3, 7, 9, 8, 9, 3), z = c(1, 3, 4, 4, 5, 2)) #-------------------------------------- # Partial correlation obj <- par.cor(dat\$x, dat\$y, p.xy = dat\$z, output = FALSE) print(obj) #-------------------------------------- # Semipartial correlation # remove z from x obj <- par.cor(dat\$x, dat\$y, p.x = dat\$z, output = FALSE) print(obj) #-------------------------------------- # Semipartial correlation # remove z from y obj <- par.cor(dat\$x, dat\$y, p.y = dat\$y, output = FALSE) print(obj) #-------------------------------------- # Partial correlation: Two-sided test # H0: rho.p == 0, H1: rho.p != 0 obj <- par.cor(dat\$x, dat\$y, p.xy = dat\$z, sig = TRUE, output = FALSE) print(obj) #-------------------------------------- # Partial correlation: One-sided test # H0: rho.p <= 0.2, H1: rho.p > 0.2 obj <- par.cor(dat\$x, dat\$y, p.xy = dat\$z, sig = TRUE, rho0 = 0.4, alternative = "less", output = FALSE) print(obj) ```