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

## Description

This function prints the `comptest.cor` object

## Usage

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

## Arguments

 `x` `comptest.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.

Zou, G. Y. (2007). Toward using confidence intervals to compare correlation. Psychological Methods, 12, 399-413.

`comptest.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 40 41 42 43 44 45``` ```#-------------------------------------- # Dependent samples # Generate random data x <- c(3, 2, 2, 3, 7, 8, 5, 9) y <- c(2, 4, 1, 5, 7, 3, 6, 7) z <- c(1, 4, 3, 3, 1, 4, 2, 5) #............................................ # H0: rho.xy == rho.xz, H1: rho.xy != rho.xz obj <- comptest.cor(x, y, z, output = FALSE) print(obj) #........................................... # H0: rho.xy <= rho.xz, H1: rho.xy > rho.xz # r.xy = 0.44, r.xz = 0.21. r.yz = 0.20, n = 120 obj <- comptest.cor(r.xy = 0.44, r.xz = 0.21, r.yz = 0.20, n = 120, alternative = "greater", output = FALSE) print(obj) #-------------------------------------- # Independent samples # Generate random data dat <- data.frame(group = rep(1:2, each = 200), rbind(sim.cor(200, rho = 0.3), sim.cor(200, rho = 0.5))) #....................................... # H0: rho.1 == rho.2, H1: rho.1 != rho.2 obj <- comptest.cor(x = dat\$x, y = dat\$y, group = dat\$group, output = FALSE) print(obj) #........................................ # H0: rho.1 >= rho.2, H1: rho.1 ! < rho.2 # Group 1: r = 0.32, n = 108 # Group 2: r = 0.56, n = 113 obj <- comptest.cor(r.1 = 0.32, n.1 = 108, r.2 = 0.56, n.2 = 113, alternative = "less", output = FALSE) print(obj) ```