# A significance testing of a product moment correlation using individual data

### Description

`zero.r.test`

conducts a significance testing of a product moment correlation using individual data

### Usage

1 | ```
zero.r.test(formula, data, sig.level = 0.05, digits = 3)
``` |

### Arguments

`formula` |
two-sided formula; the left-hand-side of which gives one dependent variable containing a numeric variable, and the right-hand-side of one independent variable containing a numeric variable |

`data` |
a data frame contains the variables in the |

`sig.level` |
a numeric contains the significance level (default 0.05) |

`digits` |
the specified number of decimal places (default 3) |

### Details

This function conducts a significance testing of a product moment correlation using individual data. Statistical power is calculated using the following specifications:

(a) small (*r = 0.10*), medium (*r = 0.30*), and large (*r = 0.50*) population effect sizes,
according to the interpretive guideline for effect sizes by Cohen (1992)

(b) sample size specified by `data`

(c) significance level specified by `sig.level`

### Value

The returned object of `zero.r.test`

contains the following components:

`samp.stat` |
returns the means and unbiased standard deviations |

`correlation` |
returns a product moment correlation, its' approximate confidence interval for population correlation, and standard error |

`power` |
returns statistical power for detecting
small ( |

### Author(s)

Yasuyuki Okumura

Department of Social Psychiatry,

National Institute of Mental Health,

National Center of Neurology and Psychiatry

yokumura@blue.zero.jp

### References

Cohen J (1992) A power primer. Psychological Bulletin, 112, 155-159.

### See Also

`zero.r.test.second`

, `samplesize.r`

### Examples

1 2 3 | ```
dat <- data.frame(x = c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1),
y = c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8))
zero.r.test(y~x, data=dat)
``` |

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