zero.r.test: A significance testing of a product moment correlation using...
In rpsychi: Statistics for psychiatric research

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

zero.r.test conducts a significance testing of a product moment correlation using individual data

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

`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 `fomrmula`
`sig.level`	a numeric contains the significance level (default 0.05)
`digits`	the specified number of decimal places (default 3)

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

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 (r = 0.10), medium (r = 0.30), and large (r = 0.50) population effect sizes

Yasuyuki Okumura
Department of Social Psychiatry,
National Institute of Mental Health,
National Center of Neurology and Psychiatry
yokumura@blue.zero.jp

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

zero.r.test.second, samplesize.r

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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)