userfriendlyscience (version 0.5-2)

dCohensd: The distribution of Cohen's d

Description

These functions use some conversion to and from the t distribution to provide the Cohen's d distribution. There are four versions that act similar to the standard distribution functions (e.g. the d., p., q., and r. functions), and three convenience functions.

Usage

dd(x, df, populationD = 0)
pd(q, df, populationD = 0, lower.tail = TRUE)
qd(p, df, populationD = 0, lower.tail = TRUE)
rd(n, df, populationD = 0)
dCohensd(x, df, populationD = 0)
pCohensd(q, df, populationD = 0, lower.tail = TRUE)
qCohensd(p, df, populationD = 0, lower.tail = TRUE)
rCohensd(n, df, populationD = 0)
pdExtreme(d, n, populationD=0)
pdMild(d, n, populationD=0)
pdInterval(ds, n, populationD=0)
cohensdCI(d, n, conf.level = .95)

Arguments

x, q, d

Vector of quantiles, or, in other words, the value(s) of Cohen's d.

ds

A vector with two Cohen's d values.

p

Vector of probabilites (p-values).

df

Degrees of freedom.

n

Desired number of Cohen's d values for rCohensd and rd, and the number of participants/datapoints for pdExtreme, pdMild, and pdInterval.

populationD

The value of Cohen's d in the population; this determines the center of the Cohen's d distribution. I suppose this is the noncentrality parameter.

lower.tail

logical; if TRUE (default), probabilities are the likelihood of finding a Cohen's d smaller than the specified value; otherwise, the likelihood of finding a Cohen's d larger than the specified value.

conf.level

The level of confidence of the confidence interval.

Value

dCohensd (or dd) gives the density, pCohensd (or pd) gives the distribution function, qCohensd (or qd) gives the quantile function, and rCohensd (or rd) generates random deviates.pdExtreme returns the probability (or probabilities) of finding a Cohen's d equal to or more extreme than the specified value(s).pdMild returns the probability (or probabilities) of finding a Cohen's d equal to or less extreme than the specified value(s).pdInterval returns the probability of finding a Cohen's d that lies in between the two specified values of Cohen's d.

Details

The functions use convert.d.to.t and convert.t.to.d to provide the Cohen's d distribution.

See Also

convert.d.to.t, convert.t.to.d, dt, pt, qt, rt

Examples

### Generate 10 random Cohen's d values
rCohensd(10, 20, populationD = .5);

### Probability of findings a Cohen's d smaller than
### .5 if it's 0 in the population (i.e. under the
### null hypothesis)
pCohensd(.5, 64);

### Probability of findings a Cohen's d larger than
### .5 if it's 0 in the population (i.e. under the
### null hypothesis)
1 - pCohensd(.5, 64);

### Probability of findings a Cohen's d more extreme
### than .5 if it's 0 in the population (i.e. under
### the null hypothesis)
pdExtreme(.5, 64);

### Probability of findings a Cohen's d more extreme
### than .5 if it's 0.2 in the population.
pdExtreme(.5, 64, populationD = .2);

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