These functions are used by nnc() in the behaviorchange package to compute the Numbers Needed for Change, but are also available for manual use.

convert.cer.to.d(
cer,
eer,
eventDesirable = TRUE,
eventIfHigher = TRUE,
dist = "norm",
distArgs = NULL,
distNS = "stats"
)

convert.d.to.eer(
d,
cer,
eventDesirable = TRUE,
eventIfHigher = TRUE,
dist = "norm",
distArgs = list(),
distNS = "stats"
)

convert.d.to.nnc(d, cer, r = 1, eventDesirable = TRUE, eventIfHigher = TRUE)

convert.eer.to.d(
eer,
cer,
eventDesirable = TRUE,
eventIfHigher = TRUE,
dist = "norm",
distArgs = NULL,
distNS = "stats"
)

## Arguments

cer

The Control Event Rate.

eer

The Experimental Event Rate.

eventDesirable

Whether an event is desirable or undesirable.

eventIfHigher

Whether scores above or below the threshold are considered 'an event'.

dist, distArgs, distNS

Used to specify the distribution to use to convert between Cohen's d and the CER and EER. distArgs can be used to specify additional arguments to the corresponding q and p functions, and distNS to specify the namespace (i.e. package) from where to get the distribution functions.

d

The value of Cohen's d.

r

The correlation between the determinant and behavior (for mediated Numbers Needed for Change).

## Value

The converted value.

nnc() in the behaviorchange package.

## Author

Gjalt-Jorn Peters & Stefan Gruijters

Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com

## Examples


convert.d.to.eer(d=.5, cer=.25);
#>  0.4307403
convert.d.to.nnc(d=.5, cer=.25);
#>  5.532801
#> attr(,"eer")
#>  0.4307403