nnc: Numbers Needed for Change
In userfriendlyscience: Quantitative Analysis Made Accessible

Description Usage Arguments Details Value Author(s) References Examples

This function computes the Numbers Needed for Change, and shows a visualisation to illustrate them. nnt is an alias for nnc.

nnc(d = NULL, cer = NULL, r = 1, n = NULL,
    threshold = NULL, mean = 0, sd = 1,
    poweredFor = NULL, thresholdSensitivity = NULL,
    eventDesirable = TRUE, eventIfHigher = TRUE,
    conf.level=.95,
    d.ci = NULL, cer.ci = NULL, r.ci = NULL,
    d.n = NULL, cer.n = NULL, r.n = NULL,
    plot = TRUE, returnPlot = TRUE, silent = FALSE)

`d`	The value of Cohen's d.
`cer`	The Control Event Rate.
`r`	The correlation between the determinant and behavior (for mediated Numbers Needed for Change).
`n`	The sample size.
`threshold`	If the event rate is not available, a threshold value can be specified instead, which is then used in conjunction with the mean (`mean`) and standard deviation (`sd`) and assuming a normal distribution to compute the event rate.
`mean`	The mean value, used to draw the plot, or, if no CER is provided but instead the threshold value, to compute the CER.
`sd`	The standard deviation, used to draw the plot (and to compute the CER if a threshold value is supplied instead of the CER).
`poweredFor`	The Cohen's d value for which the study was powered. This expected Cohen's d value can be used to compute the threshold, which then in turn is used to compute the CER. To use this approach, also specify the mean and the standard deviation.
`thresholdSensitivity`	This argument can be used to provide a vector of potential threshold values, each of which is used to compute an NNC. This enables easy inspection of whether the value chosen as threshold matters much for the NNC.
`eventDesirable`	Whether an event is desirable or undesirable.
`eventIfHigher`	Whether scores above or below the threshold are considered 'an event'.
`conf.level`	The confidence level of the confidence interval.
`d.ci`	Instead of providing a point estimate for Cohen's d, a confidence interval can be provided.
`cer.ci`	Instead of providing a point estimate for the Control Event Rate, a confidence interval can be provided.
`r.ci`	Instead of providing a point estimate for the correlation, a confidence interval can be provided.
`d.n`	In addition to providing a point estimate for Cohen's d, a sample size can be provided; if it is, the confidence interval is computed.
`cer.n`	In addition to providing a point estimate for the Control Event Rate, a sample size can be provided; if it is, the confidence interval is computed.
`r.n`	In addition to providing a point estimate for the correlation, a sample size can be provided; if it is, the confidence interval is computed.
`plot`	Whether to generate and show the plot.
`returnPlot`	Whether to return the plot (as an attribute), or to only display it.
`silent`	Whether to suppress notifications.

This function computes the Numbers Needed for Change. See Gruijters & Peters (2017) for details.

The Numbers Needed for Change (NNC), potentially with a plot visualising the NNC in an attribute.

Gjalt-Jorn Peters & Stefan Gruijters

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

Gruijters, S. L. K., & Peters, G.-J. Y. (2017). Introducing the Numbers Needed for Change (NNC): A practical measure of effect size for intervention research.

### Simple example
nnc(d=.4, cer=.3);

### Or for a scenario where events are undesirable, and the 
### intervention effective (therefore having a negative value for d):
nnc(d=-.4, cer=.3, eventDesirable=FALSE);