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

## Description

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

## Usage

 ```1 2 3 4 5 6 7 8``` ```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) ```

## Arguments

 `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.

## Details

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

## Value

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

## Author(s)

Gjalt-Jorn Peters & Stefan Gruijters

Maintainer: Gjalt-Jorn Peters <[email protected]>

## References

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.

## Examples

 ```1 2 3 4 5 6``` ```### 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); ```

userfriendlyscience documentation built on Nov. 18, 2017, 4:14 a.m.