ggConfidenceCurve

Confidence Curves

Confidence curves are a way to show the confidence in an estimate computed from sample data. They are useful because they show all confidence levels simultaneously, thereby giving a good sense of the accuracy of the estimate, without forcing the researchers to make a more or less arbitrary choice for one confidence level.

Keywords
hplot
Usage
ggConfidenceCurve(metric = "d",
                  value = NULL,
                  n = NULL,
                  conf.level = NULL,
                  wRange = c(0.05, 0.8),
                  curveSize = 1,
                  curveColor = "black",
                  confRange = c(1e-04, 0.9999),
                  confLines = c(0.5, 0.8, 0.95, 0.99),
                  confLineColor = "grey",
                  confLineSize = 1,
                  xlab = metric,
                  steps = 1000,
                  theme = theme_bw())
Arguments
metric

The metric, currently only 'd' (Cohen's d) and 'r' (Pearson's r) are implemented.

value

The value for which to create the confidence curve plot.

n

The sample size for which to create the confidence curve plot. If n is specified, the y axis shows confidence levels (i.e. a conventional confidence curve is generated). If n is set to NULL, the y axis shows sample sizes. Either n or conf.level must be NULL.

conf.level

The confidence level for which to create the confidence curve plot. If conf.level is specified, the y axis shows sample sizes. If conf.level is set to NULL, the y axis shows confidence levels (i.e. a conventional confidence curve is generated). Either n or conf.level must be NULL.

wRange

The range of 'half-widths', or margins of error, to plot in the confidence curve plot if no sample size is specified (if n=NULL).

curveSize

The line size of the confidence curve line.

curveColor

The color of the confidence curve line.

confRange

The range of confidence levels to plot.

confLines

If a traditional confidence curve is generated, lines can be added to indicate the metric values corresponding to the lower and upper confidence interval bounds.

confLineColor

If confidence lines are added (see confLines), this is the color in which they are drawn.

confLineSize

If confidence lines are added (see confLines), this is the size in which they are drawn.

xlab

The label on the x axis.

steps

The number of steps to use when generating the data for the confidence curves' more steps yield prettier, smoother curves, but take more time.

theme

The ggplot theme to use.

Value

A ggplot2 plot.

References

Bender, R., Berg, G., & Zeeb, H. (2005). Tutorial: Using confidence curves in medical research. Biometrical Journal, 47(2), 237-247. http://doi.org/10.1002/bimj.200410104

Birnbaum, A. (1961). Confidence curves: An omnibus technique for estimation and testing statistical hypotheses. Journal of the American Statistical Association, 56(294), 246-249. http://doi.org/10.1080/01621459.1961.10482107

See Also

cohensdCI, pwr.cohensdCI, confIntR, pwr.confIntR

Aliases
  • ggConfidenceCurve
Examples
# NOT RUN {
ggConfidenceCurve(metric='d', value = .5, n = 128);
ggConfidenceCurve(metric='d', value = .5, conf.level = .95);
# }
Documentation reproduced from package userfriendlyscience, version 0.6-1, License: GPL (>= 2)

Community examples

Looks like there are no examples yet.