Visualisation of the power of a Pearson correlation test

This fuction is useful when conducting power analyses for a Pearson correlation. It draws the sampling distribution of Pearson's r assuming a null hypothesis value of r and assuming a the hypothetical population value. The probability of making a Type 1 error is also illustrated.

showPearsonPower(n = 100, rho = 0.3, rNull = 0,
                 distLabels = c("Null Hypothesis", "Population"),
                 rhoColor = "green", rhoFill = "green",
                 rhoAlpha = 0.1, rhoLineSize = 1,
                 rNullColor = "blue", rNullFill = "blue",
                 rNullAlpha = 0.1, rNullLineSize = 1,
                 type2Color = "red", type2Fill = "red",
                 type2Alpha = 0.1, type2LineSize = 0,
                 theme = dlvTheme(), alpha = 0.05, digits = 3)

Arguments

n	The number of participants.
rho	The value of the correlation coefficient in the population.
rNull	The value of the correlation coefficient according to the null hypothesis.
distLabels	Labels for the two distributions; the first one is the null hypothesis distribution, the second one the alternative distribution.
rhoColor, rNullColor, type2Color	The border colors of the distributions and the region used to illustrate the Type 2 error probability.
rhoFill, rNullFill, type2Fill	The fill colors of the distributions and the region used to illustrate the Type 2 error probability.
rhoAlpha, rNullAlpha, type2Alpha	The alpha (transparency) of the distributions and the region used to illustrate the Type 2 error probability.
rhoLineSize, rNullLineSize, type2LineSize	The line thicknesses of the distributions and the region used to illustrate the Type 2 error probability.
theme	The theme to use.
alpha	The significance level (alpha) of the null hypothesis test.
digits	The number of digits to round to.

Value

A ggplot plot is returned.

See also

didacticPlot

Examples

# NOT RUN {
showPearsonPower();
# }