showPearsonPower
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.
 Keywords
 hplot
Usage
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
Examples
## Not run:
# showPearsonPower();
# ## End(Not run)
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