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)
The number of participants.
The value of the correlation coefficient in the population.
The value of the correlation coefficient according to the null hypothesis.
Labels for the two distributions; the first one is the null hypothesis distribution, the second one the alternative distribution.
The border colors of the distributions and the region used to illustrate the Type 2 error probability.
The fill colors of the distributions and the region used to illustrate the Type 2 error probability.
The alpha (transparency) of the distributions and the region used to illustrate the Type 2 error probability.
The line thicknesses of the distributions and the region used to illustrate the Type 2 error probability.
The theme to use.
The significance level (alpha) of the null hypothesis test.
The number of digits to round to.
A ggplot
plot is returned.
# NOT RUN {
showPearsonPower();
# }
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