Plot out power sensitivity plots for t or F tests

morey_plot.ttest(
  es = seq(0, 1, 0.05),
  n = NULL,
  type = c("two.sample", "one.sample", "paired"),
  alternative = c("two.sided", "one.sided"),
  alpha_level = Superpower_options("alpha_level")
)

morey_plot.ftest(
  es = seq(0, 1, 0.05),
  num_df = 1,
  den_df = NULL,
  alpha_level = Superpower_options("alpha_level"),
  liberal_lambda = Superpower_options("liberal_lambda")
)

Arguments

es: Effect size magnitudes to include on the plot; either cohen's f or cohen's d depending on whether it is an F-test or t-test
n: Sample size (t-test only) per group (two sample), total number of pairs (paired samples), or total observations (one-sample); only applies to t-test
type: string specifying the type of t test. Can be abbreviated. (t-test only)
alternative: one- or two-sided test. Can be abbreviated. (t-test only)
alpha_level: vector of alpha levels; default is 0.05
num_df: Numerator degrees of freedom for an F-test.
den_df: Denominator degrees of freedom for an F-test.
liberal_lambda: Logical indicator of whether to use the liberal (cohen_f^2\*(num_df+den_df)) or conservative (cohen_f^2\*den_df) calculation of the noncentrality (lambda) parameter estimate. Default is FALSE.

Value

Returns plots of effect size (x-axis)

Functions

morey_plot.ttest(): Power-sensitivity plot for t-tests
morey_plot.ftest(): Power-sensitivity plot for F-tests

References

Morey, R.D. (2020). Power and precision Why the push for replacing “power” with “precision” is misguided. Retrieved from: https://richarddmorey.medium.com/power-and-precision-47f644ddea5e

Examples

if (FALSE) {
# t-test example ------
# Sensitivity for cohen's d from .1 to .5
# sample sizes of 10 and 20
# alpha levels .05 and .075
# type will be paired and one sided
# Set effect sizes with seq function (?seq)

morey_plot.ttest(es = seq(.1,.5,.01),
n = c(10,20),
alpha_level = c(.05,.075),
type = "paired",
alternative = "one.sided")
}