Generalized Linear Model

Power analysis for generalized linear models using eta-squared or R-squared effect-size parameterizations.

pamlgzlm(
  aim = "n",
  mode = "eta",
  es = 0.2,
  df_model = 1,
  power = 0.9,
  n = 20,
  sig.level = 0.05,
  alternative = "two.sided",
  plot_contour = FALSE,
  plot_escurve = FALSE,
  plot_ncurve = FALSE,
  plot_log = FALSE,
  plot_palette = "viridis",
  covs = 0,
  factors = 0,
  factors_list = list(list(var = "factor 1", levels = 0)),
  covs_order = "main",
  factors_order = "main",
  mixed_order = "none",
  plot_x = "none",
  plot_y = "none",
  plot_custom_labels = FALSE,
  plot_z = "none",
  plot_x_from = 0,
  plot_x_to = 0,
  plot_z_lines = 0,
  plot_z_value = list(),
  plot_to_table = FALSE,
  data = NULL
)

Arguments

aim

The aim of the analysis: n, power, or es.

mode

Effect size parameterization: "eta" or "r2".

es

Expected effect size.

df_model

Model degrees of freedom.

power

Minimal desired power.

n

Sample size.

sig.level

Type I error rate.

alternative

Test direction: "two.sided" or "one.sided".

plot_contour, plot_escurve, plot_ncurve

Logical plot toggles.

plot_log

Logical; use a log scale where supported.

plot_palette

Color palette used for plots.

covs, factors, factors_list, covs_order, factors_order, mixed_order

Model-definition inputs used to compute model degrees of freedom.

plot_x, plot_y, plot_custom_labels, plot_z, plot_x_from, plot_x_to, plot_z_lines, plot_z_value, plot_to_table

Custom power plot options.

data

Optional data frame. Present for interface consistency.

Value

A results object.