countES: Calculates effect size measures for count regression models

In stefanycoxe/countES: Effect Size Measures For Count Regression Models

Calculates effect size measures for count regression models

Description

This function calculates the standardized mean difference (SMD, i.e., Cohen's d) and the multiplicative effect size for a count regression model

Usage

countES(
  int,
  int_se,
  slope,
  slope_se,
  disp,
  mtype,
  reps,
  CI_level,
  randseed,
  eff_plot,
  dist_plot
)

Arguments

int	Intercept value (numeric)
int_se	Standard error of the intercept (numeric)
slope	Slope value (numeric)
slope_se	Standard error of the slope (numeric)
disp	Dispersion: square root of phi for overdispersed, alpha for negative binomial (numeric)
mtype	Model type ("poisson" "overdispersed" "negative binomial")
reps	Number of Monte Carlo replications (integer)
CI_level	Confidence interval level (e.g., 95 for 95% confidence interval)
randseed	Random seed to replicate results (integer)
eff_plot	Plot of exponential effect (TRUE FALSE)
dist_plot	Histogram of Monte Carlo replications (TRUE FALSE)

Examples

# Poisson regression
countES(int = 1, int_se = 0.5, slope = 0.2, slope_se = 0.1,
disp = 0, mtype = "poisson",
reps = 10000, CI_level = 95, randseed = 12345,
eff_plot = TRUE, dist_plot = TRUE)

# Overdispersed Poisson regression
countES(int = 1, int_se = 0.5, slope = 0.2, slope_se = 0.1,
disp = 1.5, mtype = "overdispersed",
reps = 10000, CI_level = 95, randseed = 12345,
eff_plot = TRUE, dist_plot = TRUE)

countES(int = 1, int_se = 0.5, slope = 0.2, slope_se = 0.1,
disp = 1.5, mtype = "negative binomial",
reps = 10000, CI_level = 95, randseed = 12345,
eff_plot = TRUE, dist_plot = TRUE)

countES()

stefanycoxe/countES documentation built on June 12, 2022, 1:47 a.m.