lm.explore: Compute the power of a linear model for a range of sample...

In julianje/mcpa: Intuitive power analyses through monte carlo simulations

Description

lm.explore computes (via simulation) the power of a linear model trained with pilot data.

Usage

lm.explore(lmodel, lown, topn, r = 10000, alpha = 0.05, conf.level = 0.95,
  plotit = TRUE)

Arguments

lmodel	linear model trained through lm object.
lown	lowest sample size.
topn	highest sample size.
r	number of simulations to compute power.
alpha	significance threshhold.
conf.level	size of confidence intervals.

Value

The probability of finding p < α with the experiment description and a 95% Clopper-Pearson confidence interval for each item in the equation.

Examples

library(datasets)
Model <- lm(mpg ~ hp + vs, data = mtcars)
lm.pow(n=16, Model)

julianje/mcpa documentation built on May 13, 2019, 6:14 p.m.