sim.ci.mean.ps: Simulates confidence interval coverage probability for a...

In statpsych: Statistical Methods for Psychologists

Simulates confidence interval coverage probability for a paired-samples mean difference

Description

Performs a computer simulation of confidence interval performance for a mean difference in a paired-samples design. Sample data within each level of the within-subjects factor can be generated from bivariate population distributions with five different marginal distributions. All distributions are scaled to have standard deviations of 1.0 at level 1. Bivariate random data with specified marginal skewness and kurtosis are generated using the unonr function in the mnonr package.

Usage

sim.ci.mean.ps(alpha, n, sd.ratio, cor, dist1, dist2, rep)

Arguments

alpha	alpha level for 1-alpha confidence
n	sample size
sd.ratio	ratio of population standard deviations
cor	population correlation of paired observations
dist1	type of distribution at level 1 (1, 2, 3, 4, or 5)
dist2	type of distribution at level 2 (1, 2, 3, 4, or 5) 1 = Gaussian (skewness = 0 and excess kurtosis = 0) 2 = platykurtic (skewness = 0 and excess kurtosis = -1.2) 3 = leptokurtic (skewness = 0 and excess kurtsois = 6) 4 = moderate skew (skewness = 1 and excess kurtosis = 1.5) 5 = large skew (skewness = 2 and excess kurtosis = 6)
rep	number of Monte Carlo samples

Value

Returns a 1-row matrix. The columns are:

• Coverage - probability of confidence interval including population mean difference

• Lower Error - probability of lower limit greater than population mean difference

• Upper Error - probability of upper limit less than population mean difference

• Ave CI Width - average confidence interval width

Examples

sim.ci.mean.ps(.05, 30, 1.5, .7, 4, 5, 1000)

# Should return (within sampling error):
#      Coverage Lower Error Upper Error Ave CI Width
# [1,]  0.93815     0.05125      0.0106    0.7778518

statpsych documentation built on July 9, 2023, 6:50 p.m.