sim.ci.stdmean2: Simulates confidence interval coverage probability for a...

In statpsych: Statistical Methods for Psychologists

Simulates confidence interval coverage probability for a standardized mean difference in a 2-group design

Description

Performs a computer simulation of confidence interval performance for two types of standardized mean differences in a 2-group design (see ci.stdmean2). Sample data for each group can be generated from five different population distributions. All distributions are scaled to have a standard deviation of 1.0 for group 1.

Usage

sim.ci.stdmean2(alpha, n1, n2, sd2, dist1, dist2, d, rep)

Arguments

alpha	alpha level for 1-alpha confidence
n1	sample size for group 1
n2	sample size for group 2
sd2	population standard deviation for group 2
dist1	type of distribution for group 1 (1, 2, 3, 4, or 5)
dist2	type of distribution for group 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 kurtosis = 6) 4 = moderate skew (skewness = 1 and excess kurtosis = 1.5) 5 = large skew (skewness = 2 and excess kurtosis = 6)
d	population standardized mean difference
rep	number of Monte Carlo samples

Value

Returns a 1-row matrix. The columns are:

• Coverage - Probability of confidence interval including population std mean difference

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

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

• Ave CI Width - Average confidence interval width

Examples

sim.ci.stdmean2(.05, 20, 20, 1.5, 3, 4, .75, 5000)

# Should return (within sampling error):
#                         Coverage Lower Error Upper Error Ave CI Width   Ave Est
# Unweighted Standardizer   0.9058      0.0610      0.0332     1.342560 0.7838679
# Group 1 Standardizer      0.9450      0.0322      0.0228     1.827583 0.7862640

statpsych documentation built on June 10, 2025, 5:11 p.m.