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. Sample data for each group can be generated from five different population distributions. All distributions are scaled to have standard deviations of 1.0 in group 1.

Usage

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

Arguments

alpha	alpha level for 1-alpha confidence
n1	sample size for group 1
n2	sample size for group 2
sd.ratio	ratio of population standard deviations (sd2/sd1)
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 kurtsois = 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 July 9, 2023, 6:50 p.m.