R/statpsych1.R
sim.ci.stdmean.ps.Rd
Performs a computer simulation of confidence interval performance for two types of standardized mean differences in a paired-samples design (see ci.stdmean.ps). Sample data for the two levels of the within-subjects factor can be generated from five different population distributions. All distributions are scaled to have standard deviations of 1.0 at level 1.
sim.ci.stdmean.ps(alpha, n, sd.ratio, cor, dist1, dist2, d, rep)
alpha level for 1-alpha confidence
sample size
ratio of population standard deviations (sd2/sd1)
correlation between paired measurements
type of distribution at level 1 (1, 2, 3, 4, or 5)
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 kurtosis = 6)
4 = moderate skew (skewness = 1 and excess kurtosis = 1.5)
5 = large skew (skewness = 2 and excess kurtosis = 6)
population standardized mean difference
number of Monte Carlo samples
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
sim.ci.stdmean.ps(.05, 20, 1.5, .8, 4, 4, .5, 2000)
#> Coverage Lower Error Upper Error Ave CI Width Ave Est
#> Unweighted Standardizer 0.8905 0.069 0.0405 0.7371796 0.5318356
#> Level 1 Standardizer 0.9310 0.043 0.0260 0.9285844 0.5182281
# Should return (within sampling error):
# Coverage Lower Error Upper Error Ave CI Width Ave Est
# Unweighted Standardizer 0.9095 0.0555 0.035 0.7354865 0.5186796
# Level 1 Standardizer 0.9525 0.0255 0.022 0.9330036 0.5058198