docs/mean.ps.md

In cwendorf/dgb: DGB

Mean Difference from Paired Samples

ci.mean.ps

Computes confidence interval for a difference in population means in a paired-samples design.

Arguments: - alpha: alpha level for 1-alpha confidence - mj: sample mean for measure j - sdj: sample standard deviation for measure j - nj: sample size for measure j - r: correlation between the two measures

Values: - estimate, SE, df, lower limit, upper limit

alpha = .05
m1 = 4.5
m2 = 5.0
sd1 = 1.118
sd2 = 1.118
n1 = 24
n2 = 24
r = .8
ci.mean.ps(alpha, m1, m2, sd1, sd2, n1, n2, r)

##      Estimate         SE df        LL        UL
## [1,]      0.5 0.02946189 23 0.4390534 0.5609466

size.ci.mean.ps

Computes sample size required to estimate a difference in population means with desired precision in a paired-samples design.

Arguments: - alpha: alpha level for 1-alpha confidence - var: planning value of average within-group DV variance - cor: planning value of correlation - w: desired confidence interval width Values: - required sample size

alpha = .05
var = 265
cor = .8
w = 10
size.ci.mean.ps(alpha, var, cor, w)

## [1] 19

cwendorf/dgb documentation built on May 3, 2022, 9:35 p.m.