docs/lc.mean.ws.md

In cwendorf/dgb: DGB

Linear Contrast of Means (Within Subjects)

ci.lc.mean.ws

Computes confidence interval for a population linear contrast of means in a within-subjects design (assumes equal variances and correlations).

Arguments: - alpha: alpha level for 1-alpha confidence - m: vector of sample means - var: average of sample variances - cor: average of sample correlations - n: sample size - h: vector of contrast coefficients Values: - estimate, SE, df, lower limit, upper limit

alpha = .05
m = c(33.5, 37.9, 38.0)
var = 7.8
cor = .82
n = 20
h = c(-.5, -.5, 1)
ci.lc.mean.ws(alpha, m, var, cor, n, h)

##      Estimate       SE df       LL       UL
## [1,]      2.3 0.723533 19 0.785628 3.814372

size.ci.lc.mean.ws

Computes sample size required to estimate a linear contrast of population means with desired precision in a within-subjects design.

Arguments: - alpha: alpha level for 1-alpha confidence - var: planning value of largest DV variance - cor: planning value of smallest correlation - w: desired confidence interval width - h: vector of contrast coefficients

Values: - required sample size

alpha = .05
var = 265
cor = .8
w = 10
h = c(.5, .5, -.5, -.5)
size.ci.lc.mean.ws(alpha, var, cor, w, h)

##      [,1]
## [1,]   11

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