Confidence interval for a standardized linear contrast of means in a within-subjects design

Computes confidence intervals for two types of population standardized linear contrast of means (unweighted standardizer and level 1 standardizer) in a within-subjects design. Equality of variances is not assumed, but the correlations among the repeated measures are assumed to be approximately equal.

Usage

ci.lc.stdmean.ws(alpha, m, sd, cor, n, q)

Arguments

alpha

alpha level for 1-alpha confidence

m

vector of estimated means for levels of within-subjects factor

sd

vector of estimated standard deviations for levels of within-subjects factor

cor

average estimated correlation of all measurement pairs

n

sample size

q

vector of within-subjects contrast coefficients

Value

Returns a 2-row matrix. The columns are:

• Estimate - estimated standardized linear contrast

• adj Estimate - bias adjusted standardized linear contrast estimate

• SE - standard error

• LL - lower limit of the confidence interval

• UL - upper limit of the confidence interval

References

Bonett DG (2008). “Confidence intervals for standardized linear contrasts of means.” Psychological Methods, 13(2), 99–109. ISSN 1939-1463, doi:10.1037/1082-989X.13.2.99 .

Examples

m <- c(33.5, 37.9, 38.0, 44.1)
sd <- c(3.84, 3.84, 3.65, 4.98)
q <- c(.5, .5, -.5, -.5)
ci.lc.stdmean.ws(.05, m, sd, .672, 20, q)
#>                           Estimate adj Estimate        SE        LL         UL
#> Unweighted standardizer: -1.301263    -1.266557 0.3147937 -1.918248 -0.6842788
#> Level 1 standardizer:    -1.393229    -1.337500 0.3661824 -2.110934 -0.6755248

# Should return:
#                           Estimate  adj Estimate        SE        LL         UL
# Unweighted standardizer: -1.301263     -1.266557 0.3147937 -1.918248 -0.6842788
# Level 1 standardizer:    -1.393229     -1.337500 0.3661824 -2.110934 -0.6755248