welchADF (version 0.3.2)

womenStereotypeData: Students' scores (men and women) on an arithmetic test

Description

An artificial dataset created by Lix et al. from summary data presented by Wicherts et al. (2005) (see the vignette). These authors examined the effects of stereotype threat on women's mathematics ability. Originally there were four different tests administered to study participants (arithmetic, number series, word problems, and sums tests). The dataset contains only scores for the arithmetic test because these scores exhibited a greater magnitude of variance heterogeneity than scores for the other tests. It is an unbalanced design with cell sizes ranging from 45 to 50 participants, and a total sample size of 283.

Usage

womenStereotypeData

Format

A data frame with 283 rows and 3 variables:

condition

test condition (control, nullified, stereotype threat)

sex

the individual's sex (male, female)

y

score on the arithmetic test, out of 40

References

J.Wicherts, C. Dolan, and D. Hessen. Stereotype threat and group differences in test performance: a question of measurement invariance. Journal of Personality and Social Psychology, 89(5):696-716, 2005.

Examples

# NOT RUN {
omnibus_LSM <- welchADF.test(womenStereotypeData, response = "y", between.s =
  c("condition", "sex"), contrast = "omnibus", effect = "condition")
omnibus_trimmed <- update(omnibus_LSM, trimming = TRUE, effect = NULL) # unset value of "effect"
pairwise_LSM <- update(omnibus_LSM, contrast = "all.pairwise", effect = c("condition", "sex"))
pairwise_trimmed <- update(pairwise_LSM, trimming = TRUE)
summary(omnibus_LSM)
summary(omnibus_trimmed)
summary(pairwise_trimmed)
# }
# NOT RUN {
  pairwise_trimmed_boot <- update(pairwise_trimmed, bootstrap = TRUE, seed = 12345)
  summary(pairwise_trimmed_boot)
# }