lme4: VerbAgg – R documentation

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VerbAgg

Verbal Aggression item responses

Description

These are the item responses to a questionaire on verbal aggression. These data are used throughout De Boeck and Wilson, Explanatory Item Response Models (Springer, 2004) to illustrate various forms of item response models.

Format

A data frame with 7584 observations on the following 13 variables.

Anger: the subject's Trait Anger score as measured on the State-Trait Anger Expression Inventory (STAXI)
Gender: the subject's gender - a factor with levels M and F
item: the item on the questionaire, as a factor
resp: the subject's response to the item - an ordered factor with levels no < perhaps < yes
id: the subject identifier, as a factor
btype: behavior type - a factor with levels curse, scold and shout
situ: situation type - a factor with levels other and self indicating other-to-blame and self-to-blame
mode: behavior mode - a factor with levels want and do
r2: dichotomous version of the response - a factor with levels N and Y

Source

http://bear.soe.berkeley.edu/EIRM/

References

De Boeck and Wilson (2004), Explanatory Item Response Models, Springer.

Examples

str(VerbAgg)
## Show how  r2 := h(resp) is defined:
with(VerbAgg, stopifnot( identical(r2, {
     r <- factor(resp, ordered=FALSE); levels(r) <- c("N","Y","Y"); r})))

xtabs(~ item + resp, VerbAgg)
xtabs(~ btype + resp, VerbAgg)
round(100 * ftable(prop.table(xtabs(~ situ + mode + resp, VerbAgg), 1:2), 1))
person <- unique(subset(VerbAgg, select = c(id, Gender, Anger)))
require(lattice)
densityplot(~ Anger, person, groups = Gender, auto.key = list(columns = 2),
            xlab = "Trait Anger score (STAXI)")

if(lme4:::testLevel() >= 3) { ## takes about 15 sec
    print(fmVA <- glmer(r2 ~ (Anger + Gender + btype + situ)^2 +
 		   (1|id) + (1|item), family = binomial, data =
		   VerbAgg), corr=FALSE)
} ## testLevel() >= 3
if (interactive()) {
## much faster but less accurate
    print(fmVA0 <- glmer(r2 ~ (Anger + Gender + btype + situ)^2 +
                             (1|id) + (1|item), family = binomial,
                         data = VerbAgg, nAGQ=0L), corr=FALSE)
} ## interactive()

lme4

Linear Mixed-Effects Models using 'Eigen' and S4

v1.1-26

GPL (>= 2)

Authors

Douglas Bates [aut] (<https://orcid.org/0000-0001-8316-9503>), Martin Maechler [aut] (<https://orcid.org/0000-0002-8685-9910>), Ben Bolker [aut, cre] (<https://orcid.org/0000-0002-2127-0443>), Steven Walker [aut] (<https://orcid.org/0000-0002-4394-9078>), Rune Haubo Bojesen Christensen [ctb] (<https://orcid.org/0000-0002-4494-3399>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>), Bin Dai [ctb], Fabian Scheipl [ctb] (<https://orcid.org/0000-0001-8172-3603>), Gabor Grothendieck [ctb], Peter Green [ctb] (<https://orcid.org/0000-0002-0238-9852>), John Fox [ctb], Alexander Bauer [ctb], Pavel N. Krivitsky [ctb, cph] (<https://orcid.org/0000-0002-9101-3362>, shared copyright on simulate.formula)

Initial release