R Dataset / Package lme4 / VerbAgg

Submitted by pmagunia on March 9, 2018 - 1:06 PM
Dataset License
GNU General Public License v2.0
Attachment Size
dataset-97081.csv 427.64 KB
Documentation

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)
}
                       ## 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)
--

Dataset imported from https://www.r-project.org.

Documentation License
GNU General Public License v2.0

From Around the Site...

Title Authored on Content type
R Dataset / Package HistData / Bowley March 9, 2018 - 1:06 PM Dataset
R Dataset / Package DAAG / humanpower2 March 9, 2018 - 1:06 PM Dataset
R Dataset / Package car / KosteckiDillon March 9, 2018 - 1:06 PM Dataset
R Dataset / Package robustbase / CrohnD March 9, 2018 - 1:06 PM Dataset
R Dataset / Package gap / hla March 9, 2018 - 1:06 PM Dataset