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The data, from an exercise given by Meyers et al. (2006) relates to 60 fathers assessed on three subscales of a Perceived Parenting Competance Scale. The fathers were selected from three groups: (a) fathers of a child with no disabilities; (b) fathers with a physically disabled child; (c) fathers with a mentally disabled child.

1 | ```
data("Parenting")
``` |

A data frame with 60 observations on the following 4 variables.

`group`

a factor with levels

`Normal`

`Physical Disability`

`Mental Disability`

`caring`

caretaking responsibilities, a numeric vector

`emotion`

emotional support provided to the child, a numeric vector

`play`

recreational time spent with the child, a numeric vector

The scores on the response variables are discrete.

Meyers, L. S., Gamst, G, & Guarino, A. J. (2006).
*Applied Multivariate Research: Design and Interpretation*,
Thousand Oaks, CA: Sage Publications,
www.sagepub.com/amrStudy, Exercises 10B.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | ```
data(Parenting)
require(car)
# fit the MLM
parenting.mod <- lm(cbind(caring, emotion, play) ~ group, data=Parenting)
Anova(parenting.mod)
# Box's M test
boxM(parenting.mod)
plot(boxM(parenting.mod))
parenting.mod <- lm(cbind(caring, emotion, play) ~ group, data=Parenting)
Anova(parenting.mod)
# test contrasts
print(linearHypothesis(parenting.mod, "group1"), SSP=FALSE)
print(linearHypothesis(parenting.mod, "group2"), SSP=FALSE)
heplot(parenting.mod)
# display tests of contrasts
hyp <- list("N:MP" = "group1", "M:P" = "group2")
heplot(parenting.mod, hypotheses=hyp)
# make a prettier plot
heplot(parenting.mod, hypotheses=hyp, asp=1,
fill=TRUE, fill.alpha=c(0.3,0.1),
col=c("red", "blue"),
lty=c(0,0,1,1), label.pos=c(1,1,3,2),
cex=1.4, cex.lab=1.4, lwd=3)
pairs(parenting.mod, fill=TRUE, fill.alpha=c(0.3, 0.1))
## Not run:
heplot3d(parenting.mod, wire=FALSE)
## End(Not run)
``` |

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