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This data was taken from the National Longitudinal Study of Adolescent Health. It is a cross-sectional sample of participants from grades 7--12, described and analyzed by Warne (2014).

Format

A data frame with 4344 observations on the following 3 variables.

grade

an ordered factor with levels 7 < 8 < 9 < 10 < 11 < 12

depression

a numeric vector

anxiety

a numeric vector

Source

Warne, R. T. (2014). A primer on Multivariate Analysis of Variance (MANOVA) for Behavioral Scientists. Practical Assessment, Research & Evaluation, 19 (1). https://scholarworks.umass.edu/pare/vol19/iss1/17/

Details

depression is the response to the question "In the last month, how often did you feel depressed or blue?"

anxiety is the response to the question "In the last month, how often did you have trouble relaxing?"

The responses for depression and anxiety were recorded on a 5-point Likert scale, with categories 0="Never", 1="Rarely", 2="Occasionally", 3="Often", 4="Every day"

Examples


data(AddHealth)
# fit mlm
AH.mod <- lm(cbind(depression, anxiety) ~ grade, data=AddHealth)

car::Anova(AH.mod)
#> 
#> Type II MANOVA Tests: Pillai test statistic
#>       Df test stat approx F num Df den Df    Pr(>F)    
#> grade  5  0.022415    9.834     10   8676 < 2.2e-16 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(car::Anova(AH.mod))
#> 
#> Type II MANOVA Tests:
#> 
#> Sum of squares and products for error:
#>            depression  anxiety
#> depression   6058.911 3021.691
#> anxiety      3021.691 5210.233
#> 
#> ------------------------------------------
#>  
#> Term: grade 
#> 
#> Sum of squares and products for the hypothesis:
#>            depression  anxiety
#> depression  112.76722 87.57399
#> anxiety      87.57399 75.02650
#> 
#> Multivariate Tests: grade
#>                  Df test stat  approx F num Df den Df     Pr(>F)    
#> Pillai            5 0.0224153  9.833964     10   8676 < 2.22e-16 ***
#> Wilks             5 0.9776192  9.872584     10   8674 < 2.22e-16 ***
#> Hotelling-Lawley  5 0.0228579  9.911186     10   8672 < 2.22e-16 ***
#> Roy               5 0.0211939 18.387786      5   4338 < 2.22e-16 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

heplot(AH.mod, hypotheses="grade.L", fill=c(TRUE, FALSE))