Aggression, Computer-Spielzeit und mangelndes Einfühlungsvermögen

Rmd

(nach Field, Miles, & Field (2012))

  We’ll start with the conceptual and we’ll use an example of whether violent video games make people antisocial. Video games are among the favourite online activities for young people: two-thirds of 5–16-year-olds have their own video games console, and 88% of boys aged 8–15 own at least one games console (Ofcom (Office of Communications), 2008). Although playing violent video games can enhance visuospatial acuity, visual memory, probabilistic inference, and mental rotation (Feng, Spence, & Pratt, 2007; Green & Bavelier, 2007; Green, Pouget, & Bavelier, 2010; Mishra, Zinni, Bavelier, & Hillyard, 2011), compared to games such as Tetris, these games have also been linked to increased aggression in youths (Anderson & Bushman, 2001). Another predictor of aggression and conduct problems is callous-unemotional traits such as lack of guilt, lack of empathy, and callous use of others for personal gain (Rowe, Costello, Angold, Copeland, & Maughan, 2010). Imagine a scientist wanted to look at the relationship between playing violent video games such as Grand Theft Auto, MadWorld and Manhunt and aggression. She gathered data from 442 youths (Video Games.sav). She measured their aggressive behaviour (Aggression), callous unemotional traits (CaUnTs), and the number of hours per week they play video games (Vid_Games).

Kann Aggressives Verhalten erklärt werden durch die Zeit, die mit (aggressiven) Computerspielen (z. B. Ego-Shootern) verbracht wird. Welche Rolle spielt Mangel an Einfühlungsvermögen?

Datensatz (video_games.sav)

# require("foreign")
# getwd()
# # ?read.spss
# ddf.vg1 <- read.spss("http://md.psych.bio.uni-goettingen.de/mv/data/af/video_games.sav", to.data.frame=T)
# write.table(ddf.vg1, "video_games_1.txt", sep="\t", quote=F, row.names=F)
# 
# require("memisc")
# ddf.vg2 <- as.data.set(spss.system.file("~/lehre/lehre_ss_2016/mv/data/af/video_games.sav"))
# 
# write.table(ddf.vg2, "video_games_2.txt", sep="\t", quote=F, row.names=F)

ddf <- read.delim("http://md.psych.bio.uni-goettingen.de/mv/data/af/video_games.txt", fileEncoding = "UTF-8")
m.i <- lm(Aggression ~ Vid_Games * CaUnTs, data=ddf)
summary(m.i)

## 
## Call:
## lm(formula = Aggression ~ Vid_Games * CaUnTs, data = ddf)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -29.7144  -6.9087  -0.1923   6.9036  29.2290 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)    
## (Intercept)      33.120233   3.427254   9.664  < 2e-16 ***
## Vid_Games        -0.333597   0.150826  -2.212 0.027495 *  
## CaUnTs            0.168949   0.161049   1.049 0.294731    
## Vid_Games:CaUnTs  0.027062   0.006981   3.877 0.000122 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.976 on 438 degrees of freedom
## Multiple R-squared:  0.3773, Adjusted R-squared:  0.373 
## F-statistic: 88.46 on 3 and 438 DF,  p-value: < 2.2e-16

Modell nach Anpassung der Parameter:

Aggression = 33.120 + (-.334 * games) + (0.169 * Mangel) + (0.027 * Interaktion)

Visualisierung 3d

Mit der library(rockchalk)

df <- read.delim("http://md.psych.bio.uni-goettingen.de/mv/data/af/video_games.txt", fileEncoding = "UTF-8")
m.i <- lm(Aggression ~ Vid_Games * CaUnTs, data=df)

require(rockchalk)

## Loading required package: rockchalk

plotPlane(model = m.i, plotx1 = "Vid_Games", plotx2 = "CaUnTs")

plotPlane(model = m.i, plotx1 = "Vid_Games", plotx2 = "CaUnTs", theta = 0, phi = 10, drawArrows = T)

## Warning in arrows(mypoints4$x, mypoints4$y, mypoints2s$x, mypoints2s$y, : zero-
## length arrow is of indeterminate angle and so skipped

## Warning in arrows(mypoints4$x, mypoints4$y, mypoints2s$x, mypoints2s$y, : zero-
## length arrow is of indeterminate angle and so skipped

plotPlane(model = m.i, plotx1 = "Vid_Games", plotx2 = "CaUnTs", theta = 90, phi = 10, drawArrows = T)

## Warning in arrows(mypoints4$x, mypoints4$y, mypoints2s$x, mypoints2s$y, : zero-
## length arrow is of indeterminate angle and so skipped

## Warning in arrows(mypoints4$x, mypoints4$y, mypoints2s$x, mypoints2s$y, : zero-
## length arrow is of indeterminate angle and so skipped

# or to emphasize the view of the interaction
plotPlane(model = m.i, plotx1 = "Vid_Games", plotx2 = "CaUnTs", theta = 0, phi = -12, drawArrows = T)

## Warning in arrows(mypoints4$x, mypoints4$y, mypoints2s$x, mypoints2s$y, : zero-
## length arrow is of indeterminate angle and so skipped

## Warning in arrows(mypoints4$x, mypoints4$y, mypoints2s$x, mypoints2s$y, : zero-
## length arrow is of indeterminate angle and so skipped

Mit library(rgl)

df <- read.delim("http://md.psych.bio.uni-goettingen.de/mv/data/af/video_games.txt", fileEncoding = "UTF-8")
require(rgl)

## Loading required package: rgl

open3d()

## glX 
##   1

plot3d(x=df$Vid_Games, y=df$CaUnTs, z=df$Aggression, col="red", size=1)

m.i <- lm(Aggression ~ Vid_Games * CaUnTs, data=df)
# planes3d(m.i$coefficients["Vid_Games"], m.i$coefficients["CaUnTs"], -1, m.i$coefficients["(Intercept)"], alpha=0.5)
grd <- expand.grid(Vid_Games = sort(unique(df$Vid_Games)), CaUnTs = sort(unique(df$CaUnTs)) )
grd$pred <-predict(m.i, newdata=grd)
persp3d(x=unique(grd[[1]]), y=unique(grd[[2]]), 
              z=matrix(grd[[3]],length(unique(grd[[1]])),length(unique(grd[[2]]))), add=TRUE)

Field, A., Miles, J., & Field, Z. (2012). Discover statistics using r. London: Sage.