Using ggpairs()

Let’s move on to your challenge: You want to test the relationship between satisfaction with democracy and the variables trstprl, trstlgl, stfeco, and agea. Try using ggpairs()!

Try it out before looking at the other tabs!

oneSolution <- ggpairs(
  pss, 
  columns = c(
    "stfdem",
    "trstprl",
    "trstlgl",
    "stfeco"
  ),
  lower = list(
    continuous = wrap(
      "points",
      position = position_jitter(width = 0.5)
    ),
    combo = wrap(
      "facethist",
      binwidth = 1
    )
  ),
  upper = list(
    continuous = "cor",
    combo = "box_no_facet"
  ),
  diag = list(
    continuous = wrap("densityDiag", bw = 1),
    discrete = "barDiag"
  )
) 

oneSolution
library("psych")

pairs.panels(
  pss[c(
    "stfdem",
    "trstprl",
    "trstlgl",
    "stfeco"
  )
  ],
  method = "pearson",   
  jiggle = TRUE,   # für pseudometrische Daten
  stars = TRUE  # Konvention für Signifikanzen
) 
cor <- corr.test(
  pss[c(
    "stfdem",
    "trstprl",
    "trstlgl",
    "stfeco"
  )
  ],
  method = "pearson",
  use = "complete.obs"
) 

library("corrplot")

corrplot(
  cor$r, 
  p.mat = cor$p,    # Matrix mit p-Werten
  insig = "blank",   # nicht signifikante = leer
  type = "upper",    # auch lower möglich
  method = "circle" # verschiedene Optionen möglich
)   

On the next page, you can explore a ggplot alternative to corrplot, or you can skip ahead to comparing means!