The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Interaction Models with plssem

This vignette shows how to estimate interaction models, with both continuous and ordered (categorical) data.

Model Syntax

m <- '
  X =~ x1 + x2 + x3
  Z =~ z1 + z2 + z3
  Y =~ y1 + y2 + y3

  Y ~ X + Z + X:Z
'

Continuous Indicators

fit_cont <- pls(
  m,
  data      = modsem::oneInt,
  bootstrap = TRUE,
  boot.R    = 50
)
summary(fit_cont)

Ordered Indicators

fit_ord <- pls(
  m,
  data      = oneIntOrdered,
  bootstrap = TRUE,
  boot.R    = 50,
  ordered   = colnames(oneIntOrdered) # explicitly specify variables as ordered
)
summary(fit_ord)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.