plot.multiLCA function

Plots conditional response probabilities

Visualizes conditional response probabilities estimated by the multiLCA function. The method works for both single- and multilevel models.

Let out denote the list object returned by the multiLCA function. Executing plot(out) visualizes the conditional response probabilities given by the mPhi matrix in out.

## S3 method for class 'multiLCA'
plot(x, horiz = FALSE, clab = NULL, ...)

Arguments

• x: The object returned by the multiLCA function
• horiz: Whether item labels should be oriented horizontally (TRUE) or vertically (FALSE). Default FALSE
• clab: A character vector with user-specified class labels, if available, in the order "Class 1", "Class 2", ... under the default settings, i.e. top-to-bottom. Default NULL
• ...: Additional plotting arguments

Returns

No return value

Examples

# Use IEA data
data = dataIEA

# Define vector with names of columns with items
Y = colnames(data)[4+1:12]

# Define number of (low-level) classes
iT = 3

# Estimate single-level measurement model
out = multiLCA(data = data, Y = Y, iT = iT)
out

# Plot conditional response probabilities with default settings
plot(out)

# Plot with vertical item labels and custom class labels
plot(out, horiz = FALSE, clab = c("Maximal", "Engaged", "Subject"))