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umxRAM with Ordinal Data

This post covers using umxRAM with ordinal data. It’s all pretty transparent: The key is that uxmRAM knows variables are ordinal based on their type in the data.frame type.

So: let’s first of all make a dataframe with three ordinal variable:

Create a dataframe of three ordinal variables

require(umx)

data(myFADataRaw)
df = myFADataRaw[,c("z1", "z2", "z3")]
df$z1 = mxFactor(df$z1, levels = c(0, 1))
df$z2 = mxFactor(df$z2, levels = c(0, 1))
df$z3 = mxFactor(df$z3, levels = c(0, 1, 2))    
str(df)

Now we have a 500 observation dataframe of 3 variables, each of which is an ordinal factor:

Making a model with ordinal variables

Once the variables are typed correctly, umxRAM can figure out which ones to model (using the threshold liability model) as ordinal:

So the model is exactly as you would use for continuous data:

m1 = umxRAM("Common_Factor_Model", data = df,
	umxPath(var = c("z1","z2","z3"), fixedAt = 1), # latent variance
	umxPath(var = "F1", values = 1, labels = "varF1"), # factor loadings
	umxPath(from="F1", to = c("z1","z2","z3"), firstAt = 1), # means
	umxPath(means= c("z1","z2","z3","F1"), fixedAt = 0) # thresholds
)

plot(m1)

χ²(2) = 50.2, p < 0.001; CFI = 0.797; TLI = 0.695; RMSEA = 0.22