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library(lavaan)
model <- 'x4 ~ x1'
fit <- cfa(model, data = HolzingerSwineford1939)
fscores <- lavPredict(fit)
results in a matrix with 301 rows and 0 columns. I would suggest that this should result in an error or at least in a warning. So, error or warning for lavPredict if model contains no latent variables.
The text was updated successfully, but these errors were encountered:
Warning message: lavaan->lavPredict(): fitted model does not contain regular (i.e., measured) latent variables; the matrix of factor scores may contain no columns
Very minor, but this
results in a matrix with 301 rows and 0 columns. I would suggest that this should result in an error or at least in a warning. So, error or warning for lavPredict if model contains no latent variables.
The text was updated successfully, but these errors were encountered: