Getting 'unused arguments' error in confirmatory factor analysis with lavaan

CFA
1

I’m trying to do a confirmatory factor analysis using lavaan, but I’m running into issues. I’ve set up my model like this:

model_spec <- '
Factor1: F1_1, F1_2, F1_3, F1_4, F1_5
Factor2: F2_1, F2_2, F2_3, F2_4, F2_5
Factor3: F3_1, F3_2, F3_3, F3_4, F3_5
'

result <- cfa(model_spec, auto.var = TRUE)

But when I try to run it, I get an error saying ‘unused arguments’. I’ve already installed the lavaan package, but it’s still not working. Am I missing something in my syntax or setup? I thought this would automatically add variances and covariances. Any help would be great!

2

I’ve encountered similar issues with lavaan before. One thing to check is whether you’re using the correct operator for specifying factor loadings. In lavaan, the ‘=~’ operator is typically used for this purpose, not ‘:’.

Try modifying your model specification like this:

model_spec <- '
Factor1 =~ F1_1 + F1_2 + F1_3 + F1_4 + F1_5
Factor2 =~ F2_1 + F2_2 + F2_3 + F2_4 + F2_5
Factor3 =~ F3_1 + F3_2 + F3_3 + F3_4 + F3_5
'

Also, ensure you’re passing your data to the cfa() function:

result <- cfa(model_spec, data = your_data, auto.var = TRUE)

If the issue persists, it might be worth checking for any missing data or inconsistencies in variable names between your model specification and dataset. The ‘unused arguments’ error often points to a mismatch in function parameters or data structure.

3

Hey ExploringOcean! :ocean:

I feel ya on the CFA struggles - those errors can be super frustrating! Have you tried running summary() on your dataset to make sure all the variables are there and named correctly? Sometimes R can be picky about exact matches.

Also, curious if you’ve considered using the lavaan syntax for factor loadings instead? It might give you more control. Something like:

model_spec <- '
Factor1 =~ F1_1 + F1_2 + F1_3 + F1_4 + F1_5
Factor2 =~ F2_1 + F2_2 + F2_3 + F2_4 + F2_5
Factor3 =~ F3_1 + F3_2 + F3_3 + F3_4 + F3_5
'

What kind of data are you working with, by the way? CFA can be tricky with certain types. Let me know if you figure it out - always eager to learn new lavaan tricks!

4

hey there, ran into similar issues before. make sure you’re passing your data to the cfa() function.

try somethin like:

result ← cfa(model_spec, data = your_data_frame, auto.var = TRUE)

if that dont work, double check ur variable names match whats in ur dataset. good luck!