Struggling with CFA in R: File Opening Issue

CFA
1

Hey everyone, I’m hitting a roadblock with my confirmatory factor analysis in R. I’ve been trying to run a CFA but keep getting an error when I use the cfa() function. Here’s what I’m dealing with:

my_data <- read.csv('survey_results.csv')
factor_model <- '
  self_reliance =~ q1 + q2 + q3 + q4
  treatment_options =~ q5 + q6
'

analysis <- cfa(factor_model, data=my_data)

When I run this, R throws an error saying it can’t open the connection and there’s no such file or directory. It’s like it’s trying to read the model string as a file path instead of a model specification.

I’m pretty sure my data is loaded correctly, and I’ve double-checked the variable names. Has anyone run into this before or know what might be causing it? I’m scratching my head here and would really appreciate any pointers. Thanks!

2

Hey Ethan85! :wave: That’s a tricky one you’ve got there. I’ve run into similar head-scratchers with R before, so I feel your pain!

Have you tried using the lavaan package for your CFA? It’s pretty awesome for this kind of thing. You might need to tweak your code a bit, but it could solve your file path issue. Something like this might do the trick:

library(lavaan)
my_data <- read.csv('survey_results.csv')
factor_model <- '
  self_reliance =~ q1 + q2 + q3 + q4
  treatment_options =~ q5 + q6
'
analysis <- sem(factor_model, data = my_data)

Just curious - what made you choose these specific factors for your analysis? It sounds like an interesting study! :thinking:

Oh, and quick question - are you sure all your variable names in the data match exactly with what’s in your model? Sometimes I’ve found that a tiny typo can cause the weirdest errors.

Let us know if this helps or if you’re still stuck. We’re all learning here, right? Good luck with your analysis! :blush:

3

I’ve encountered similar issues with CFA in R before. It seems the problem might be related to how the cfa() function is interpreting your model specification. Have you considered using the lavaan package? It’s quite robust for this type of analysis.

Try modifying your code like this:

library(lavaan)
my_data <- read.csv('survey_results.csv')
factor_model <- '
  self_reliance =~ q1 + q2 + q3 + q4
  treatment_options =~ q5 + q6
'
analysis <- sem(factor_model, data = my_data)

This approach uses the sem() function from lavaan, which should handle your model specification correctly. Make sure your variable names in the data match exactly with those in your model. Sometimes a small discrepancy can cause unexpected errors.

If you’re still having trouble, double-check your data import and consider printing out the first few rows of my_data to ensure it’s loaded properly. Let us know if this helps or if you need further assistance.

4

hey ethan, sry to hear ur having trouble! have u tried using the lavaan package? it’s pretty great for CFA stuff. try this:

library(lavaan)
analysis <- sem(factor_model, data = my_data)

make sure ur variable names match exactly in ur data and model. sometimes a tiny typo can mess everything up. hope this helps!