I'm stuck with a Confirmatory Factor Analysis (CFA) using Lavaan in R. My code isn't working right and I keep getting this error:
**lavaan 0.6-7 did NOT end normally after 2044 iterations**
I've been trying to figure it out but no luck. Can anyone help me understand what's going wrong?
Here's a simplified version of my code:
```r
library(lavaan)
data <- read.csv('my_data.csv')
model <- '
Factor1 =~ Item1 + Item2 + Item3
Factor2 =~ Item4 + Item5 + Item6
Factor3 =~ Item7 + Item8 + Item9
HigherOrder =~ Factor1 + Factor2 + Factor3
'
fit <- cfa(model, data = data)
summary(fit)
The data has all numeric columns. I’ve double-checked everything but can’t spot the issue. Any ideas on what might be causing this? Thanks!
Hey there WhisperingWind! 
Ooh, CFA troubles can be so tricky! I’ve been there too. Have you thought about checking your data for any outliers or weird patterns? Sometimes those sneaky data points can throw everything off.
Also, I’m curious - how many observations do you have in your dataset? With a higher-order factor model, you might need quite a few to get things to converge properly.
Oh, and here’s a random thought - have you tried standardizing your variables? Sometimes that can help with convergence issues.
What other models have you tried? Maybe starting with a simpler model and building up could help pinpoint where things are going wonky.
Keep us posted on how it goes! CFA puzzles are always fun to solve together. 
It sounds like the convergence issue might be due to several potential factors. I’ve faced similar situations where limited data or an overly complex model led to instability in estimation.
One approach is to verify that your sample size is sufficient relative to the number of parameters. It may help to simplify your model temporarily to confirm that each part behaves as expected. Also, ensuring there’s no excessive correlation among items can rule out multicollinearity. Additionally, consider trying custom starting values and reviewing the model’s identification conditions to resolve the error.
I hope these suggestions point you toward a solution.