Hi,
Please I need help to understand problems on CFA using lavaan package.
When I run the following code:
#Specify the CFA model
ModelCFA <- ' Factor 1=~ COMM1 + COMM2 + COMM3
Factor 2=~ CLOS1 + CLOS2 + CLOS3 + CLOS4
Factor 3=~ COMP1 + COMP2 + COMP3 + COMP4 '
#Get model fit
fit <- cfa(ModelCFA, data=DavAuraMarR)
Then the Warning message indicates:
Warning message:
In lav_object_post_check(object) :
lavaan WARNING: covariance matrix of latent variables
is not positive definite;
use lavInspect(fit, "cov.lv") to investigate.
When I check covariances and correlations using lavInspect(fit, "cor.lv") and lavInspect(fit, "cor.lv"), I obtain:
lavInspect(fit, "cov.lv")
Fact 1 Fact 2 Fact 3
Factor 1 1.363
Factor 2 1.409 1.677
Factor 3 1.240 1.434 1.117
lavInspect(fit, "cor.lv")
Fact 1 Fact 2 Fact 3
Factor 1 1.000
Factor 2 0.932 1.000
Factor 3 1.005 1.048 1.000
How is it possible to see correlations greater than 1?
What can I do?
The model fits good but I have this warning message, and overall I can't see the modification indices.
When I try t see it, the second warning message tells me:
Warning messages:
1: In lav_start_check_cov(lavpartable = lavpartable, start = START) :
lavaan WARNING: starting values imply a correlation larger than 1;
variables involved are: Factor 1 Factor 3
2: In lav_start_check_cov(lavpartable = lavpartable, start = START) :
lavaan WARNING: starting values imply a correlation larger than 1;
variables involved are: Factor 2 Factor 3
I have a great population (over 1000)...
Thank you for your answers