Dear all
I am trying to fit a cross lagged panel model in lavaan, but it return the following error message:
Fejl i modindices(result1) :
lavaan ERROR: could not compute modification indices; information matrix is singular
In addition: Advarselsbeskeder:
1: I lav_start_check_cov(lavpartable = lavpartable, start = START) :
lavaan WARNING: starting values imply a correlation larger than 1;
variables involved are: A1 G1
2: I sqrt(var.lhs.value * var.rhs.value) : NaNs produced
3: I lav_start_check_cov(lavpartable = lavpartable, start = START) :
lavaan WARNING: starting values imply NaN for a correlation value;
variables involved are: A2 G2
4: I lav_start_check_cov(lavpartable = lavpartable, start = START) :
lavaan WARNING: starting values imply a correlation larger than 1;
variables involved are: A3 G3
5: I sqrt(var.lhs.value * var.rhs.value) : NaNs produced
6: I lav_start_check_cov(lavpartable = lavpartable, start = START) :
lavaan WARNING: starting values imply NaN for a correlation value;
variables involved are: AA GG
Does anyone know what went wrong?
'''
RI-CLPM, for simplicity only considering the first three sessions:
define latent variables (A1,A2,A3,G1,G2,G3) from observed ones (a1,a2,a3,g1,g2,g3)
model1 <- '
A1 =~ 1anx1
A2 =~ 1anx2
A3 =~ 1anx3
G1 =~ 1gq1
G2 =~ 1gq2
G3 =~ 1gq3
define stable individual trait variables
AA =~ 1anx1 + 1anx2 + 1anx3
GG =~ 1gq1 + 1gq2 + 1gq3
set up clpm for latent variables
G3 + A3 ~ A2 + G2
G2 + A2 ~ A1 + G1
include residual correlations in clpm
A1 ~~ G1
A2 ~~ G2
A3 ~~ G3
allow correlation btw individual trait variables
AA ~~ GG
disallow correlations btw latent variables and trait-variables
A1 + A2 + A3 + G1 + G2 + G3 ~~ 0AA + 0GG'
'''
Best wishes Morten