Dear R users,
I have a hard time interpreting the covariances in the parameter estimates
output (standardized), even in the example documented (PoliticalDemocracy).
Can anyone tell me if the estimated covariances are residual covariances
(unexplained by the model), or the covariances of the observable variables?
I haved checked the data and it does not look like the covariances of the
observable variables, however when I tried to find out using simulated data
( with correlated residuals) the estimates did not seem to be the covariance
of the residuals either (much much underestimated). Can anyone help?
Below is the output:
lavaan (0.4-14) converged normally after 70 iterations
Number of observations 75
Estimator ML
Minimum Function Chi-square 38.125
Degrees of freedom 35
P-value 0.329
Parameter estimates:
Information Expected
Standard Errors Standard
Estimate Std.err Z-value P(>|z|) Std.lv Std.all
Latent variables:
Ind60 =~
x1 1.000 0.670 0.920
x2 2.180 0.139 15.742 0.000 1.460 0.973
x3 1.819 0.152 11.967 0.000 1.218 0.872
Dem60 =~
y1 1.000 2.223 0.850
y2 1.257 0.182 6.889 0.000 2.794 0.717
y3 1.058 0.151 6.987 0.000 2.351 0.722
y4 1.265 0.145 8.722 0.000 2.812 0.846
Dem65 =~
y5 1.000 2.103 0.808
y6 1.186 0.169 7.024 0.000 2.493 0.746
y7 1.280 0.160 8.002 0.000 2.691 0.824
y8 1.266 0.158 8.007 0.000 2.662 0.828
Regressions:
Dem60 ~
Ind60 1.483 0.399 3.715 0.000 0.447 0.447
Dem65 ~
Ind60 0.572 0.221 2.586 0.010 0.182 0.182
Dem60 0.837 0.098 8.514 0.000 0.885 0.885
Covariances:
y1 ~~
y5 0.624 0.358 1.741 0.082 0.624 0.296
y2 ~~
y4 1.313 0.702 1.871 0.061 1.313 0.273
y6 2.153 0.734 2.934 0.003 2.153 0.356
y3 ~~
y7 0.795 0.608 1.308 0.191 0.795 0.191
y4 ~~
y8 0.348 0.442 0.787 0.431 0.348 0.109
y6 ~~
y8 1.356 0.568 2.386 0.017 1.356 0.338
Variances:
x1 0.082 0.019 0.082 0.154
x2 0.120 0.070 0.120 0.053
x3 0.467 0.090 0.467 0.239
y1 1.891 0.444 1.891 0.277
y2 7.373 1.374 7.373 0.486
y3 5.067 0.952 5.067 0.478
y4 3.148 0.739 3.148 0.285
y5 2.351 0.480 2.351 0.347
y6 4.954 0.914 4.954 0.443
y7 3.431 0.713 3.431 0.322
y8 3.254 0.695 3.254 0.315
Ind60 0.448 0.087 1.000 1.000
Dem60 3.956 0.921 0.800 0.800
Dem65 0.172 0.215 0.039 0.039
--
View this message in context:
http://r.789695.n4.nabble.com/covariance-estimate-in-function-sem-Lavaan-tp4638454.html
Sent from the R help mailing list archive at Nabble.com.
On 07/30/2012 11:00 PM, Luna wrote:> Dear R users, > I have a hard time interpreting the covariances in the parameter estimates > output (standardized), even in the example documented (PoliticalDemocracy). > Can anyone tell me if the estimated covariances are residual covariances > (unexplained by the model), or the covariances of the observable variables?They are *residual* covariances.> I haved checked the data and it does not look like the covariances of the > observable variables, however when I tried to find out using simulated data > ( with correlated residuals) the estimates did not seem to be the covariance > of the residuals either (much much underestimated). Can anyone help?How did you simulate your data? It is rather tricky to generate data under a known CFA/SEM model with pre-specified residual (co)variances. Yves Rosseel. http://lavaan.org