Dear Statalisters,

I am running a CFA on a 17 items scale. because of the binary (yes/no) nature of the items, I was advised to use Asymtpotic distrubuition free method instead of maximum-likelihood estimation. After running my syntax:

sem (L1->var1 - var17), method(adf)
esta gof, stas(all)

I get only the chi2, SMRM and CD indices. ----------------------------------------------------------------------------
Fit statistic | Value Description
---------------------+------------------------------------------------------
Discrepancy |
chi2_ms(.) | . model vs. saturated
p > chi2 | .
chi2_bs(136) | 20476.639 baseline vs. saturated
p > chi2 | 0.000
---------------------+------------------------------------------------------
Population error |
RMSEA | . Root mean squared error of approximation
90% CI, lower bound | 0.000
upper bound | .
pclose | . Probability RMSEA <= 0.05
---------------------+------------------------------------------------------
Baseline comparison |
CFI | 1.000 Comparative fit index
TLI | . Tucker-Lewis index
---------------------+------------------------------------------------------
Size of residuals |
SRMR | 0.056 Standardized root mean squared residual
CD | 0.935 Coefficient of determination
----------------------------------------------------------------------------


Instead, when using standard ml estimation, I get all of the gof indices. why is that?
thanks in advance