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Measures of Fit
The smaller the RMR is, the better. An RMR of 0 indicates a perfect fit.
The following output from Example 6 shows that, according to the RMR, Model A
is the best among the models considered except for the saturated model:
Note: Use the \rmr text macro to display the value of the root mean square residual in
the output path diagram.
Selected List of Fit Measures
If you want to focus on a few fit measures, you might consider the implicit
recommendation of Browne and Mels (1992), who elect to report only the following
fit measures:
“CMIN” on p. 599
“P” on p. 599
“FMIN” on p. 602
“F0” on p. 603, with 90% confidence interval
“PCLOSE” on p. 605
“RMSEA” on p. 603, with 90% confidence interval
“ECVI” on p. 607, with 90% confidence interval (See also “AIC” on p. 605)
For the case of maximum likelihood estimation, Browne and Cudeck (1989, 1993)
suggest substituting MECVI (p. 608) for ECVI.
Model RMR GFI AGFI PGFI
Model A: No Autocorrelation 0.284 0.975 0.913 0.279
Model B: Most General 0.757 0.998 0.990 0.238
Model C: Time-Invariance 0.749 0.997 0.993 0.380
Model D: A and C Combined 0.263 0.975 0.941 0.418
Saturated model 0.000 1.000
Independence model 12.342 0.494 0.292 0.353