Fit the Simple Mediation Model using Normal Theory Maximum Likelihood
Source:R/manMCMedMiss-fit-model-ml.R
FitModelML.RdFit the Simple Mediation Model using Normal Theory Maximum Likelihood
Arguments
- data
Numeric matrix. Output of the
GenDataorAmputeDatafunctions.- mplus_bin
Character string. Path of Mplus binary.
Value
Returns a list with the following elements:
- fit
Model fit.
- coef
Coefficients/parameter estimates
- vcov
Sampling variance-covariance matrix.
- output
Mplus output.
Values in fit.
- free_parameters
Number of free parameters
- h0_loglikelihood
H0 loglikelihood.
- h1_loglikelihood
H1 loglikelihood.
- aic
Akaike information criterion (AIC).
- bic
Bayesian information criterion (BIC).
- sabic
Sample-size adjusted BIC (SABIC).
- chisq
Chi-square value.
- chisq_df
Chi-square degrees of freedom.
- chisq_p
Chi-square p-value.
- cfi
Comparative fit index (CFI).
- tli
Tucker–Lewis index (TLI).
- rmsea
Root mean square error of approximation (RMSEA) estimate.
- rmsea_low
Root mean square error of approximation (RMSEA) lower limit confidence interval.
- rmsea_up
Root mean square error of approximation (RMSEA) upper limit confidence interval.
- rmsea_p
Root mean square error of approximation (RMSEA) probability.
- srmr
Standardized root mean square residual (SRMR).
- condition_number
Condition number for the information matrix (ratio of smallest to largest eigenvalue).
See also
Other Model Fitting Functions:
FitModelIndirect(),
FitModelMI()