Parses a group of Mplus model output files (.out extension) for model fit statistics.
At this time, the details extracted are fixed and include: Filename, InputInstructions, Title, Estimator,
LL, BIC, aBIC, AIC, AICC, Parameters, Observations, CFI, TLI, RMSEA_Estimate, RMSEA_90CI_LB, RMSEA_90CI_UB,
RMSEA_pLT05, ChiSqM_Value, ChiSqM_DF, ChiSq_PValue, BLRT_KM1LL, BLRT_PValue, BLRT_Numdraws). The
infrastructure is in place to allow for user-specified selection of summary statistics in future versions.
extractModelSummaries(target = getwd(), recursive = FALSE, filefilter)Returns a data.frame containing model fit statistics for all output files within directory.
The data.frame contains some of the following variables (depends on model type):
Title: Title for the model, specified by the TITLE: command
Filename: Filename of the output file
Estimator: Estimator used for the model (e.g., ML, MLR, WLSMV, etc.)
LL: Log-likelihood of the model
BIC: Bayesian Information Criterion
aBIC: Sample-Size-Adjusted BIC (Sclove, 1987)
AIC: Akaike's Information Criterion
AICC: Corrected AIC, based on Sugiura (1978) and recommended by Burnham & Anderson (2002)
DIC: Deviance Information Criterion. Available in ESTIMATOR=BAYES output.
Parameters: Number of parameters estimated by the model
pD: Estimated number of parameters in Bayesian output
Observations: The number of observations for the model (does not suppport multiple-groups analysis at this time)
CFI: Confirmatory Fit Index
TLI: Tucker-Lewis Index
RMSEA_Estimate: Point estimate of root mean squared error of approximation
RMSEA_90CI_LB: Lower bound of the 90\
RMSEA_90CI_UB: Upper bound of the 90\
RMSEA_pLT05: Probability that the RMSEA estimate falls below .05, indicating good fit.
ChiSqM_Value: Model chi-squared value
ChiSqM_DF: Model chi-squared degrees of freedom
ChiSqM_PValue: Model chi-squared p value
ChiSqM_ScalingCorrection: H0 Scaling Correction Factor
ObsRepChiSqDiff_95CI_LB: Lower bound of 95\
ObsRepChiSqDiff_95CI_UB: Upper bound of 95\
PostPred_PValue: Posterior predictive p-value
PriorPostPred_PValue: Prior Posterior Predictive P-Value
BLRT_RequestedDraws: Number of requested bootstrap draws for TECH14.
BLRT_KM1LL: Log-likelihood of the K-1 model (one less class) for the Bootstrapped Likelihood Ratio Test (TECH14).
BLRT_2xLLDiff: Two times the log-likelihood difference of the models with K and K-1 classes (TECH14).
BLRT_ParamDiff: Difference in the number of parameters for models with K and K-1 classes (TECH14).
BLRT_PValue: P-value of the Bootstrapped Likelihood Ratio Test (TECH14) testing whether the K class model is significantly better than K-1
BLRT_SuccessfulDraws: The number of successful bootstrapped samples used in the Bootstrapped Likelihood Ratio Test
SRMR: Standardized root mean square residual
SRMR.Between: For TYPE=TWOLEVEL output, standardized root mean square residual for between level
SRMR.Within: For TYPE=TWOLEVEL output, standardized root mean square residual for within level
WRMR: Weighted root mean square residual
ChiSqBaseline_Value: Baseline (unstructured) chi-squared value
ChiSqBaseline_DF: Baseline (unstructured) chi-squared degrees of freedom
ChiSqBaseline_PValue: Baseline (unstructured) chi-squared p value
NumFactors: For TYPE=EFA output, the number of factors
T11_KM1Starts: TECH11: Number of initial stage random starts for k-1 model
T11_KM1Final: TECH11: Number of final stage optimizations for k-1 model
T11_KM1LL: TECH11: Log-likelihood of the K-1 model used for the Vuong-Lo-Mendell-Rubin LRT
T11_VLMR_2xLLDiff: TECH11: 2 * Log-likelihood Difference of K-class vs. K-1-class model for the Vuong-Lo-Mendell-Rubin LRT
T11_VLMR_ParamDiff: TECH11: Difference in number of parameters between K-class and K-1-class model for the Vuong-Lo-Mendell-Rubin LRT
T11_VLMR_Mean: TECH11: Vuong-Lo-Mendell-Rubin LRT mean
T11_VLMR_SD: TECH11: Vuong-Lo-Mendell-Rubin LRT standard deviation
T11_VLMR_PValue: TECH11: Vuong-Lo-Mendell-Rubin LRT p-value
T11_LMR_Value: TECH11: Lo-Mendell-Rubin Adjusted LRT value
T11_LMR_PValue: TECH11: Lo-Mendell-Rubin Adjusted LRT p-value
the directory containing Mplus output files (.out) to parse OR the single output file to be parsed. Defaults to the current working directory. Example: "C:/Users/Michael/Mplus Runs"
optional. If TRUE, parse all models nested in
subdirectories within directory. Defaults to FALSE.
a Perl regular expression (PCRE-compatible) specifying particular
output files to be parsed within directory. See regex or
https://www.pcre.org/pcre.txt for details about regular expression syntax.
Michael Hallquist
regex, runModels, readModels
if (FALSE) {
allExamples <- extractModelSummaries(
"C:/Program Files/Mplus/Mplus Examples/User's Guide Examples")
}
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