Provide summary of model fit across replications
This function will provide fit index cutoffs for values of alpha, and mean fit index values across all replications.
summaryFit(object, alpha = NULL, improper = TRUE, usedFit = NULL)
object |
|
alpha |
The alpha level used to find the fit indices cutoff. If there is no varying condition, a vector of different alpha levels can be provided. |
improper |
If TRUE, include the replications that provided improper solutions |
usedFit |
Vector of names of fit indices that researchers wish to summarize. |
A data frame that provides fit statistics cutoffs and means
When linkS4class{SimResult} has fixed simulation parameters the first colmns are fit index cutoffs for values of alpha and the last column is the mean fit across all replications. Rows are
Chi Chi-square fit statistic
AIC Akaike Information Criterion
BIC Baysian Information Criterion
RMSEA Root Mean Square Error of Approximation
CFI Comparative Fit Index
TLI Tucker-Lewis Index
SRMR Standardized Root Mean Residual
When linkS4class{SimResult} has random simulation parameters (sample size or percent missing), columns are the fit indices listed above and rows are values of the random parameter.
Alexander M. Schoemann (East Carolina University; schoemanna@ecu.edu) Sunthud Pornprasertmanit (psunthud@gmail.com)
SimResult for the result object input
loading <- matrix(0, 6, 1) loading[1:6, 1] <- NA LY <- bind(loading, 0.7) RPS <- binds(diag(1)) RTE <- binds(diag(6)) CFA.Model <- model(LY = LY, RPS = RPS, RTE = RTE, modelType="CFA") # We make the examples running only 5 replications to save time. # In reality, more replications are needed. Output <- sim(5, n=500, CFA.Model) # Summarize the sample fit indices summaryFit(Output)
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