Description Usage Arguments Value Author(s) See Also Examples
View source: R/summarySimResult.R
This function will provide fit index cutoffs for values of alpha, and mean fit index values across all replications.
1 | summaryFit(object, alpha = NULL, improper = TRUE, usedFit = NULL)
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object |
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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
1 2 3 4 5 6 7 8 9 10 11 12 13 | 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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