| nullRMSEA {semTools} | R Documentation |
Calculate the RMSEA of the null (baseline) model
nullRMSEA(object, scaled = FALSE, silent=FALSE)
object |
The lavaan model object provided after running the |
scaled |
If |
silent |
If |
RMSEA of the null model is calculated similar to the formula provided in the lavaan package. The standard formula of RMSEA is
RMSEA =√{\frac{χ^{2}}{N \times df} - \frac{1}{N}} \times √{G}
where χ^{2} is the chi-square test statistic value of the target model, N is the total sample size, df is the degree of freedom of the hypothesized model, G is the number of groups. Kenny proposed in his website that
"A reasonable rule of thumb is to examine the RMSEA for the null model and make sure that is no smaller than 0.158. An RMSEA for the model of 0.05 and a TLI of .90, implies that the RMSEA of the null model is 0.158. If the RMSEA for the null model is less than 0.158, an incremental measure of fit may not be that informative."
See http://davidakenny.net/cm/fit.htm.
A value of RMSEA of the null model. This value is hidden. Users may be assigned the output of this function to any object for further usage.
Ruben Arslan (Humboldt-University of Berlin, rubenarslan@gmail.com)
Kenny, D. A., Kaniskan, B., & McCoach, D. B. (2015). The performance of RMSEA in models with small degrees of freedom. Sociological Methods Research, 44(3), 486-507. doi:10.1177/0049124114543236
miPowerFit For the modification indices and their power approach for model fit evaluation
moreFitIndices For other fit indices
HS.model <- ' visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9 '
fit <- cfa(HS.model, data=HolzingerSwineford1939)
nullRMSEA(fit)