nullRMSEA | 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 also http://davidakenny.net/cm/fit.htm
A value of RMSEA of the null model (a numeric
vector)
returned invisibly.
Ruben Arslan (Humboldt-University of Berlin, rubenarslan@gmail.com)
Terrence D. Jorgensen (University of Amsterdam; TJorgensen314@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)
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