Dear Dr Pornprasertmanit and all,
I am one of newbees of the simsem package.
When I use simsem to do a simulation like the below, I am bit confused by pValue() function.
I know p is the proportion of the number of replications that provide poorer fit (e.g., less CFI value or greater RMSEA value) than the analysis result from the observed data.
Does it mean that the data-fitted model is reliable if p are very small such as <0.05?
Is the smaller the P value the better data-fitted model?
OR just inverse?
Should I need to look at parameter coverages and powers as well?
Yong
library(simsem) | |
library(lavaan) | |
HS.model <- ' visual =~ x1 + x2 + x3 | |
textual =~ x4 + x5 + x6 | |
speed =~ x7 + x8 + x9 ' | |
fit <- cfa(HS.model, data=HolzingerSwineford1939) | |
output.nomis <- sim(1000, n=nrow(HolzingerSwineford1939), model = fit, generate = fit) | |
plotCutoff(output.nomis, 0.05) | |
pValue(fit, output.nomis) |
Does it mean that the data-fitted model is reliable if p are very small such as <0.05?
Is the smaller the P value the better data-fitted model?
OR just inverse?