rsem.print {rsem} | R Documentation |
Organize the output for Lavaan with robust s.e. and test statistics
Description
Organize the output for Lavaan with robust s.e. and test statistics. Modified from the print function of Lavaan.
Usage
rsem.print(object, robust.se, robust.fit, estimates=TRUE, fit.measures=FALSE,
standardized=FALSE, rsquare=FALSE, std.nox=FALSE, modindices=FALSE)
Arguments
object |
Output from lavaan analysis, such as growth, factor, sem functions. |
robust.se |
Robust standard error from the function rsem.se |
robust.fit |
Robust fit statistics from the function rsem.fit |
estimates |
Show parameter estimates |
fit.measures |
Show fit statistics of lavaan (no need for it) |
standardized |
standardized coefficients |
rsquare |
R square for dependent variables. |
std.nox |
to add |
modindices |
Modification indices |
Details
This function will run the robust analysis and output results.
Value
If EQSmodel
is not supplied
sem |
Information for SEM analysis including estimated means, covariance matrix and their sandwich type covariance matrix in the order of mean first and then covariance matrix. |
misinfo |
Information related to missing data pattern |
em |
Results from expectation robust algorithm |
ascov |
Covariance matrix |
If EQSmodel
is supplied,
sem |
Information for SEM analysis including estimated means, covariance matrix and their sandwich type covariance matrix according to the requirement of EQS. |
In addition, the following model parameters are from EQS
fit.stat |
Fit indices and associated p-values |
para |
Parameter estimates |
eqs |
All information from REQS |
Author(s)
Ke-Hai Yuan and Zhiyong Zhang
References
Ke-Hai Yuan and Zhiyong Zhang (2011) Robust Structural Equation Modeling with Missing Data and Auxiliary Variables
See Also
rsem.pattern
, rsem.emmusig
, rsem.Ascov
Examples
##\dontrun{
## an example
data(mardiamv25)
names(mardiamv25)<-paste('V', 1:5, sep='')
fa.model<-'f1 =~ V1 + V2
f2 =~ V4 + V5
f1 ~ 1
f2 ~ 1
V1 ~0*1
V2 ~0*1
V4 ~0*1
V5 ~0*1'
pat<-rsem.pattern(mardiamv25)
phi<-0.1
musig<-rsem.emmusig(pat, varphi=phi)
res.lavaan<-sem(fa.model, sample.cov=musig$sigma, sample.mean=musig$mu, sample.nobs=88,mimic='EQS')
ascov<-rsem.Ascov(pat, musig, varphi=phi)
robust.se<-rsem.se(res.lavaan, ascov$Gamma)
robust.fit <- rsem.fit(res.lavaan, ascov$Gamma, musig)
rsem.print(res.lavaan, robust.se, robust.fit)
## }