It summaries results for either class tssem1FEM,
class tssem1FEM.cluster, class tssem1REM, class
wls, class wls.cluster, class meta, class
meta3X, class reml, class CorPop, or class bootuniR2.
# S3 method for tssem1FEM
summary(object, …)
# S3 method for tssem1FEM.cluster
summary(object, …)
# S3 method for tssem1REM
summary(object, …)
# S3 method for wls
summary(object, df.adjustment=0, R=50, …)
# S3 method for wls.cluster
summary(object, df.adjustment=0, R=50, …)
# S3 method for meta
summary(object, homoStat=TRUE, …)
# S3 method for meta3X
summary(object, allX=FALSE, …)
# S3 method for reml
summary(object, …)
# S3 method for CorPop
summary(object, …)
# S3 method for bootuniR2
summary(object, probs=c(0, 0.1, 0.5, 0.9, 1),
cutoff.chisq.pvalue=0.05, cutoff.CFI=0.9, cutoff.SRMR=0.1, cutoff.RMSEA=0.05, …)
# S3 method for tssem1FEM
print.summary(x, …)
# S3 method for wls
print.summary(x, …)
# S3 method for meta
print.summary(x, …)
# S3 method for meta3X
print.summary(x, …)
# S3 method for reml
print.summary(x, …)
# S3 method for CorPop
print.summary(x, …)
# S3 method for bootuniR2
print.summary(x, …)An object returned from either class
tssem1FEM, class tssem1FEM.cluster,
class tssem1REM, class wls, class wls.cluster,
class meta, class meta3X, class reml or class CorPop.
An object returned from either class summary.tssem1FEM,
class tssem1FEM.cluster, class summary.wls, class
summary.meta, class summary.meta3X, class
summary.reml or class summary.CorPop.
Logical. Whether to conduct a homogeneity test on the effect sizes.
Logical. Whether to report the predictors and the auxiliary variables.
Numeric. Adjust the degrees of freedom
manually. It may be necessary if the df calculated is incorrect when
diag.constraints=TRUE.
Positive integer. The number of parameter bootstrap
replicates when diag.constraints=TRUE.
Quantiles for the parameter estimates.
Cutoff of the p-value for the chi-square statistic.
Cutoff of the CFI.
Cutoff of the SRMR.
Cutoff of the RMSEA.
Further arguments to be passed to printCoefmat