summary: Summary Method for tssem1, wls, meta, and meta3LFIML Objects

In metaSEM: Meta-Analysis using Structural Equation Modeling

Summary Method for tssem1, wls, meta, and meta3LFIML Objects

Description

It summaries results for various class.

Usage

## S3 method for class 'tssem1FEM'
summary(object, ...)
## S3 method for class 'tssem1FEM.cluster'
summary(object, ...)
## S3 method for class 'tssem1REM'
summary(object, robust=FALSE, ...)
## S3 method for class 'wls'
summary(object, df.adjustment=0, ...)
## S3 method for class 'wls.cluster'
summary(object, df.adjustment=0, ...)
## S3 method for class 'meta'
summary(object, homoStat=TRUE, robust=FALSE, ...)
## S3 method for class 'meta3LFIML'
summary(object, allX=FALSE, robust=FALSE, ...)
## S3 method for class 'reml'
summary(object, ...)
## S3 method for class 'CorPop'
summary(object, ...)
## S3 method for class 'Cor3L'
summary(object, ...)
## S3 method for class '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 class 'osmasem'
summary(object, fitIndices=FALSE, numObs, robust=FALSE, ...)
## S3 method for class 'tssem1FEM'
print.summary(x, ...)
## S3 method for class 'wls'
print.summary(x, ...)
## S3 method for class 'meta'
print.summary(x, ...)
## S3 method for class 'meta3LFIML'
print.summary(x, ...)
## S3 method for class 'reml'
print.summary(x, ...)
## S3 method for class 'CorPop'
print.summary(x, ...)
## S3 method for class 'Cor3L'
print.summary(x, ...)
## S3 method for class 'bootuniR2'
print.summary(x, ...)

Arguments

object	An object returned from either class tssem1FEM, class tssem1FEM.cluster, class tssem1REM, class wls, class wls.cluster, class meta, class meta3LFIML, class reml or class CorPop.
x	An object returned from either class summary.tssem1FEM, class tssem1FEM.cluster, class summary.wls, class summary.meta, class summary.meta3LFIML, class summary.reml or class summary.CorPop.
homoStat	Logical. Whether to conduct a homogeneity test on the effect sizes.
allX	Logical. Whether to report the predictors and the auxiliary variables.
robust	Logicial. Whether to use robust standard error from imxRobustSE.
df.adjustment	Numeric. Adjust the degrees of freedom manually. It may be necessary if the df calculated is incorrect when diag.constraints=TRUE.
probs	Quantiles for the parameter estimates.
cutoff.chisq.pvalue	Cutoff of the p-value for the chi-square statistic.
cutoff.CFI	The cutoff of the CFI.
cutoff.SRMR	The cutoff of the SRMR.
cutoff.RMSEA	The cutoff of the RMSEA.
fitIndices	Whether to calculate the chi-square statistic and various goodness-of-fit indices in osmasem. Note. It may take a while since statistics of the saturated and independence models are required.
numObs	The number of observations in calculating the fit statistics in osmasem. If it is missing, the total number of observations is used.
...	Further arguments to be passed to printCoefmat

Note

If the OpenMx status1 is either 0 or 1, the estimation is considered fine. If the OpenMx status1 is other values, it indicates estimation problems. Users should refer to https://openmx.ssri.psu.edu//wiki/errors for more details.

Author(s)

Mike W.-L. Cheung <[e-mail]>

See Also

tssem1, wls, meta, reml, rCor, bootuniR2, osmasem

metaSEM documentation built on Aug. 10, 2023, 1:09 a.m.