metaSEM: summary – R documentation

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metaSEM

summary

Summary Method for tssem1, wls, meta, and meta3X 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 'meta3X'
summary(object, allX=FALSE, robust=FALSE, ...)
## S3 method for class 'reml'
summary(object, ...)
## S3 method for class 'CorPop'
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 'meta3X'
print.summary(x, ...)
## S3 method for class 'reml'
print.summary(x, ...)
## S3 method for class 'CorPop'
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 `meta3X`, 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.meta3X`, 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 <mikewlcheung@nus.edu.sg>