R: Bootstrap distribution of standardized RAM path coefficients

mxBootstrapStdizeRAMpaths {OpenMx} | R Documentation

## Bootstrap distribution of standardized RAM path coefficients

### Description

Uses the bootstrap distribution of a RAM model's free parameters to produce a bootstrap distribution of standardized path coefficients. Model must have already been run through `mxBootstrap()`.

### Usage

    mxBootstrapStdizeRAMpaths(model, bq=c(.25,.75),
    	method=c('bcbci','quantile'), returnRaw=FALSE)

### Arguments

`model` | An MxModel that uses RAM expectation and has already been run through `mxBootstrap()`.
`bq` | Quantiles corresponding to the lower and upper limits, respectively, of the bootstrap confidence interval.
`method` | Character string. One of 'bcbci' or 'quantile'.
`returnRaw` | Logical; should the function return the raw bootstrapping results? Defaults to `FALSE`, in which case a dataframe summarizing the results is returned.

### Details

In effect, what `mxBootstrapStdizeRAMpaths()` does is use the point estimates from each bootstrap replication to produce `mxStandardizeRAMpaths()` output for each replication. The output of `mxStandardizeRAMpaths()` has one entry for each nonzero path coefficient. Therefore, it is possible (though unlikely) that the number of nonzero paths, or which elements of the `A` and `S` RAM matrices are nonzero, may vary among bootstrap replications. Such an occurrence defies simple summary of the standardized paths' bootstrapping results. In this case, a raw list of bootstrapping results is returned, with a warning, if `returnRaw=TRUE`, or an error is throw if `returnRaw=FALSE`.

`mxBootstrapStdizeRAMpaths()` ignores any submodels of `model`. That is, it must be able to find, in the MxModel it is provided, a RAM expectation and an MxComputeBootstrap object. It can be run on submodels directly,

### Value

Under extraordinary circumstances described above, `mxBootstrapStdizeRAMpaths()` may return a list object. In ordinary circumstances, if `returnRaw=FALSE` (default), it returns a dataframe containing, inter alia, the standardized path coefficients as estimated from the real data, their bootstrap SEs, and the lower and upper limits of a bootstrap confidence interval. If instead `returnRaw=TRUE`, `mxBootstrapStdizeRAMpaths()` returns a matrix containing the raw bootstrap results; this matrix has one column per nonzero path coefficient, and one row for each succesfully converged bootstrap replication.

### See Also

`mxBootstrap()`, `mxStandardizeRAMpaths()`, `mxBootstrapEval`, `mxSummary`

### Examples

    require(OpenMx)
    data(myFADataRaw)
    myFADataRaw <- myFADataRaw[,c("x1","x2","x3","x4","x5","x6")]
    dataRaw      <- mxData( observed=myFADataRaw, type="raw" )
    resVars      <- mxPath( from=c("x1","x2","x3","x4","x5","x6"), arrows=2,
                            free=TRUE, values=c(1,1,1,1,1,1),
                            labels=c("e1","e2","e3","e4","e5","e6") )
    latVar       <- mxPath( from="F1", arrows=2,
                            free=TRUE, values=1, labels ="varF1" )
    facLoads     <- mxPath( from="F1", to=c("x1","x2","x3","x4","x5","x6"), arrows=1,
                            free=c(FALSE,TRUE,TRUE,TRUE,TRUE,TRUE), values=c(1,1,1,1,1,1),
                            labels =c("l1","l2","l3","l4","l5","l6") )
    means        <- mxPath( from="one", to=c("x1","x2","x3","x4","x5","x6","F1"), arrows=1,
                            free=c(TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE),
                            values=c(1,1,1,1,1,1,0),
                            labels =c("meanx1","meanx2","meanx3",
                                      "meanx4","meanx5","meanx6",NA) )
    oneFactorModel <- mxModel("Common Factor Model Path Specification", type="RAM",
                            manifestVars=c("x1","x2","x3","x4","x5","x6"), latentVars="F1",
                            dataRaw, resVars, latVar, facLoads, means)
    oneFactorFit <- mxRun(oneFactorModel)
    set.seed(170505)

    ## Not run: oneFactorBoot <- mxBootstrap(oneFactorFit)
    mxBootstrapStdizeRAMpaths(oneFactorBoot)
    ## End(Not run)

[Package OpenMx version 2.9.6 Index]