View source: R/MxFitFunctionWLS.R
mxDescribeDataWLS | R Documentation |
Given either a data.frame or an mxData of type raw, this function determines whether mxFitFunctionWLS
will generate expectations for means.
mxDescribeDataWLS(
data,
allContinuousMethod = c("cumulants", "marginals"),
verbose = FALSE
)
data |
the (currently raw) data being used in a |
allContinuousMethod |
the method used to process data when all columns are continuous. |
verbose |
logical. Whether to report diagnostics. |
All-continuous data processed using the "cumulants" method lack means, while all continuous data processed with allContinuousMethod = "marginals" will have means.
When data are not all continuous, allContinuousMethod is ignored, and means are modelled.
- list describing the data.
- mxFitFunctionWLS
, omxAugmentDataWithWLSSummary
# ====================================
# = All continuous, data.frame input =
# ====================================
tmp = mxDescribeDataWLS(mtcars, allContinuousMethod= "cumulants", verbose = TRUE)
tmp$hasMeans # FALSE - no means with cumulants
tmp = mxDescribeDataWLS(mtcars, allContinuousMethod= "marginals")
tmp$hasMeans # TRUE we get means with marginals
# ==========================
# = mxData object as input =
# ==========================
tmp = mxData(mtcars, type="raw")
mxDescribeDataWLS(tmp, allContinuousMethod= "cumulants", verbose = TRUE)$hasMeans # FALSE
mxDescribeDataWLS(tmp, allContinuousMethod= "marginals")$hasMeans # TRUE
# =======================================
# = One var is a factor: Means modelled =
# =======================================
tmp = mtcars
tmp$cyl = factor(tmp$cyl)
mxDescribeDataWLS(tmp, allContinuousMethod= "cumulants")$hasMeans # TRUE - always has means
mxDescribeDataWLS(tmp, allContinuousMethod= "marginals")$hasMeans # TRUE
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