umx_polytriowise {umx} | R Documentation |
FIML-based trio-based polychoric, polyserial, and Pearson correlations
Description
Compute polychoric/polyserial/Pearson correlations with FIML in OpenMx.
Usage
umx_polytriowise(
data,
useDeviations = TRUE,
printFit = FALSE,
use = "any",
tryHard = c("no", "yes", "ordinal", "search")
)
Arguments
data |
Dataframe |
useDeviations |
Whether to code the mode using deviation thresholds (default = TRUE) |
printFit |
Whether to print information about the fit achieved (default = FALSE) |
use |
parameter (default = "any") |
tryHard |
'no' uses normal mxRun (default), "yes" uses mxTryHard, and others used named versions: "mxTryHardOrdinal", "mxTryHardWideSearch" |
Value
- matrix of correlations
References
- doi:10.3389/fpsyg.2016.00528
See Also
Other Data Functions:
noNAs()
,
prolific_anonymize()
,
prolific_check_ID()
,
prolific_read_demog()
,
umxFactor()
,
umxHetCor()
,
umx_as_numeric()
,
umx_cont_2_quantiles()
,
umx_lower2full()
,
umx_make_MR_data()
,
umx_make_TwinData()
,
umx_make_fake_data()
,
umx_make_raw_from_cov()
,
umx_merge_randomized_columns()
,
umx_polychoric()
,
umx_polypairwise()
,
umx_read_lower()
,
umx_rename()
,
umx_reorder()
,
umx_score_scale()
,
umx_select_valid()
,
umx_stack()
,
umx_strings2numeric()
,
umx
Examples
tmp = mtcars
tmp$am = umxFactor(mtcars$am)
tmp$vs = umxFactor(mtcars$vs)
tmp = umx_scale(tmp)
x = umx_polytriowise(tmp[, c("hp", "mpg", "am", "vs")], tryHard = "yes")
x$R
cor(mtcars[, c("hp", "mpg", "am", "vs")])