umx_var: Get variances from a df that might contain some non-numeric...

In tbates/umx: Structural Equation Modeling and Twin Modeling in R

Get variances from a df that might contain some non-numeric columns

Description

Pass in any dataframe and get variances despite some non-numeric columns. Cells involving these non-numeric columns are set to ordVar (default = 1).

Usage

umx_var(
  df,
  format = c("full", "diag", "lower"),
  use = c("complete.obs", "pairwise.complete.obs", "everything", "all.obs",
    "na.or.complete"),
  ordVar = 1,
  digits = NULL,
  strict = TRUE,
  allowCorForFactorCovs = FALSE
)

Arguments

df	A dataframe of raw data from which to get variances.
format	to return: options are c("full", "diag", "lower"). Defaults to full, but this is not implemented yet.
use	Passed to cov() - defaults to "complete.obs" (see param default for other options).
ordVar	The value to return at any ordinal columns (defaults to 1).
digits	digits to round output to (Ignored if NULL). Set for easy printing.
strict	Whether to allow non-ordered factors to be processed (default = FALSE (no)).
allowCorForFactorCovs	When ordinal data are present, use heterochoric correlations in affected cells, in place of covariances.

Value

• OpenMx::mxModel()

References

• https://tbates.github.io

See Also

Other Miscellaneous Stats Functions: FishersMethod(), SE_from_p(), geometric_mean(), harmonic_mean(), oddsratio(), reliability(), umx, umxCov2cor(), umxHetCor(), umxParan(), umxWeightedAIC(), umx_apply(), umx_cor(), umx_means(), umx_r_test(), umx_round(), umx_scale()

Examples

tmp     = mtcars[,1:4]
tmp$cyl = ordered(mtcars$cyl) # ordered factor
tmp$hp  = ordered(mtcars$hp)  # binary factor
umx_var(tmp, format = "diag", ordVar = 1, use = "pair")
tmp2 = tmp[, c(1, 3)]
umx_var(tmp2, format = "diag")
umx_var(tmp2, format = "full")

data(myFADataRaw)
df = myFADataRaw[,c("z1", "z2", "z3")]
df$z1 = mxFactor(df$z1, levels = c(0, 1))
df$z2 = mxFactor(df$z2, levels = c(0, 1))
df$z3 = mxFactor(df$z3, levels = c(0, 1, 2))    
umx_var(df, format = "diag")
umx_var(df, format = "full", allowCorForFactorCovs=TRUE)

# Ordinal/continuous mix
data(twinData)
twinData= umx_scale_wide_twin_data(data=twinData,varsToScale="wt",sep= "")
# Cut BMI column to form ordinal obesity variables
obLevels   = c('normal', 'overweight', 'obese')
cuts       = quantile(twinData[, "bmi1"], probs = c(.5, .8), na.rm = TRUE)
twinData$obese1=cut(twinData$bmi1,breaks=c(-Inf,cuts,Inf),labels=obLevels)
twinData$obese2=cut(twinData$bmi2,breaks=c(-Inf,cuts,Inf),labels=obLevels)
# Make the ordinal variables into mxFactors
ordDVs = c("obese1", "obese2")
twinData[, ordDVs] = umxFactor(twinData[, ordDVs])
varStarts = umx_var(twinData[, c(ordDVs, "wt1", "wt2")], 
		format= "diag", ordVar = 1, use = "pairwise.complete.obs")

tbates/umx documentation built on Dec. 14, 2024, 11:28 a.m.