umxFactor: umxFactor

Description

A convenient version of mxFactor() supporting the common case in which the factor levels are those in the variable.

Usage

umxFactor(
  x = character(),
  levels = NULL,
  labels = levels,
  exclude = NA,
  ordered = TRUE,
  collapse = FALSE,
  verbose = FALSE,
  sep = NA
)

Value

mxFactor()

Arguments

x: A variable to recode as an mxFactor (see mxFactor())
levels: (default NULL). Like factor() but UNLIKE mxFactor(), unique values will be used if levels not specified.
labels: = levels (see mxFactor())
exclude: = NA (see mxFactor())
ordered: = TRUE By default return an ordered mxFactor
collapse: = FALSE (see mxFactor())
verbose: Whether to tell user about such things as coercing to factor
sep: If twin data are being used, the string that separates the base from twin index will try and ensure factor levels same across all twins.

References

https://github.com/tbates/umx, https://tbates.github.io

Other Data Functions: noNAs(), prolific_anonymize(), prolific_check_ID(), prolific_read_demog(), 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_polytriowise(), umx_read_lower(), umx_rename(), umx_reorder(), umx_score_scale(), umx_select_valid(), umx_stack(), umx_strings2numeric(), umx

Examples

Run this code

umxFactor(letters)
umxFactor(letters, verbose = TRUE) # report coercions
umxFactor(letters, ordered = FALSE) # non-ordered factor like factor(x)
# Dataframe example:
x = umx_factor(mtcars[,c("cyl", "am")], ordered = FALSE); str(x)
# =================
# = Twin example: =
# =================
data(twinData)
tmp = twinData[, c("bmi1", "bmi2")]
tmp$bmi1[tmp$bmi1 <= 22] = 22
tmp$bmi2[tmp$bmi2 <= 22] = 22
# remember to factor _before_ breaking into MZ and DZ groups
x = umxFactor(tmp, sep = ""); str(x)
xmu_check_levels_identical(x, "bmi", sep="")

# Simple example to check behavior
x = round(10 * rnorm(1000, mean = -.2))
y = round(5 * rnorm(1000))
x[x < 0] = 0; y[y < 0] = 0
jnk = umxFactor(x); str(jnk)
df  = data.frame(x = x, y = y)
jnk = umxFactor(df); str(jnk)