umx (version 1.9.1)

umxFactorScores: Return factor scores from a model as an easily consumable dataframe.

Description

umxFactorScores takes a model, and computes factors scores using the selected method (one of 'ML', 'WeightedML', or 'Regression') It is a simple wrapper around mxFactorScores. For missing data, you must specify the least number of variables allowed for a score (subjects with fewer than minManifests will return a score of NA.

Usage

umxFactorScores(model, type = c("ML", "WeightedML", "Regression"),
  minManifests = NA)

Arguments

model

The model to generate scores from.

type

The method used to compute the score ('ML', 'WeightedML', or 'Regression').

minManifests

The least number of variables required to return a score for a participant (Default = NA).

Value

- dataframe of scores.

References

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

See Also

- mxFactorScores

Other Reporting Functions: loadings.MxModel, tmx_is.identified, umxAPA, umxGetParameters, umxReduce, umxSummary, umx_APA_pval, umx_aggregate, umx_parameters, umx_print, umx_show, umx_time, umx

Examples

# NOT RUN {
m1 = umxEFA(mtcars, factors = 2)
x = umxFactorScores(m1, type = c('Regression'), minManifests = 3)
m1 = umxEFA(mtcars, factors = 1)
x = umxFactorScores(m1, type = c('Regression'), minManifests = 3)
# }