mxMmodModel: Create an MMOD

In mxmmod: Measurement Model of Derivatives in 'OpenMx'

Description

This function builds a Measurement Model of Derivatives (MMOD; Estabrook 2015) with a given factor structure.

Usage

mxMmodModel(
  data,
  modelName,
  idvar,
  timevar,
  structure,
  orthogonal = F,
  embed_dim = NULL,
  fiml = F
)

Arguments

data	a data frame with measurements in long format
modelName	name for the resulting model
idvar	name of column for subject IDs
timevar	name of column for measurement occasion
structure	factor structure, see 'Details'
orthogonal	if true, fix correlations between factors to 0 (A factor and its derivatives will still intercorrelate)
embed_dim	time delay embedding dimension
fiml	if true, use raw data to fit model with FIML. Otherwise, fit using cov matrix (dropping missing values if necessary).

Details

The structure argument is a list of latent factors and their mappings to manifest variables. For example, a one factor structure would be:

list(F1 = c('m1', 'm2', 'm3', 'm4', 'm5', 'm6'))

And a two factor structure would be:

list(F1 = c('m1', 'm2', 'm3'), F2 = c('m4', 'm5', 'm6'))

Value

an MMOD as an mxModel object

Examples

data(nlsy97depression)
# Fit one factor MMOD
structure <- list(
  F1 = c('nervous', 'down', 'depressed', 'calm', 'happy')
)
mmod_model <- mxMmodModel(data=nlsy97depression,
                          modelName='1 Factor MMOD',
                          idvar='pid', timevar='occasion', structure=structure)
mmod_fit <- OpenMx::mxRun(mmod_model)
summary(mmod_fit)

mxmmod documentation built on May 18, 2021, 5:09 p.m.