fitStackGPCM: Up-dates association parameters of the GPCM by fitting model...

In pleLMA: Pseudo-Likelihood Estimation of Log-Multiplicative Association Models

Description

Discrete choice model (conditional multinomial logistic regression) is fit to stacked data to up-date matrix of association parameters of the LMA that corresponds to the generalized partial credit model. This function is called from 'fit.gpcm', which is called from 'ple.lma'. It is unlikely that it would be run outside of these wrappers. It is only slightly different from 'fitStack' for nominal models.

Usage

fitStackGPCM(
  Master,
  item.log,
  phi.log,
  fstack,
  TraitByTrait,
  starting.sv,
  npersons,
  nitems,
  ncat,
  nless,
  ntraits,
  Maxnphi,
  pq.mat,
  LambdaNames,
  PhiNames
)

Arguments

Master	Master data set from which stacked data is created
item.log	Needed to get most recent values of scale values (item.log)
phi.log	History of estimates parameters from stacked regression
fstack	Forumla for stacked regression
TraitByTrait	inTraitAdj matrix
starting.sv	Fixed category scores
npersons	Number of persons
nitems	Number of items
ncat	Number of categories per item
nless	Number of unique lambdas and unique nus per item
ntraits	Number of latent traits
Maxnphi	Number of phi parameters to bet estimated (NULL for 1 dimensional)
pq.mat	Used to compute rest-scores and totals
LambdaNames	Needed for formula and data for up-dating phi (stacked regresson)
PhiNames	Null for 1D models

Value

Phi.mat Up-dated matrix of phi parameters

item.log of iterations for LogLike, Lambda and phi parameters

pleLMA documentation built on Oct. 6, 2021, 1:08 a.m.