FitStack: Up-dates association parameters of the nominal model

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

Description

Discrete choice model (conditional multinominal logistic regression model) is fit to stacked data to up-date the matrix of association parameters of the LMA that corresponds to the nominal item response model. This is a function internal to 'fit.nominal' and is used for multi-dimensional models. The function is similar to 'fit.StackGPCM'. This function is unlikely to be run outside of 'fit.nominal' or 'ple.lma'.

Usage

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

Arguments

Master	Master data set from which stacked data is created
item.log	Last row contains current scale values (item.history)
phi.log	Last row contains current estimates of phi
fstack	Formula for stacked regression
TraitByTrait	inTraitAdj matrix
pq.mat	Summing array to get rest scores and totals
npersons	Number of persons
nitems	Number of items
ncat	Number of categories per item
nless	Number of categories less 1 (unique lambdas & unique nus)
ntraits	Number of latent traits
Maxnphi	Number of phis to be estimated
PhiNames	Names of the Phi parameters
LambdaNames	Names of lambdas that correspond to those in Master

Value

Phi.mat Matrix of up-dated estimates of assocation (phi) parameters

phi.log History of iterations log likelihood and estimates of lambda and phi parameters

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