ScaleGPCM {pleLMA}

Imposes scaling constraint to identify parameters of LMA (GPCM)

Description

Scaling is internal to the function 'fit.gpcm', which fits the GPCM version of the LMA. It imposes the required scaling identification constraint by transforming the conditional covariance matrix 'Phi.mat' to a conditional correlation matrix. The inverse transformation is applied to the current estimates of the slope or 'a' parameters. Category scale values are recomputed using the re-scale slopes (i.e., nu= a*x) and these are put back into the Master data set so that data are ready for the next iteration of the algorithm.

Usage

ScaleGPCM(
  Master,
  item.log,
  Phi.mat,
  PersonByItem,
  npersons,
  nitems,
  ncat,
  nless,
  ntraits,
  starting.sv,
  item.by.trait
)

Arguments

Master

Master/main data set

item.log

Iteration history array, last row are current parameters

Phi.mat

Current phi matrix

PersonByItem

inData (response patterns)

npersons

Number of persons

nitems

Number of items

ncat

Number of categories

nless

Number of unique lambdas (ncat-1)

ntraits

Number of latent traits

starting.sv

Matrix of fixed category scores (nitems x ncat)

item.by.trait

Object that indicates which trait item loads on

Value

Master Master data set with re-scaled scale values

Phi.mat Re-scaled matrix of association parameters