Scale {pleLMA}

Imposes scaling constraint to identify parameters of the LMA (nominal) model

Description

Scaling is internal to the function 'fit.nominal', which corresponds the the nominal item response theory model. It imposes the required scaling identification constraint by transforming the conditional covariance matrix 'Phi.mat' to a conditional correlation matrix (i.e., set phi_mm=1 for all m). The inverse transformation is applied to the current category scale value estimates and these are put back into the Master data frame so that data are ready for the next iteration of the algorithm.

Usage

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

Arguments

Master

Current Master data frame.

item.log

Iteration history of LogLike, lambda, and item parameters

Phi.mat

Current phi matrix

PersonByItem

inData

npersons

Number of persons

nitems

Number of items

ncat

Number of categories

nless

Number of unique nus (ncat-1)

ntraits

Number of (latent) dimensions

item.by.trait

Indicates the trait an item load on.

Value

Master Master frame with re-scaled scale values

Phi.mat Re-scaled matrix of association parameters