Scale: Imposes scaling constraint to identify parameters of the LMA...

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

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

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