Description Usage Arguments Value
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'.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | FitStack(
Master,
item.log,
phi.log,
fstack,
TraitByTrait,
pq.mat,
npersons,
nitems,
ncat,
nless,
ntraits,
Maxnphi,
PhiNames,
LambdaNames
)
|
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 |
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
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