Pseudo-Likelihood Estimation of Log-Multiplicative Association Models

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Documentation for package ‘pleLMA’ version 0.2.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

convergence.stats	Computes statistics to assess convergence of the nominal model
convergenceGPCM	Computes statistics to assess convergence for generalized partial credit models
dass	Dateframe of responses to items from depression, anxiety, and stress scales
error.check	Checks for basic errors in input to the 'ple.lma' function
fit.gpcm	Fits LMA model where category scale values equal a_im * x_j
fit.independence	Fits the log-linear model of independence
fit.nominal	Fits the nominal model
fit.rasch	Fits an LMA using fixed category scores
FitStack	Up-dates association parameters of the nominal model
fitStackGPCM	Up-dates association parameters of the GPCM by fitting model to stacked data
item.gpcm	Estimates item parameters of LMA with linear restrictions on category scores
ItemData	Prepares data for up-dating scale value parameters of nominal model
ItemGPCM.data	Creates data frame up-dating phi parameters of the gpcm.
ItemLoop	loops through items and up-dates estimates of scale values for each item in Nominal Model
iterationPlot	Plots estimated parameters by iteration for the gpcm and nominal models
lma.summary	Produces a summary of results
ple.lma	Main function for estimating parameters of LMA models
reScaleItem	Re-scales the category scale values and Phi after convergence of the nominal model
Scale	Imposes scaling constraint to identify parameters of the LMA (nominal) model
ScaleGPCM	Imposes scaling constraint to identify parameters of LMA (GPCM)
scalingPlot	Graphs estimated scale values by integers of the LMA (nominal) model
set.up	Sets up the data based on input data and model specifications
StackData	Prepares data for up-dating association parameters of a multidimensional nominal LMA
StackDataGPCM	Prepares data for up-dating association parameters of LMA (GPCM) model
theta.estimates	Computes estimates of theta (values on latent trait(s)) for all LMA models
vocab	Dataframe of response to vocabulary items from the 2018 General Social Survey