Stan Models for the Paired Comparison Factor Model

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Documentation for package ‘pcFactorStan’ version 1.5.4

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

Help Pages

pcFactorStan-package	Stan Models for the Pairwise Comparison Factor Model
calibrateItems	Determine the optimal scale constant for a set of items
cmp_probs	Item response function for pairwise comparisons
filterGraph	Filter graph to remove vertices that are not well connected
findModel	Given a model name, return stanmodel object
generateCovItems	Generate paired comparison data with random correlations between items
generateFactorItems	Generate paired comparison data for a factor model
generateItem	Generate paired comparison data for one or more items given absolute latent scores
generateSingleFactorItems	Generate paired comparison data with a common factor that accounts for some proportion of the variance
itemModelExplorer	A Shiny app to experiment with the item response model
normalizeData	Normalize data according to a canonical order
outlierTable	List observations with Pareto values larger than a given threshold
parDistributionCustom	Produce data suitable for plotting parameter distributions
parDistributionFor	Produce data suitable for plotting parameter distributions
parInterval	Produce data suitable for plotting parameter estimates
pcFactorStan	Stan Models for the Pairwise Comparison Factor Model
pcStan	Fit a paired comparison Stan model
phyActFlowPropensity	Physical activity flow propensity
prepCleanData	Transforms data into a form tailored for efficient evaluation by Stan
prepData	Transforms data into a form tailored for efficient evaluation by Stan
prepFactorModel	Specify a factor model
prepSingleFactorModel	Specify a single factor model
responseCurve	Produce data suitable for plotting item response curves
roundRobinGraph	Create an edge list with round-robin connectivity
toLoo	Compute approximate leave-one-out (LOO) cross-validation for Bayesian models using Pareto smoothed importance sampling (PSIS)
twoLevelGraph	Create an edge list with a random two level connectivity
unfactor	Turn a factor back into a vector of integers
withoutIndex	Remove the array indexing from a parameter name