The goodness-of-fit statistics of Rasch analysis for items and persons. It consists of Outfit (Unweighted) Mean Square, Infit (Weighted) Mean Square, Outfit ZSTD (Standardized Unweighted Mean Square), and Outfit ZSTD (Standardized Weighted Mean Square)
fitStats(obj, isAlpha = TRUE)# S3 method for fit
summary(object, ...)
itemfit(objFit)
personfit(objFit)
plot_fitStats(objFit, toPlot = c("alpha", "infit"), useName = FALSE, ...)
fitStats() will return a list which contains:
A vector of estimated discrimination parameters for each items.
i.fit Item fit statistics.
i.outfitMSQ A vector of Outfit mean square values for each items.
i.infitMSQ A vector of Infit mean square values for each items.
i.outfitZ A vector of OutfitZ values for each items.
i.infitZ A vector of InfitZ values for each items.
p.fit Person fit statistics.
p.outfitMSQ A vector of Outfit mean square values for each persons.
p.infitMSQ A vector of Infit mean square values for each persons.
p.outfitZ A vector of OutfitZ values for each persons.
p.infitZ A vector of InfitZ values for each persons.
traceMat Some computed matrices in the process. Only if isTraced = TRUE
emat The expected values matrix.
vmat The variance matrix.
cmat The curtosis matrix.
std.res The standardized residual.
The object of class 'pcm' or 'pcmdif'.
Boolean value that indicates whether the discrimination parameters is needed to be estimated or not. The discrimination parameters are estimated using the corresponding models (GPCM or GPCM-DIF).
The object of class 'fit'.
Further arguments to be passed.
The object of class 'fit'.
An array with length two c(x,y), to choose what to plot. There are five options to plot, which are alpha, outfit, infit, outfitz, and infitz
A logical statement whether the name of the variable are going to be used in the plot instead of the variable order.