| 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 |