psketti_distractor: Distractor Analysis Plots

In SBGalvin/psketti: Generating Investigatory Plots and Tables for Rasch Analysis

Description

Implementation of a graphical (Asril and Marais, 2011) approach to assigning a partial credit scoring system to data previously estimated with a dichotomous Rasch model. The function console output prints object details, a list of items, and generic example of how to call the plot.

Usage

psketti_distractor(
  x,
  ID,
  Item,
  K,
  response_options,
  eRm.obj,
  p.style = "present",
  distractor_colours = NULL,
  ncut = 10
)

Arguments

x	A long formatted dataframe
ID	column name for ID column
Item	column name for Item column
K	column name for column containing multiple choice responses.
response_options	An ordered factor object to arrange column order in the distractor table.
eRm.obj	An object of class eRm and model RM. Use 'eRm::RM(score_data)' to create this object. To plot empirical values for PCM see 'pskettify', 'psketti' and 'psketto'.
p.style	Plot output style, "print" for black and white, or "present" for color. Defaults to "present".
distractor_colours	An optional vector of colours for distractor plot lines. Must be the same length as response_options. Defaults to 'NULL' for viridis color palette.
ncut	Number of cut points to use for the theta axis. Defaults to ncut = 10. You can also set ncut = "Raw" to use the raw theta scores; which is only advisable if the ability data is uniformly distributed.

Value

Plot.List is a list object containing plots of empirical distractor proportions plotted against the dichotomous Rasch IRF.

Examples

library(eRm)
library(psketti)
data("FakeData")
Fake_Data_scores <- reshape(FakeData[, c("ID", "Item", "X")],
                            timevar = "Item",
                            idvar = "ID",
                            direction = "wide")

# set column names to be equal to original item names
names(Fake_Data_scores) <- c("ID",
                             paste0("i",
                                    sprintf(fmt  = "%02d", 1:23)))

row.names(Fake_Data_scores) <- Fake_Data_scores$ID  # set ID as row names
Fake_Data_scores$ID         <- NULL                 # drop the ID column
fake_rm                     <- RM(Fake_Data_scores) # fit a Rasch Model

# Prepare response options factor
r_o <- factor(sort(unique(FakeData$K)),          # input var
              levels = sort(unique(FakeData$K)), # factor levels
              ordered = TRUE)                    # ordered

# multiple plots
spag_plot <- psketti_distractor(ID = "ID",              # set ID column
                                Item = "Item",          # set Item column
                                K= "K",                 # Set resp categories
                                x = FakeData,           # select data
                                eRm.obj = fake_rm,      # select eRm object
                                response_options = r_o, # set resp options
                                p.style = "present")    # set plotting style

spag_plot                         # plot call instructions
spag_plot$Plot.List[['i01']][[1]] # plot item 1

SBGalvin/psketti documentation built on March 13, 2021, 1:47 p.m.