DistractorAnalysis() R function from [ShinyItemAnalysis]

Distractor analysis

Performs distractor analysis for each item and optional number of groups.


DistractorAnalysis(
  Data,
  key,
  item = "all",
  p.table = FALSE,
  num.groups = 3,
  criterion = NULL,
  crit.discrete = FALSE,
  cut.points,
  data,
  matching,
  match.discrete
)

Arguments

Data: character: data matrix or data.frame with rows representing unscored item responses from a multiple-choice test and columns corresponding to the items.
key: character: answer key for the items. The key must be a vector of the same length as ncol(Data). In case it is not provided, criterion needs to be specified.
item: numeric or character: either character "all" to apply for all items (default), or a vector of item names (column names of Data), or item identifiers (integers specifying the column number).
p.table: logical: should the function return the proportions? If FALSE (default), the counts are returned.
num.groups: numeric: number of groups to which are the respondents split.
criterion: numeric: numeric vector. If not provided, total score is calculated and distractor analysis is performed based on it.
crit.discrete: logical: is criterion discrete? Default value is FALSE. See details.
cut.points: numeric: numeric vector specifying cut points of criterion. See details.
data: deprecated. Use argument Data instead.
matching: deprecated. Use argument criterion instead.
match.discrete: deprecated. Use argument crit.discrete

instead.

Details

This function is an adapted version of the distractor.analysis() function from CTT package. In case that no criterion is provided, the scores are calculated using the item Data and key. The respondents are by default split into the num.groups-quantiles and the number (or proportion) of respondents in each quantile is reported with respect to their answers. In case that criterion is discrete (crit.discrete = TRUE), criterion is split based on its unique levels. Other cut points can be specified via cut.points

argument.

Examples


Data <- dataMedicaltest[, 1:100]
Databin <- dataMedical[, 1:100]
key <- dataMedicalkey

# distractor analysis for all items
DistractorAnalysis(Data, key)

# distractor analysis for item 1
DistractorAnalysis(Data, key, item = 1)
## Not run:

# distractor analysis with proportions
DistractorAnalysis(Data, key, p.table = TRUE)

# distractor analysis for 6 groups
DistractorAnalysis(Data, key, num.group = 6)

# distractor analysis using specified criterion
criterion <- round(rowSums(Databin), -1)
DistractorAnalysis(Data, key, criterion = criterion)

# distractor analysis using discrete criterion
DistractorAnalysis(Data, key, criterion = criterion, crit.discrete = TRUE)

# distractor analysis using groups specified by cut.points
DistractorAnalysis(Data, key, cut.points = seq(10, 96, 10))
## End(Not run)