Item-Total correlation (ITC) is a Pearson's correlation of an item with the Number-Right Score (NRS) or total score. This function is applicable only to binary response data.
The ITC is a measure of item discrimination, indicating how well an item distinguishes between high and low performing examinees.
ItemTotalCorr(U, na = NULL, Z = NULL, w = NULL)# S3 method for default
ItemTotalCorr(U, na = NULL, Z = NULL, w = NULL)
# S3 method for binary
ItemTotalCorr(U, na = NULL, Z = NULL, w = NULL)
# S3 method for ordinal
ItemTotalCorr(U, na = NULL, Z = NULL, w = NULL)
A numeric vector of item-total correlations. Values typically range from -1 to 1, where:
Values near 1: Strong positive discrimination
Values near 0: No discrimination
Negative values: Potential item problems (lower ability students performing better than higher ability students)
Either an object of class "exametrika" or raw data. When raw data is given,
it is converted to the exametrika class with the dataFormat function.
Values to be treated as missing values.
Missing indicator matrix of type matrix or data.frame. Values of 1 indicate observed responses, while 0 indicates missing data.
Item weight vector specifying the relative importance of each item.
The correlation is calculated between:
Each item's responses (0 or 1)
The total test score (sum of correct responses)
Higher positive correlations indicate items that better discriminate between high and low ability examinees.
# using sample dataset
ItemTotalCorr(J15S500)
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