mu: Compute the expected test score by substituting probability...

In TestGardener: Information Analysis for Test and Rating Scale Data

Compute the expected test score by substituting probability of choices for indicator variable 0-1 values. Binary items assumed coded as two choice items.

Description

Compute the expected test score by substituting probability of choices for indicator variable 0-1 values. Binary items assumed coded as two choice items.

Usage

  mu(index, SfdList, scoreList)

Arguments

index	Initial values for score indices in the interval [0,100]. A vector of size N.
SfdList	A numbered list object produced by a TestGardener analysis of a test. Its length is equal to the number of items in the test or questions in the scale. Each member of SfdList is a named list containing information computed during the analysis.
scoreList	A numbered list of length n. Each member contains the weights assigned to each option for that item or question.

Value

A vector of test score values.

Author(s)

Juan Li and James Ramsay

References

Ramsay, J. O., Li J. and Siberg, M. (2020) Full information optimal scoring. Journal of Educational and Behavioral Statistics, 45, 297-315.

Ramsay, J. O., Li J. and Siberg, M. (2020) Better rating scale scores with information-based psychometrics. Psych, 2, 347-360.

See Also

scoreDensity

Examples

#  Example 1.  Compute expected sum score values for the 
#  short SweSAT multiple choice test with 24 items and 1000 examinees
scoreList <- Quant_13B_problem_dataList$scoreList
SfdList   <- Quant_13B_problem_parmList$SfdList
index     <- Quant_13B_problem_parmList$index
muvec     <- mu(index, SfdList, scoreList)
par(c(1,1))
hist(muvec,11)

TestGardener documentation built on Nov. 24, 2023, 5:08 p.m.