View source: R/dataSimulation.R
dataSimulation | R Documentation |
Estimate sum score,s score index values theta and test information values bias and mean squared errors using simulated data.
dataSimulation(dataList, parList, theta.pop = seq(0, 100, len = 101), nsample = 1000)
dataList |
The list object set up by function |
parList |
The list object containing objects compuated by function
|
theta.pop |
A vector containing true values of theta to be estimated using simulated data. |
nsample |
The number of simulated samples. |
A named list object containing objects produced from analyzing the simulations, one set for each simulation:
Sum score estimates
Score index estimates
Expected sum score estimates
Total arc length estimates
True or population score index values
Expected sum score population values
Total test length population values
Number of items
Number of theta values
Fine mesh over score index range
Five marker percentages: 5, 25, 50, 75 and 95
Juan Li and James Ramsay
Ramsay, J. O., Li J. and Wiberg, M. (2020) Full information optimal scoring. Journal of Educational and Behavioral Statistics, 45, 297-315.
Ramsay, J. O., Li J. and Wiberg, M. (2020) Better rating scale scores with information-based psychometrics. Psych, 2, 347-360.
http://testgardener.azurewebsites.net
scorePerformance
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