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Subscores

All-access Pass
This provides immediate access to ALL print and digital modules in the portal by "registering" you for each and displaying all modules as a single collection as part of this pass.
All-access Pass (PRINT ONLY)
This provides access to a ZIP folder with all 45 previously published print modules.
Digital Module 07: Subscore Evaluation & Reporting
In this digital ITEMS module, Dr. Sandip Sinharay reviews the status quo on the reporting of subscores, which includes how they are used in operational reporting, what kinds of professional standards they need to meet, and how their psychometric properties can be evaluated. Keywords: Diagnostic scores, disattenuation, DETECT, DIMTEST, factor analysis, multidimensional item response theory (MIRT), proportional reduction in mean squared error (PRMSE), reliability, subscores
Module 32: Subscores
In this print module, Dr. Sandip Sinharay, Dr. Gautam Puhan, and Dr. Shelby J. Haberman provide an introduction to the issue of the added value of subscores using operational and simulated data. Keywords: added value, augmented subscore, classical test theory, CTT, diagnostic score, item response theory, IRT, mean squared error, proportional reduction in mean squared error, PRMSE, reliability
Module 37: Improving Subscore Value through Item Removal
In this print module, Dr. Richard A. Feinberg and Dr. Howard Wainer show, for a broad range of conditions of item overlap on subscores, that the value of the subscore is always improved through the removal of items with little diagnostic value. Keywords: added value, classical test theory, CTT, diagnostic value, empirical Bayes, ​item removal, overlapping items, ReliaVAR plots, simulation, subscores
Module 38: A Simple Equation to Predict a Subscore’s Value
In this print module, Dr. Richard A. Feinberg and Dr. Howard Wainer help analysts determine if a particular subscore adds enough value to be worth reporting through the use of a simple linear equation. Keywords: added value, ​classical test theory, CTT, linear equation, subscores, reliability, orthogonal, proportional reduction in mean squared error, PRMSE