Best Test Design (Wright & Stone, 1979 p. 96) gives formulae for evaluating the statistical quality of a linking constant between dichotomous tests with common items.
When Test A is given to a sample of NA persons, and Test B to a different sample of NB persons, then each item i of the K equally trustworthy common items is estimated to have two difficulties, DiA in Test A and DiB in Test B. DiA and DiB have standard errors of approximately 2.5/NA½ and 2.5/NB½ respectively.
If a cross-plot of the two sets of common items indicates that there is a single constant that adds to all difficulties and abilities in Test B to translate them onto the scale of Test A, then that constant is
with standard error
If NANBN, then
A test of the hypothesis that this linking constant explains the difference between difficulties of common items is
These formulae can be generalized for tests containing polytomous items with both common items and common judges. Tests A and B have K common items and J common judges. Common items have difficulties DiA and DiB. Common judges have severities SjA and SjB. The standard errors of the item and judge measures are obtained from the reported results of analyses of Test A and Test B separately.
If cross-plots of the two sets of common item difficulties and of the two sets of judge severities exhibit approximately 45 trends, then the constants to add to difficulties (the Item Link), severities (the Judge Link) and abilities (GAB) in Test B to translate them onto the scale of Test A are
with standard errors of
A test of the hypothesis that each piece of the linking constant explains the difference between common measures in its facet has the form
When the standard errors of measures within the sets of linking items or judges differ noticeably and their precision is deemed to reflect the influence they should have on the linking constant, then the construction of information-weighted linking constants for the items or judges may be preferred. For instance, the Fisher information in each item difficulty shift is:
Then, the linking constant for the items is
with standard error of
A test of the hypothesis that this linking constant explains the difference between common items is
These item and judge links substitute directly in the earlier formulae for GAB and its standard error.
John Michael Linacre
Linacre J. M. (1998) Linking Constants with Common Items and Judges. Rasch Measurement Transactions 12:1 p. 621.
Linking Constants with Common Items and Judges. Linacre J. M. Rasch Measurement Transactions, 1998, 12:1 p. 621.
Please help with Standard Dataset 4: Andrich Rating Scale Model
|Rasch Measurement Transactions (free, online)||Rasch Measurement research papers (free, online)||Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch||Applying the Rasch Model 3rd. Ed., Bond & Fox||Best Test Design, Wright & Stone|
|Rating Scale Analysis, Wright & Masters||Introduction to Rasch Measurement, E. Smith & R. Smith||Introduction to Many-Facet Rasch Measurement, Thomas Eckes||Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr.||Statistical Analyses for Language Testers, Rita Green|
|Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar||Journal of Applied Measurement||Rasch models for measurement, David Andrich||Constructing Measures, Mark Wilson||Rasch Analysis in the Human Sciences, Boone, Stave, Yale|
|in Spanish:||Análisis de Rasch para todos, Agustín Tristán||Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez|
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