[Rasch] CTT vs Rasch
Mike Linacre (RMT)
rmt at rasch.org
Tue Jun 10 08:01:32 EST 2008
Anthony asks "Is there any source available to show how and why Rasch
accommodate missing data? What property of the Rasch modelling takes care
of missing data?"
The exact details depend on the estimation method, but in general, the
1.) Rasch models are formulated at the individual observation level, and
2.) the accumulation of the observations for any parameter are its
Accordingly, in principle, only the observations which relate to a
parameter are required in order to estimate that parameter.
Consequently, the Rasch model does not know that any data are "missing", it
only knows about the data that are present.
If the data are rectangularly complete, then short-cuts can be taken in the
estimation process, such as the non-iterative PROX method, or using a
scoring table to assign measures to all the persons. Conditional Maximum
Likelihood Estimation (CMLE) becomes computationally overwhelming if there
are more than a few missing data patterns.
Editor, Rasch Measurement Transactions
rmt at rasch.org www.rasch.org/rmt/ Latest RMT: 21:4 Spring 2008
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