Under the linear logistic test model, a weight is
assigned to each cognitive operation used to
respond to an item. The allocation of these
weights is open to misspecification that can result
in faulty estimates of the basic parameters. The
effect on root mean squares (RMSs) of the difference
between the parameter estimates obtained
under misspecification conditions and those
obtained under correct specification conditions was
examined. Six levels of misspecification and four
sample sizes were used. Even a small number of
errors in the weight specifications resulted in large
RMS values. However, weight matrices with a high
proportion of nonzero elements tended to yield
RMSs that were approximately half as large as
those with a small number of nonzero elements.
Although sample size had some effect on the RMS
values, it was quite small compared to that due to
the level of misspecification of the weights. The
results suggest that because specifying the elements
in the weight matrix is a subjective process, it must
be done with great care. Index terms: error rates,
linear logistic test model, misspecification, parameter
estimation, weight matrix.
Baker, Frank B. (1993). Sensitivity of the linear logistic test model to misspecification of the weight matrix. Applied Psychological Measurement, 17, 201-210. doi:10.1177/014662169301700301
Baker, Frank B..
Sensitivity of the linear logistic test model to misspecification of the weight matrix.
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