Structural Modeling of Measurement Error in Generalized Linear Models with Rasch Measures as Covariates |
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Authors: | Michela Battauz Ruggero Bellio |
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Institution: | 1.Department of Statistics,University of Udine,Udine,Italy |
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Abstract: | This paper proposes a structural analysis for generalized linear models when some explanatory variables are measured with
error and the measurement error variance is a function of the true variables. The focus is on latent variables investigated
on the basis of questionnaires and estimated using item response theory models. Latent variable estimates are then treated
as observed measures of the true variables. This leads to a two-stage estimation procedure which constitutes an alternative
to a joint model for the outcome variable and the responses given to the questionnaire. Simulation studies explore the effect
of ignoring the true error structure and the performance of the proposed method. Two illustrative examples concern achievement
data of university students. Particular attention is given to the Rasch model. |
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Keywords: | |
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