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Skrondal, Anders; Kuha, Jouni – Psychometrika, 2012
The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration…
Descriptors: Computation, Maximum Likelihood Statistics, Error of Measurement, Regression (Statistics)
Peer reviewedRamsay, J. O.; Winsberg, S. – Psychometrika, 1991
A method is presented for estimating the item characteristic curve (ICC) using polynomial regression splines. Estimation of spline ICCs is described by maximizing the marginal likelihood formed by integrating ability over a beta prior distribution. Simulation results compare this approach with the joint estimation of ability and item parameters.…
Descriptors: Ability, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
Blumberg, Carol Joyce – 1988
Traditionally, the errors-in-variables problem is concerned with the point estimation of the slope of the true scores regression line when the regressor is measured with error, and when no specification error is present. In this paper, the errors-in-variables problem is extended to include specification error. Least squares procedures provide a…
Descriptors: Computer Simulation, Equations (Mathematics), Error of Measurement, Graphs

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