Slope estimation in structural line-segment heteroscedastic measurement error models.
This paper extends the line-segment parametrization of the structural measurement error (ME) model to situations in which the error variance on both variables is not constant over all observations. Under these conditions, we develop a method-of-moments estimate of the slope, and derive its asymptotic variance. We further derive an accurate estimator of the variability of the slope estimate based on sample data in a rather general setting. We perform simulations that validate our results and demonstrate that our estimates are more precise than estimates under a different model when the ME variance is not small. Finally, we illustrate our estimation approach using real data involving heteroscedastic ME, and compare its performance with that of earlier models.
McAssey
Michael P
MP
Department of Statistics, University of California at Davis, MSB 4118, 1 Shields Ave., Davis, CA 95616, USA.
Hsieh
Fushing
F
D000704:Analysis of Variance; D015982:Bias; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D016018:Least-Squares Analysis; D016014:Linear Models; D018570:Risk Assessment / Q000379:methods*
Stat Med. 2002 Apr 30;21(8):1089-101
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