Literature DB >> 20799248

Slope estimation in structural line-segment heteroscedastic measurement error models.

Michael P McAssey1, Fushing Hsieh.   

Abstract

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.
Copyright © 2010 John Wiley & Sons, Ltd.

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Year:  2010        PMID: 20799248      PMCID: PMC2962777          DOI: 10.1002/sim.4030

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  1 in total

1.  Estimation of an errors-in-variables regression model when the variances of the measurement errors vary between the observations.

Authors:  S B Kulathinal; Kari Kuulasmaa; Dario Gasbarra
Journal:  Stat Med       Date:  2002-04-30       Impact factor: 2.373

  1 in total

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