By Ludwig Fahrmeir, Brian Francis, Robert Gilchrist, Gerhard Tutz
This quantity provides the printed lawsuits of the joint assembly of GUM92 and the seventh foreign Workshop on Statistical Modelling, held in Munich, Germany from thirteen to 17 July 1992. The assembly aimed to assemble researchers drawn to the improvement and purposes of generalized linear modelling in GUM and people attracted to statistical modelling in its widest experience. This joint assembly outfitted upon the luck of earlier workshops and GUM meetings. past GUM meetings have been held in London and Lancaster, and a joint GUM Conference/4th Modelling Workshop used to be held in Trento. (The complaints of prior GUM conferences/Statistical Modelling Workshops can be found as numbers 14 , 32 and fifty seven of the Springer Verlag sequence of Lecture Notes in Statistics). Workshops were equipped in Innsbruck, Perugia, Vienna, Toulouse and Utrecht. (Proceedings of the Toulouse Workshop seem as numbers three and four of quantity thirteen of the magazine Computational records and knowledge Analysis). a lot statistical modelling is performed utilizing GUM, as is clear from some of the papers in those complaints. therefore the Programme Committee have been additionally partial to encouraging papers which addressed difficulties which aren't simply of sensible significance yet that are additionally appropriate to GUM or different software program improvement. The Programme Committee asked either theoretical and utilized papers. therefore there are papers in a variety of sensible parts, similar to ecology, breast melanoma remission and diabetes mortality, banking and coverage, quality controls, social mobility, organizational behaviour.
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Additional info for Advances in GLIM and Statistical Modelling: Proceedings of the GLIM92 Conference and the 7th International Workshop on Statistical Modelling, Munich, 13–17 July 1992
Annals of Statistics 18, 354-372. APPROACHES TO ESTIMATION WITH ERRORS IN PREDICTORS R. J. Carroll Department of Statistics Texas A&M University College Station, TX 77843 SUMMARY We provide an overview of some approaches to estimation in generalized linear models when predictors are measured with error. These approaches include likelihood, small error, semiparametric and dimension reduction methods. 1. INTRODUCTION There has been an explosion of research in the last ten years in the area of nonlinear and especially generalized linear models with errors in predictors.
Journal of the American Statistical Association, 85, 652663. Carroll, R. J. & Stefanski, L. A. (1992). Meta-analysis, measurement error and corrections for attenuation. Statistics in Medicine, to appear. Carroll, R. J. & Wand, M. P. (1991). Semiparametric estimation in logistic measurement error models. Journal of the Royal Statistical Society, Series B, 53, 573-585. Crouch, E. A. & Spiegelman, D. (1990). The evaluation of integrals of the form J~oo f( t)exp( -t 2 )dt: applications to logistic-normal models.
Wand, M. P. (1991). Semiparametric estimation in logistic measurement error models. Journal of the Royal Statistical Society, Series B, 53, 573-585. Crouch, E. A. & Spiegelman, D. (1990). The evaluation of integrals of the form J~oo f( t)exp( -t 2 )dt: applications to logistic-normal models. Journal of the American Statistical Association, 85, 464-467. Ekholm, A. (1991). Algorithms versus models for analyzing data that contain misclassification errors. Biometrics, 1171-1182. Ekholm, A. & Palmgren, J.