Abstract
This paper deals with beta regression models with a covariate that is not directly observed; instead, it is replaced by a surrogate covariate that underpredicts its actual value. We propose a multiplicative errors-in-variables model tailored for this situation and develop calibration regression and pseudo-likelihood-based inference for the unknown parameters. The impact of ignoring the measurement error and the performance of the inference methods are evaluated through simulations and a real data illustration.
Funding Statement
The second author gratefully acknowledges funding provided by Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq (Grant No. 305963-2018-0).
Acknowledgments
The authors thank the reviewers for valuable suggestions that improved the paper.
Although no longer with us, the authors would like to offer special thanks and deep appreciation to Professor Heleno Bolfarine, who continues to inspire us with his example and dedication to the scientific research.
Citation
Jalmar M. F. Carrasco. Silvia L. P. Ferrari. Reinaldo B. Arellano–Valle. "Multiplicative errors-in-variables beta regression." Braz. J. Probab. Stat. 37 (2) 249 - 262, June 2023. https://doi.org/10.1214/22-BJPS543
Information
