Robust designs for generalized linear mixed models with possible model misspecification
@article{Xu2021RobustDF, title={Robust designs for generalized linear mixed models with possible model misspecification}, author={Xiaojian Xu and Sanjoy K. Sinha}, journal={Journal of Statistical Planning and Inference}, year={2021}, volume={210}, pages={20-41} }
7 Citations
Robust Simulation Design for Generalized Linear Models in Conditions of Heteroscedasticity or Correlation
- Computer Science2022 Winter Simulation Conference (WSC)
- 2022
In this paper, a computational approach to robust design for computer experiments without the need to assume independence or identical distribution of errors is developed.
A random model for the scale parameter in the Fréchet populations
- MathematicsJournal of the Korean Statistical Society
- 2021
This paper deals with one-way classification analysis when the response variable follows the one-parameter Frechet distribution and the factor effects are random. The stochastic properties of the…
Model-robust Bayesian design through Generalised Additive Models for monitoring submerged shoals
- Computer Science
- 2022
A Bayesian design strategy to optimise sampling for a shoal deep reef system using three years of pilot data is developed and applied to design future monitoring of sub-merged shoals on the north-west coast of Australia with the aim of improving on current monitoring designs.
Causes of Changing Woodland Landscape Patterns in Southern China
- Environmental ScienceForests
- 2022
Forests are composed of landscape spatial units (patches) of different sizes, shapes, and characteristics. The forest landscape pattern and its trends are closely related to resistance to…
A robust linear mixed-effects model for longitudinal data using an innovative multivariate skew-Huber distribution
- MathematicsJ. Multivar. Anal.
- 2022
D- and I-Optimal design of multi-factor industrial experiments with ordinal outcomes
- EconomicsChemometrics and Intelligent Laboratory Systems
- 2021
Robust designs for dose-response studies: Model and labelling robustness
- MathematicsComput. Stat. Data Anal.
- 2021
References
SHOWING 1-10 OF 23 REFERENCES
Robust designs for generalized linear models with possible overdispersion and misspecified link functions
- MathematicsComput. Stat. Data Anal.
- 2010
Sequential designs for repeated-measures experiments
- Mathematics
- 2016
We discuss optimal sequential designs for analyzing longitudinal data or repeated measurements in the framework of generalized linear mixed models (GLMMs). The construction of optimal designs for…
Designs for Generalized Linear Models With Several Variables and Model Uncertainty
- MathematicsTechnometrics
- 2006
A method is proposed for finding exact designs for experiments that uses a criterion allowing for uncertainty in the link function, the linear predictor, or the model parameters, together with a design search.
Bayesian D-Optimal Designs for Poisson Regression Models
- Computer Science, Mathematics
- 2014
By incorporating informative and/or historical knowledge of the unknown parameters, Bayesian experimental design under the decision-theory framework can combine all the information available to the…
Bayesian D-optimal design for logistic regression model with exponential distribution for random intercept
- Mathematics, Computer Science
- 2016
This article considered logistic regression models with a random intercept having exponential distribution to obtain the Bayesian D-optimal design, which is a function of the quasi-information matrix that depends on the unknown parameters of the model.
Robust sequential designs for nonlinear regression
- Mathematics
- 2002
The authors introduce the formal notion of an approximately specified nonlinear regression model and investigate sequential design methodologies when the fitted model is possibly of an incorrect…
Some robust design strategies for percentile estimation in binary response models
- Mathematics
- 2004
For the problem of percentile estimation of a quantal response curve, the authors determine multiobjective designs which are robust with respect to misspecifications of the model assumptions. They…
Misspecified maximum likelihood estimates and generalised linear mixed models
- Mathematics
- 2001
SUMMARY We investigate the impact of model violations on the estimate of a regression coefficient in a generalised linear mixed model. Specifically, we evaluate the asymptotic relative bias that…