Spectral adjustment for spatial confounding
Biometrika. 2023 Sep;110(3):699-719. doi: 10.1093/biomet/asac069. Epub 2022 Dec 21.ABSTRACTAdjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. We derive necessary conditions on the coherence between the exposure and the unmeasured confounder that ensure the effect of exposure is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. One assumption that ensures identifiability is that confounding present at global scales dissipates at ...
Source: Biometrika - March 19, 2024 Category: Biotechnology Authors: Yawen Guan Garritt L Page Brian J Reich Massimo Ventrucci Shu Yang Source Type: research

Spectral adjustment for spatial confounding
Biometrika. 2023 Sep;110(3):699-719. doi: 10.1093/biomet/asac069. Epub 2022 Dec 21.ABSTRACTAdjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. We derive necessary conditions on the coherence between the exposure and the unmeasured confounder that ensure the effect of exposure is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. One assumption that ensures identifiability is that confounding present at global scales dissipates at ...
Source: Biometrika - March 19, 2024 Category: Biotechnology Authors: Yawen Guan Garritt L Page Brian J Reich Massimo Ventrucci Shu Yang Source Type: research

Spectral adjustment for spatial confounding
Biometrika. 2023 Sep;110(3):699-719. doi: 10.1093/biomet/asac069. Epub 2022 Dec 21.ABSTRACTAdjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. We derive necessary conditions on the coherence between the exposure and the unmeasured confounder that ensure the effect of exposure is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. One assumption that ensures identifiability is that confounding present at global scales dissipates at ...
Source: Biometrika - March 19, 2024 Category: Biotechnology Authors: Yawen Guan Garritt L Page Brian J Reich Massimo Ventrucci Shu Yang Source Type: research

Spectral adjustment for spatial confounding
Biometrika. 2023 Sep;110(3):699-719. doi: 10.1093/biomet/asac069. Epub 2022 Dec 21.ABSTRACTAdjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. We derive necessary conditions on the coherence between the exposure and the unmeasured confounder that ensure the effect of exposure is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. One assumption that ensures identifiability is that confounding present at global scales dissipates at ...
Source: Biometrika - March 19, 2024 Category: Biotechnology Authors: Yawen Guan Garritt L Page Brian J Reich Massimo Ventrucci Shu Yang Source Type: research

Spectral adjustment for spatial confounding
Biometrika. 2023 Sep;110(3):699-719. doi: 10.1093/biomet/asac069. Epub 2022 Dec 21.ABSTRACTAdjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. We derive necessary conditions on the coherence between the exposure and the unmeasured confounder that ensure the effect of exposure is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. One assumption that ensures identifiability is that confounding present at global scales dissipates at ...
Source: Biometrika - March 19, 2024 Category: Biotechnology Authors: Yawen Guan Garritt L Page Brian J Reich Massimo Ventrucci Shu Yang Source Type: research

Spectral adjustment for spatial confounding
Biometrika. 2023 Sep;110(3):699-719. doi: 10.1093/biomet/asac069. Epub 2022 Dec 21.ABSTRACTAdjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. We derive necessary conditions on the coherence between the exposure and the unmeasured confounder that ensure the effect of exposure is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. One assumption that ensures identifiability is that confounding present at global scales dissipates at ...
Source: Biometrika - March 19, 2024 Category: Biotechnology Authors: Yawen Guan Garritt L Page Brian J Reich Massimo Ventrucci Shu Yang Source Type: research

Spectral adjustment for spatial confounding
Biometrika. 2023 Sep;110(3):699-719. doi: 10.1093/biomet/asac069. Epub 2022 Dec 21.ABSTRACTAdjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. We derive necessary conditions on the coherence between the exposure and the unmeasured confounder that ensure the effect of exposure is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. One assumption that ensures identifiability is that confounding present at global scales dissipates at ...
Source: Biometrika - March 19, 2024 Category: Biotechnology Authors: Yawen Guan Garritt L Page Brian J Reich Massimo Ventrucci Shu Yang Source Type: research

Statistical summaries of unlabelled evolutionary trees
Biometrika. 2023 Apr 26;111(1):171-193. doi: 10.1093/biomet/asad025. eCollection 2024 Mar.ABSTRACTRooted and ranked phylogenetic trees are mathematical objects that are useful in modelling hierarchical data and evolutionary relationships with applications to many fields such as evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explores the posterior distribution of trees via Markov chain Monte Carlo methods. However, assessing uncertainty and summarizing distributions remains challenging for these types of structures. While labelled phylogenetic trees have been extensively studied, rela...
Source: Biometrika - February 14, 2024 Category: Biotechnology Authors: Rajanala Samyak Julia A Palacios Source Type: research

Statistical summaries of unlabelled evolutionary trees
Biometrika. 2023 Apr 26;111(1):171-193. doi: 10.1093/biomet/asad025. eCollection 2024 Mar.ABSTRACTRooted and ranked phylogenetic trees are mathematical objects that are useful in modelling hierarchical data and evolutionary relationships with applications to many fields such as evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explores the posterior distribution of trees via Markov chain Monte Carlo methods. However, assessing uncertainty and summarizing distributions remains challenging for these types of structures. While labelled phylogenetic trees have been extensively studied, rela...
Source: Biometrika - February 14, 2024 Category: Biotechnology Authors: Rajanala Samyak Julia A Palacios Source Type: research

Statistical summaries of unlabelled evolutionary trees
Biometrika. 2023 Apr 26;111(1):171-193. doi: 10.1093/biomet/asad025. eCollection 2024 Mar.ABSTRACTRooted and ranked phylogenetic trees are mathematical objects that are useful in modelling hierarchical data and evolutionary relationships with applications to many fields such as evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explores the posterior distribution of trees via Markov chain Monte Carlo methods. However, assessing uncertainty and summarizing distributions remains challenging for these types of structures. While labelled phylogenetic trees have been extensively studied, rela...
Source: Biometrika - February 14, 2024 Category: Biotechnology Authors: Rajanala Samyak Julia A Palacios Source Type: research

Statistical summaries of unlabelled evolutionary trees
Biometrika. 2023 Apr 26;111(1):171-193. doi: 10.1093/biomet/asad025. eCollection 2024 Mar.ABSTRACTRooted and ranked phylogenetic trees are mathematical objects that are useful in modelling hierarchical data and evolutionary relationships with applications to many fields such as evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explores the posterior distribution of trees via Markov chain Monte Carlo methods. However, assessing uncertainty and summarizing distributions remains challenging for these types of structures. While labelled phylogenetic trees have been extensively studied, rela...
Source: Biometrika - February 14, 2024 Category: Biotechnology Authors: Rajanala Samyak Julia A Palacios Source Type: research

Statistical summaries of unlabelled evolutionary trees
Biometrika. 2023 Apr 26;111(1):171-193. doi: 10.1093/biomet/asad025. eCollection 2024 Mar.ABSTRACTRooted and ranked phylogenetic trees are mathematical objects that are useful in modelling hierarchical data and evolutionary relationships with applications to many fields such as evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explores the posterior distribution of trees via Markov chain Monte Carlo methods. However, assessing uncertainty and summarizing distributions remains challenging for these types of structures. While labelled phylogenetic trees have been extensively studied, rela...
Source: Biometrika - February 14, 2024 Category: Biotechnology Authors: Rajanala Samyak Julia A Palacios Source Type: research

Statistical summaries of unlabelled evolutionary trees
Biometrika. 2023 Apr 26;111(1):171-193. doi: 10.1093/biomet/asad025. eCollection 2024 Mar.ABSTRACTRooted and ranked phylogenetic trees are mathematical objects that are useful in modelling hierarchical data and evolutionary relationships with applications to many fields such as evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explores the posterior distribution of trees via Markov chain Monte Carlo methods. However, assessing uncertainty and summarizing distributions remains challenging for these types of structures. While labelled phylogenetic trees have been extensively studied, rela...
Source: Biometrika - February 14, 2024 Category: Biotechnology Authors: Rajanala Samyak Julia A Palacios Source Type: research

Statistical summaries of unlabelled evolutionary trees
Biometrika. 2023 Apr 26;111(1):171-193. doi: 10.1093/biomet/asad025. eCollection 2024 Mar.ABSTRACTRooted and ranked phylogenetic trees are mathematical objects that are useful in modelling hierarchical data and evolutionary relationships with applications to many fields such as evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explores the posterior distribution of trees via Markov chain Monte Carlo methods. However, assessing uncertainty and summarizing distributions remains challenging for these types of structures. While labelled phylogenetic trees have been extensively studied, rela...
Source: Biometrika - February 14, 2024 Category: Biotechnology Authors: Rajanala Samyak Julia A Palacios Source Type: research

Statistical summaries of unlabelled evolutionary trees
Biometrika. 2023 Apr 26;111(1):171-193. doi: 10.1093/biomet/asad025. eCollection 2024 Mar.ABSTRACTRooted and ranked phylogenetic trees are mathematical objects that are useful in modelling hierarchical data and evolutionary relationships with applications to many fields such as evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explores the posterior distribution of trees via Markov chain Monte Carlo methods. However, assessing uncertainty and summarizing distributions remains challenging for these types of structures. While labelled phylogenetic trees have been extensively studied, rela...
Source: Biometrika - February 14, 2024 Category: Biotechnology Authors: Rajanala Samyak Julia A Palacios Source Type: research