Correlated inverse Gaussian frailty models for bivariate survival data
DD Hanagal, A Pandey - Communications in Statistics-Theory and …, 2020 - Taylor & Francis
Frailty models are used in the survival analysis to account for the unobserved heterogeneity
in individual risks to disease and death. To analyze the bivariate data on related survival …
in individual risks to disease and death. To analyze the bivariate data on related survival …
Shared inverse Gaussian frailty models based on additive hazards
DD Hanagal, A Pandey - Communications in Statistics-Theory and …, 2017 - Taylor & Francis
Frailty models are used in the survival analysis to account for the unobserved heterogeneity
in individual risks to disease and death. To analyze the bivariate data on related survival …
in individual risks to disease and death. To analyze the bivariate data on related survival …
Correlated positive stable frailty models
DD Hanagal - Communications in Statistics-Theory and Methods, 2021 - Taylor & Francis
Frailty models are used in the survival analysis to account for the unobserved heterogeneity
in individual risks to disease and death. To analyze the bivariate data on related survival …
in individual risks to disease and death. To analyze the bivariate data on related survival …
Correlated gamma frailty models for bivariate survival data
Frailty models are used in the survival analysis to account for the unobserved heterogeneity
in individual risks to disease and death. To analyze the bivariate data on related survival …
in individual risks to disease and death. To analyze the bivariate data on related survival …
Modeling of inverse Gaussian frailty model for bivariate survival data
DD Hanagal, AD Dabade - Communications in Statistics-Theory …, 2013 - Taylor & Francis
Shared frailty models are often used to model heterogeneity in survival analysis. The most
common shared frailty model is a model in which hazard function is a product of random …
common shared frailty model is a model in which hazard function is a product of random …
Compound Poisson shared frailty models based on additive hazards
DD Hanagal - Communications in Statistics-Theory and Methods, 2023 - Taylor & Francis
Frailty models are used in the survival analysis to account for the unobserved heterogeneity
in individual risks to disease and death. To analyze the bivariate data on related survival …
in individual risks to disease and death. To analyze the bivariate data on related survival …
Modeling bivariate survival data using shared inverse Gaussian frailty model
DD Hanagal, SM Bhambure - Communications in Statistics-Theory …, 2016 - Taylor & Francis
The shared frailty models are often used to model heterogeneity in survival analysis. The
most common shared frailty model is a model in which hazard function is a product of a …
most common shared frailty model is a model in which hazard function is a product of a …
Shared gamma frailty models based on additive hazards
DD Hanagal, A Pandey - Journal of the Indian Society for Probability and …, 2016 - Springer
Frailty models are used in the survival analysis to account for the unobserved heterogeneity
in individual risks to disease and death. To analyze the bivariate data on related survival …
in individual risks to disease and death. To analyze the bivariate data on related survival …
Analysis of kidney infection data using correlated compound poisson frailty models
DD Hanagal - Model Assisted Statistics and Applications, 2024 - content.iospress.com
Shared frailty models are used despite their limitations. To overcome their disadvantages
correlated frailty models may be used. In this paper, we introduce the correlated compound …
correlated frailty models may be used. In this paper, we introduce the correlated compound …
[PDF][PDF] Correlated inverse Gaussian frailty models based on reversed hazard rate
DD Hanagal - Statistics and Applications, 2022 - ssca.org.in
Frailty models are used in the survival analysis to account for the unobserved heterogeneity
in individual risks to disease and death. To analyze the bivariate data on related survival …
in individual risks to disease and death. To analyze the bivariate data on related survival …