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20182023
most citedMulti-Parameter Regression Survival Modelling: An Alternative to Proportional Hazards

24 citations · 91 across the 16 of their papers we have counts for

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Showing 2019Show all

10 papers · 1 filter

physics.soc-ph2019

Agreement Threshold on Axelrod's model of Cultural Dissemination

Pádraig Mac Carron, Paul J. Maher, Susan Fennell +4

Shared opinions are an important feature in the formation of social groups. In this paper, we use the Axelrod model of cultural dissemination to represent opinion-based groups. In…

stat.AP2019

A modelling methodology for social interaction experiments

Susan C. Fennell, James P. Gleeson, Michael Quayle +2

Analysis of temporal network data arising from online interactive social experiments is not possible with standard statistical methods because the assumptions of these models, such…

stat.AP2019

An Alternative Formulation of Coxian Phase-type Distributions with Covariates: Application to Emergency Department Length of Stay

Jean Rizk, Kevin Burke, Cathal Walsh

In this paper we present a new methodology to model patient transitions and length of stay in the emergency department using a series of conditional Coxian phase-type distributions…

stat.ME2019

Penalized Variable Selection in Multi-Parameter Regression Survival Modelling

Fatima-Zahra Jaouimaa, Il Do Ha, Kevin Burke

Multi-parameter regression (MPR) modelling refers to the approach whereby covariates are allowed to enter the model through multiple distributional parameters simultaneously. This…

stat.ME2019

A Multi-parameter regression model for interval censored survival data

Defen Peng, Gilbert MacKenzie, Kevin Burke

We develop flexible multi-parameter regression survival models for interval censored survival data arising in longitudinal prospective studies and longitudinal randomised controlle…

stat.ME2019★ 1 cited

Semiparametric multi-parameter regression survival modelling

Kevin Burke, Frank Eriksson, C. B. Pipper

We consider a log-linear model for survival data, where both the location and scale parameters depend on covariates and the baseline hazard function is completely unspecified. This…

stat.ME2019★ 24 cited

Multi-Parameter Regression Survival Modelling: An Alternative to Proportional Hazards

Kevin Burke, Gilbert MacKenzie

It is standard practice for covariates to enter a parametric model through a single distributional parameter of interest, for example, the scale parameter in many standard survival…

stat.ME2019

A Flexible Parametric Modelling Framework for Survival Analysis

Kevin Burke, M. C. Jones, Angela Noufaily

We introduce a general, flexible, parametric survival modelling framework which encompasses key shapes of hazard function (constant, increasing, decreasing, up-then-down, down-then…

stat.ME2019

A Bivariate Power Generalized Weibull Distribution: a Flexible Parametric Model for Survival Analysis

M. C. Jones, Angela Noufaily, Kevin Burke

We are concerned with the flexible parametric analysis of bivariate survival data. Elsewhere, we have extolled the virtues of the "power generalized Weibull" (PGW) distribution as…

math.ST2019★ 1 cited

On the Non-uniqueness of Representations of Coxian Phase-Type Distributions

Jean Rizk, Kevin Burke, Cathal Walsh

Parameter estimation in Coxian phase-type models can be challenging due to their non-unique representation leading to a multi-modal likelihood. Since each representation correspond…