Modelling IVF data using an extended continuation ratio random effects model

Ruth Penman; Gillian Heller; John Tyler

Modelling IVF data using an extended continuation ratio random effects model

Ruth Penman, Gillian Heller, John Tyler

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

Abstract

In Vitro Fertilization (IVF) offers infertile couples the opportunity to have a baby. Many of these couples have multiple attempts to try to achieve this goal. To model the risk factors that affect the process at any of its stages, across the multiple attempts, an ordinal response and an extended continuation ratio random effects model have been used. This enabled the modelling of differential effects of covariates on different stages of the process. A significant random effect suggests that there is a couple specific effect, which may be interpreted as a fertility index.

Original language	English
Title of host publication	Proceedings of the 22nd International Workshop on Statistical Modelling
Editors	Joan del Castillo, Anna Espinal, Pere Puig
Place of Publication	Barcelona, Spain
Publisher	L'Institut d'Estadistica de Catalunya, IDESCAT
Pages	485-489
Number of pages	5
ISBN (Print)	9788469059432
Publication status	Published - 2007
Event	International Workshop on Statistical Modelling (22nd : 2007) - Barcelona, Spain Duration: 2 Jul 2007 → 6 Jul 2007

Workshop

Workshop	International Workshop on Statistical Modelling (22nd : 2007)
City	Barcelona, Spain
Period	2/07/07 → 6/07/07

Keywords

IVF
extended continuation ratio model
random effects model

Cite this

@inproceedings{04365d49b6e040e3a449c31a8db7a2a7,

title = "Modelling IVF data using an extended continuation ratio random effects model",

abstract = "In Vitro Fertilization (IVF) offers infertile couples the opportunity to have a baby. Many of these couples have multiple attempts to try to achieve this goal. To model the risk factors that affect the process at any of its stages, across the multiple attempts, an ordinal response and an extended continuation ratio random effects model have been used. This enabled the modelling of differential effects of covariates on different stages of the process. A significant random effect suggests that there is a couple specific effect, which may be interpreted as a fertility index.",

keywords = "IVF, extended continuation ratio model, random effects model",

author = "Ruth Penman and Gillian Heller and John Tyler",

year = "2007",

language = "English",

isbn = "9788469059432",

pages = "485--489",

editor = "Castillo, {Joan del} and Anna Espinal and Pere Puig",

booktitle = "Proceedings of the 22nd International Workshop on Statistical Modelling",

publisher = "L'Institut d'Estadistica de Catalunya, IDESCAT",

note = "International Workshop on Statistical Modelling (22nd : 2007) ; Conference date: 02-07-2007 Through 06-07-2007",

}

Penman, R, Heller, G & Tyler, J 2007, Modelling IVF data using an extended continuation ratio random effects model. in JD Castillo, A Espinal & P Puig (eds), Proceedings of the 22nd International Workshop on Statistical Modelling. L'Institut d'Estadistica de Catalunya, IDESCAT, Barcelona, Spain, pp. 485-489, International Workshop on Statistical Modelling (22nd : 2007), Barcelona, Spain, 2/07/07.

Modelling IVF data using an extended continuation ratio random effects model. / Penman, Ruth; Heller, Gillian; Tyler, John.
Proceedings of the 22nd International Workshop on Statistical Modelling. ed. / Joan del Castillo; Anna Espinal; Pere Puig. Barcelona, Spain: L'Institut d'Estadistica de Catalunya, IDESCAT, 2007. p. 485-489.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Modelling IVF data using an extended continuation ratio random effects model

AU - Penman, Ruth

AU - Heller, Gillian

AU - Tyler, John

PY - 2007

Y1 - 2007

N2 - In Vitro Fertilization (IVF) offers infertile couples the opportunity to have a baby. Many of these couples have multiple attempts to try to achieve this goal. To model the risk factors that affect the process at any of its stages, across the multiple attempts, an ordinal response and an extended continuation ratio random effects model have been used. This enabled the modelling of differential effects of covariates on different stages of the process. A significant random effect suggests that there is a couple specific effect, which may be interpreted as a fertility index.

AB - In Vitro Fertilization (IVF) offers infertile couples the opportunity to have a baby. Many of these couples have multiple attempts to try to achieve this goal. To model the risk factors that affect the process at any of its stages, across the multiple attempts, an ordinal response and an extended continuation ratio random effects model have been used. This enabled the modelling of differential effects of covariates on different stages of the process. A significant random effect suggests that there is a couple specific effect, which may be interpreted as a fertility index.

KW - IVF

KW - extended continuation ratio model

KW - random effects model

M3 - Conference proceeding contribution

SN - 9788469059432

SP - 485

EP - 489

BT - Proceedings of the 22nd International Workshop on Statistical Modelling

A2 - Castillo, Joan del

A2 - Espinal, Anna

A2 - Puig, Pere

PB - L'Institut d'Estadistica de Catalunya, IDESCAT

CY - Barcelona, Spain

T2 - International Workshop on Statistical Modelling (22nd : 2007)

Y2 - 2 July 2007 through 6 July 2007

ER -

Modelling IVF data using an extended continuation ratio random effects model

Abstract

Workshop

Keywords

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