LONGITUDINAL RASCH MODEL FOR SELF ASSESSMENT OF SIDE EFFECTS IN CHEMOTHERAPY CYCLES

Laura Pagani; Maria Chiara Zanarotti

doi:10.1285/i20705948v5n3p387

LONGITUDINAL RASCH MODEL FOR SELF ASSESSMENT OF SIDE EFFECTS IN CHEMOTHERAPY CYCLES

Laura Pagani
, Maria Chiara Zanarotti

University of Udine

Risultato della ricerca: Contributo in rivista › Articolo › peer review

Abstract

In this paper longitudinal responses data are considered and it is showed how to benefit of the use of multilevel setting to model data structure. In fact, both longitudinal and item responses data can be ascribed to hierarchical generalized linear model, so that the whole data complexity is effectively modeled in a 3-level multilevel structure. An application to chemotherapy side effects is showed.

Lingua originale	Inglese
pagine (da-a)	387-392
Numero di pagine	6
Rivista	Electronic Journal of Applied Statistical Analysis
Volume	5
DOI	https://doi.org/10.1285/i20705948v5n3p387
Stato di pubblicazione	Pubblicato - 2012

Keywords

Longitudinal data
chemotherapy side effects.
hierarchical generalized linear model
multilevel rasch model

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10.1285/i20705948v5n3p387

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abstract = "In this paper longitudinal responses data are considered and it is showed how to benefit of the use of multilevel setting to model data structure. In fact, both longitudinal and item responses data can be ascribed to hierarchical generalized linear model, so that the whole data complexity is effectively modeled in a 3-level multilevel structure. An application to chemotherapy side effects is showed.",

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N2 - In this paper longitudinal responses data are considered and it is showed how to benefit of the use of multilevel setting to model data structure. In fact, both longitudinal and item responses data can be ascribed to hierarchical generalized linear model, so that the whole data complexity is effectively modeled in a 3-level multilevel structure. An application to chemotherapy side effects is showed.

AB - In this paper longitudinal responses data are considered and it is showed how to benefit of the use of multilevel setting to model data structure. In fact, both longitudinal and item responses data can be ascribed to hierarchical generalized linear model, so that the whole data complexity is effectively modeled in a 3-level multilevel structure. An application to chemotherapy side effects is showed.

KW - Longitudinal data

KW - chemotherapy side effects.

KW - hierarchical generalized linear model

KW - multilevel rasch model

KW - Longitudinal data

KW - chemotherapy side effects.

KW - hierarchical generalized linear model

KW - multilevel rasch model

UR - http://hdl.handle.net/10807/37513

UR - http://siba-ese.unisalento.it/index.php/ejasa/article/view/12252/11130

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JO - Electronic Journal of Applied Statistical Analysis

JF - Electronic Journal of Applied Statistical Analysis

ER -

LONGITUDINAL RASCH MODEL FOR SELF ASSESSMENT OF SIDE EFFECTS IN CHEMOTHERAPY CYCLES

Abstract

Keywords

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