Considering the sample sizes as truncated Poisson random variables in mixed effects models

Célia Nunes; Elsa Moreira; Sandra S. Ferreira; Dário Ferreira; João T. Mexia

doi:10.1080/02664763.2019.1641188

Considering the sample sizes as truncated Poisson random variables in mixed effects models

Célia Nunes, Elsa Moreira, Sandra S. Ferreira, Dário Ferreira, João T. Mexia

CMA - Centro de Matemática e Aplicações

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

When applying analysis of variance, the sample sizes may not be previously known, so it is more appropriate to consider them as realizations of random variables. A motivating example is the collection of observations during a fixed time span in a study comparing, for example, several pathologies of patients arriving at a hospital. This paper extends the theory of analysis of variance to those situations considering mixed effects models. We will assume that the occurrences of observations correspond to a counting process and the sample dimensions have Poisson distribution. The proposed approach is applied to a study of cancer patients.

Original language	English
Journal	Journal of Applied Statistics
Volume	47
Early online date	Jul 2019
DOIs	https://doi.org/10.1080/02664763.2019.1641188
Publication status	Published - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

cancer registries
counting processes
F-tests
L extensions models
mixed effects
Random sample sizes

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10.1080/02664763.2019.1641188

Cite this

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title = "Considering the sample sizes as truncated Poisson random variables in mixed effects models",

abstract = "When applying analysis of variance, the sample sizes may not be previously known, so it is more appropriate to consider them as realizations of random variables. A motivating example is the collection of observations during a fixed time span in a study comparing, for example, several pathologies of patients arriving at a hospital. This paper extends the theory of analysis of variance to those situations considering mixed effects models. We will assume that the occurrences of observations correspond to a counting process and the sample dimensions have Poisson distribution. The proposed approach is applied to a study of cancer patients.",

keywords = "cancer registries, counting processes, F-tests, L extensions models, mixed effects, Random sample sizes",

author = "C{\'e}lia Nunes and Elsa Moreira and Ferreira, \{Sandra S.\} and D{\'a}rio Ferreira and Mexia, \{Jo{\~a}o T.\}",

note = "UID/MAT/00212/2019. UID/MAT/00297/2019. Sem PDF conforme despacho.",

year = "2020",

doi = "10.1080/02664763.2019.1641188",

language = "English",

volume = "47",

journal = "Journal of Applied Statistics",

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TY - JOUR

T1 - Considering the sample sizes as truncated Poisson random variables in mixed effects models

AU - Nunes, Célia

AU - Moreira, Elsa

AU - Ferreira, Sandra S.

AU - Ferreira, Dário

AU - Mexia, João T.

N1 - UID/MAT/00212/2019. UID/MAT/00297/2019. Sem PDF conforme despacho.

PY - 2020

Y1 - 2020

N2 - When applying analysis of variance, the sample sizes may not be previously known, so it is more appropriate to consider them as realizations of random variables. A motivating example is the collection of observations during a fixed time span in a study comparing, for example, several pathologies of patients arriving at a hospital. This paper extends the theory of analysis of variance to those situations considering mixed effects models. We will assume that the occurrences of observations correspond to a counting process and the sample dimensions have Poisson distribution. The proposed approach is applied to a study of cancer patients.

AB - When applying analysis of variance, the sample sizes may not be previously known, so it is more appropriate to consider them as realizations of random variables. A motivating example is the collection of observations during a fixed time span in a study comparing, for example, several pathologies of patients arriving at a hospital. This paper extends the theory of analysis of variance to those situations considering mixed effects models. We will assume that the occurrences of observations correspond to a counting process and the sample dimensions have Poisson distribution. The proposed approach is applied to a study of cancer patients.

KW - cancer registries

KW - counting processes

KW - F-tests

KW - L extensions models

KW - mixed effects

KW - Random sample sizes

UR - https://www.scopus.com/pages/publications/85069046326

U2 - 10.1080/02664763.2019.1641188

DO - 10.1080/02664763.2019.1641188

M3 - Article

AN - SCOPUS:85069046326

SN - 0266-4763

VL - 47

JO - Journal of Applied Statistics

JF - Journal of Applied Statistics

ER -

Considering the sample sizes as truncated Poisson random variables in mixed effects models

Abstract

UN SDGs

Keywords

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