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316546

Two-Way Cross Classification with Multiple Covariates and One Observation Per Cell

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Last updated: 05 Jan 2025

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Abstract

The two-way cross classification model with multiple covariate and one observation per cell is considered. The model is given by yᵢⱼ = μ + τᵢ + βⱼ + ∑(r=1)ᵏ δᵢᵣ Xⱼᵣ + λαᵢ Yⱼ + εᵢⱼ, the εᵢⱼ are independent and εᵢⱼ is N(0, σ2). Maximum likelihood estimators are developed for all parameters including σ2 when λ ≠ 0. The likelihood ratio test is obtained for the hypothesis: no interaction (λ = 0).

DOI

10.21608/esju.1989.316546

Keywords

Likelihood ratio test, Maximum likelihood estimators, Multiple Covariates, Two-Way Cross Classification Model

Authors

First Name

Seham

Last Name

Mira

MiddleName

I.

Affiliation

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City

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Orcid

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Volume

33

Article Issue

2

Related Issue

43395

Issue Date

1989-12-01

Receive Date

2023-09-07

Publish Date

1989-12-01

Page Start

261

Page End

279

Print ISSN

0542-1748

Online ISSN

2786-0086

Link

https://esju.journals.ekb.eg/article_316546.html

Detail API

https://esju.journals.ekb.eg/service?article_code=316546

Order

7

Type

Original Article

Type Code

1,914

Publication Type

Journal

Publication Title

The Egyptian Statistical Journal

Publication Link

https://esju.journals.ekb.eg/

MainTitle

Two-Way Cross Classification with Multiple Covariates and One Observation Per Cell

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Article

Created At

28 Dec 2024