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).
Mira, S. (1989). Two-Way Cross Classification with Multiple Covariates and One Observation Per Cell. The Egyptian Statistical Journal, 33(2), 261-279. doi: 10.21608/esju.1989.316546
MLA
Seham I. Mira. "Two-Way Cross Classification with Multiple Covariates and One Observation Per Cell", The Egyptian Statistical Journal, 33, 2, 1989, 261-279. doi: 10.21608/esju.1989.316546
HARVARD
Mira, S. (1989). 'Two-Way Cross Classification with Multiple Covariates and One Observation Per Cell', The Egyptian Statistical Journal, 33(2), pp. 261-279. doi: 10.21608/esju.1989.316546
VANCOUVER
Mira, S. Two-Way Cross Classification with Multiple Covariates and One Observation Per Cell. The Egyptian Statistical Journal, 1989; 33(2): 261-279. doi: 10.21608/esju.1989.316546
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