In this paper we investigate properties of the power function of the generalized least squaresF ted for linear hypotheses under regression models with two-way error component model. Thecovariance structure of the mode...In this paper we investigate properties of the power function of the generalized least squaresF ted for linear hypotheses under regression models with two-way error component model. Thecovariance structure of the model depends on the correlation coefficients ρ1 and ρ2 correspondingto the random effects. This model has been frequently applied to the analysis of panel data.In general, we show that the power is a monotonically increasing function of ρ1 (ρ2) in a regionwhich is ciO6e to the ρ1 (ρ2) axis, and a monotonically decreasing function of ρ1 (ρ2) in a regionclose to the ρ2 (ρ1) axis.展开更多
文摘In this paper we investigate properties of the power function of the generalized least squaresF ted for linear hypotheses under regression models with two-way error component model. Thecovariance structure of the model depends on the correlation coefficients ρ1 and ρ2 correspondingto the random effects. This model has been frequently applied to the analysis of panel data.In general, we show that the power is a monotonically increasing function of ρ1 (ρ2) in a regionwhich is ciO6e to the ρ1 (ρ2) axis, and a monotonically decreasing function of ρ1 (ρ2) in a regionclose to the ρ2 (ρ1) axis.
