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非线性多层模型及其离散响应数据应用
A procedure is proposed for the analysis of multilevel nonlinear models using a linearization. The case of log linear models for discrete response data is studied in detail.
受限无偏迭代广义最小二乘估计
It is shown that the iterative least-squares procedure for estimating the parameters in a general multilevel random coefficients linear model can be modified to produce unbiased estimates of the random parameters. In the multivariate normal case these are equivalent to restricted maximum likelihood estimates.
It is shown that the iterative least-squares procedure for estimating the parameters in a general multilevel random coefficients linear model can be modified to produce unbiased estimates of the random parameters. In the multivariate normal case these are equivalent to restricted maximum likelihood estimates.