Abstract:

Nonlinear mixed effects model(NLMEM) is based on the relationship between the fixed and random effects in the regression function. The NLMEM has a competitive advantage in analyzing repeated measures data, the longitudinal data and multilevel data. This paper chose two kinds of two-level nonlinear mixed model to analyze basal area growth for Chinese Fir(Cunninghamia lanceolata). Model 1 is a general two-level NLMEM and model 2 is based on model 1 to further consider the fixed effects parameters changes with a specific factor. Firstly, through the analysis of these two models, this paper defined the basic model to build the two-level NLMEM. Secondly, 665 kinds of models derived from model 1 and 2 703 kinds of models derived from model 2 were calculated and compared. The results showed that: for model 1,there were 57 kinds of models converging, and when the formal parameter b₀considered the block effects and plot effects,b₁and b₄only considered the block effects, the model fitted the best. For model 2, there were 24 kinds of model converging,and when the formal parameter b₅considered the block effects and plot effects, b₁ only considered block effects and the fixed effects b₀changed with any level of block level, the model 2 fitted the best. Finally, by comparing the traditional nonlinear regression model, model 1 and model 2, the results showed that model 1 and model 2 fitted better than the traditional nonlinear regression, and model 2 was best fitting model.

Key words: nonlinear mixed effects model(NLMEM), two-level nonlinear mixed effects model, basal area for Chinese Fir, the best fitting model