Fitting four-parameter logistic model using mixed-effects modeling approach

Four-parameter logistic model is used to describe height-diameter relationship of dahurian larch (Larix gmelinii. Rupr.) from longitudinal measurements using nonlinear mixed-effects modeling approach. The parameter variation in the model was divided into random effects, fixed effects, and variance-covariance structure. The values for fixed effects parameters and the variance-covariance matrix of random effects were estimated using NLME function. Autocorrelation structure was considered for explaining the dependency among multiple measurements within the each individual. Information criterion statistics (AIC, BIC and Likelihood ratio test) are used for comparing different structures of the random effects components. These methods are illustrated using the nonlinear mixed-effects methods in S-Plus software.