A Multilevel Nonlinearity Study
نویسندگان
چکیده
| Multilevel models are designed to deal with studies on data that contain hierarchical structures and are becoming increasingly important in many elds of research. Since they are limited to parametric models, in practice only linear multilevel models are used. We present a nonlinear multilevel approach to investigate nonlinearity in relations. This model is based on nonlinear feed-forward networks. Furthermore, the proposed multilevel model enables us to study how errors in measurements may obscure nonlinear relations. An imaginary dataset was generated as an example , based on an epidemiological model, and with this dataset the eeect of noise on nonlinear relations was studied, using the proposed multilevel model. This simulation con-rms the applicability of the multilevel nonlinearity study and indicates strong obscuring of nonlinearity due to noise.
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