A generalized partially linear mean-covariance regression model for longitudinal proportional data, with applications to the analysis of quality of life data from cancer clinical trials.

摘要: Motivated by the analysis of quality life data from a clinical trial on early breast cancer, we propose in this paper generalized partially linear mean-covariance regression model for longitudinal proportional data, which are bounded closed interval. Cholesky decomposition covariance matrix within-subject responses and estimation equations used to estimate unknown parameters nonlinear function model. Simulation studies performed evaluate performance proposed procedures. Our new is also applied analyze cancer that motivated research. In comparison with available models literature, does not require specific parametric assumptions density probability boundary values can capture dynamic changes time or other interested variables both mean correlated responses. Copyright © 2017 John Wiley & Sons, Ltd.