An autoregressive linear mixed effects model for the analysis of longitudinal data which show profiles approaching asymptotes.
In longitudinal data, a continuous response sometimes shows a profile approaching an asymptote. For such data, we propose a new class of models, autoregressive linear mixed effects models in which the current response is regressed on the previous response, fixed effects, and random effects. Asymptotes can shift depending on treatment groups, individuals, and so on, and can be modelled by fixed and random effects. We also propose error structures that are useful in practice. The estimation methods of linear mixed effects models can be used as long as there is no intermittent missing.
Funatogawa
Ikuko
I
Department of Hygiene and Public Health, Teikyo University of Medicine, Tokyo, Japan. ifunatogawa-tky@umin.ac.jp
Funatogawa
Takashi
T
Ohashi
Yasuo
Y
D001379:Azathioprine / Q000627:therapeutic use; D002117:Calcitriol / Q000031:analogs & derivatives / Q000627:therapeutic use; D003198:Computer Simulation; D004359:Drug Therapy, Combination; D006801:Humans; D006961:Hyperparathyroidism / Q000188:drug therapy; D007166:Immunosuppressive Agents / Q000627:therapeutic use; D016014:Linear Models; D008137:Longitudinal Studies; D008775:Methylprednisolone / Q000627:therapeutic use; D009103:Multiple Sclerosis / Q000276:immunology / Q000628:therapy; D010281:Parathyroid Hormone / Q000097:blood; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D011961:Receptors, Fc / Q000097:blood
D007166:Immunosuppressive Agents; D010281:Parathyroid Hormone; D011961:Receptors, Fc; D002117:Calcitriol; D001379:Azathioprine; C051883:maxacalcitol; D008775:Methylprednisolone