Identification of multivariate responders and non-responders by using Bayesian growth curve latent class models

Responders and non-responders to probiotic interventions

"Responders and non-responders to probiotic interventions" (2010).

Studying Multivariate Change Using Multilevel Models and Latent Curve Models.

In longitudinal research investigators often measure multiple variables at multiple points in time and are interested in investigating individual differences in patterns of change on those variables. In the vast majority of applications, researchers focus on studying change in one variable at a time. In this article we consider methods for studying relations1.1ips between patterns of change on ...

Immunoglobulin treatment in post-polio syndrome: Identification of responders and non-responders.

OBJECTIVE To define and characterize responders and non-responders in a group of 124 patients with post-polio syndrome who received a single treatment with intravenous immunoglobulin. DESIGN Open trial, prospective follow-up study. METHODS Clinical examination and data from medical records. Short Form 36 (SF-36), Physical Activity Scale for the Elderly (PASE) and visual analogue scale (VAS)...

The Influence of Clinical and Biological Factors on Transfusion-Associated Non-ABO Antigen Alloimmunization: Responders, Hyper-Responders, and Non-Responders.

In the context of transfusion medicine, alloimmunization most often refers to the development of antibodies to non-ABO red blood cell (RBC) antigens following pregnancy, transfusion, or transplantation. The development of RBC alloantibodies can have important clinical consequences, particularly in patients who require chronic transfusions. It has been suggested that alloimmunization is more com...

Latent Growth Curve Models