Page 25 - Contributed Paper Session (CPS) - Volume 4

CPS2106 Julio M. Singer et al.
Figure 2: Predicted subject specific response curves (MSC males)
Week

Acknowledgements
This research received partial financial support from Conselho Nacional de
Desenvolvimento Cient´ıfico e Tecnol´ogico (CNPq, grant 3304126/2015-2)
and Fundac¸˜ao de Amparo `a Pesquisa do Estado de S˜ao Paulo (FAPESP,
grant 2013/21728-2), Brazil.

References
1. Coatti, G.C. (2015). Avalia¸c˜ao do potencial terapˆeutico de pericitos e
de c´elulas mesenquimais no camundongo SOD1, modelo animal para
esclerose lateral amiotr´ofica. Tese de doutorado, Departamento de
Biocˆencias, Universidade de S˜ao Paulo.
http://www.teses.usp.br/teses/disponiveis/41/41131/tde-14012016-
143346/pt-br.php
2. Fasola, S., Muggeo, V.M.R. and Ku¨chenhoff, H. (2018). A heuristic,
iterative algorithm for change-point detection in abrupt change models.
Compuational Statistics 33, 997-1015.
3. Muggeo, V.M.R., Atkins, D.C., Gallop, R.J. and Dimidjian, S. (2014).
Segmented mixed models with random changepoints: a maximum
likelihood approach with application to treatment for depression study.
Statistical Modelling 14, 293-313.
4. Singer, J.M., Rocha, F.M.M. and Nobre, J.S. (2017). Graphical tools for
detecting departures from linear mixed models assumptions and some
remedial measures. International Statistical Review 85, 290-324.

14 | I S I W S C 2 0 1 9