Proust-Lima C - Search Results

1

Guidelines for reporting methodological challenges and evaluating potential bias in dementia research.

Weuve J, Proust-Lima C, Power MC, Gross AL, Hofer SM, Thiébaut R, Chêne G, Glymour MM, Dufouil C; MELODEM Initiative. Weuve J, et al. Alzheimers Dement. 2015 Sep;11(9):1098-109. doi: 10.1016/j.jalz.2015.06.1885. Alzheimers Dement. 2015. PMID: 26397878 Free PMC article. Review.

2

Disease Progression in Multiple System Atrophy: The Value of Clinical Cohorts with Long Follow-Up.

Saulnier T, Fabbri M, Pavy-Le Traon A, Le Goff M, Helmer C, Péran P, Meissner WG, Rascol O, Foubert-Samier A, Proust-Lima C. Saulnier T, et al. Mov Disord. 2023 Aug;38(8):1567-1569. doi: 10.1002/mds.29534. Mov Disord. 2023. PMID: 37565400 No abstract available.

3

A nonlinear latent class model for joint analysis of multivariate longitudinal data and a binary outcome.

Proust-Lima C, Letenneur L, Jacqmin-Gadda H. Proust-Lima C, et al. Stat Med. 2007 May 10;26(10):2229-45. doi: 10.1002/sim.2659. Stat Med. 2007. PMID: 16900568

4

Sensitivity of four psychometric tests to measure cognitive changes in brain aging-population-based studies.

Proust-Lima C, Amieva H, Dartigues JF, Jacqmin-Gadda H. Proust-Lima C, et al. Am J Epidemiol. 2007 Feb 1;165(3):344-50. doi: 10.1093/aje/kwk017. Epub 2006 Nov 14. Am J Epidemiol. 2007. PMID: 17105962 Free PMC article.

5

Gender and education impact on brain aging: a general cognitive factor approach.

Proust-Lima C, Amieva H, Letenneur L, Orgogozo JM, Jacqmin-Gadda H, Dartigues JF. Proust-Lima C, et al. Psychol Aging. 2008 Sep;23(3):608-620. doi: 10.1037/a0012838. Psychol Aging. 2008. PMID: 18808250

6

Score test for conditional independence between longitudinal outcome and time to event given the classes in the joint latent class model.

Jacqmin-Gadda H, Proust-Lima C, Taylor JM, Commenges D. Jacqmin-Gadda H, et al. Biometrics. 2010 Mar;66(1):11-9. doi: 10.1111/j.1541-0420.2009.01234.x. Epub 2009 May 7. Biometrics. 2010. PMID: 19432771 Free article.

7

Semi-parametric latent process model for longitudinal ordinal data: Application to cognitive decline.

Jacqmin-Gadda H, Proust-Lima C, Amiéva H. Jacqmin-Gadda H, et al. Stat Med. 2010 Nov 20;29(26):2723-31. doi: 10.1002/sim.4035. Stat Med. 2010. PMID: 20809483

8

Misuse of the linear mixed model when evaluating risk factors of cognitive decline.

Proust-Lima C, Dartigues JF, Jacqmin-Gadda H. Proust-Lima C, et al. Am J Epidemiol. 2011 Nov 1;174(9):1077-88. doi: 10.1093/aje/kwr243. Epub 2011 Sep 30. Am J Epidemiol. 2011. PMID: 21965187 Free PMC article.

9

Pattern mixture models and latent class models for the analysis of multivariate longitudinal data with informative dropouts.

Dantan E, Proust-Lima C, Letenneur L, Jacqmin-Gadda H. Dantan E, et al. Int J Biostat. 2008;4(1):Article 14. doi: 10.2202/1557-4679.1088. Int J Biostat. 2008. PMID: 22462120 Free article.

10

Joint latent class models for longitudinal and time-to-event data: a review.

Proust-Lima C, Séne M, Taylor JM, Jacqmin-Gadda H. Proust-Lima C, et al. Stat Methods Med Res. 2014 Feb;23(1):74-90. doi: 10.1177/0962280212445839. Epub 2012 Apr 19. Stat Methods Med Res. 2014. PMID: 22517270 Free PMC article. Review.

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