Blanchin M - Search Results

1

Power and sample size determination for the group comparison of patient-reported outcomes with Rasch family models.

Blanchin M, Hardouin JB, Guillemin F, Falissard B, Sébille V. Blanchin M, et al. PLoS One. 2013;8(2):e57279. doi: 10.1371/journal.pone.0057279. Epub 2013 Feb 28. PLoS One. 2013. PMID: 23468955 Free PMC article.

2

Comparison of CTT and Rasch-based approaches for the analysis of longitudinal Patient Reported Outcomes.

Blanchin M, Hardouin JB, Le Neel T, Kubis G, Blanchard C, Mirallié E, Sébille V. Blanchin M, et al. Stat Med. 2011 Apr 15;30(8):825-38. doi: 10.1002/sim.4153. Epub 2010 Dec 28. Stat Med. 2011. PMID: 21432877 Free article.

3

Rasch-family models are more valuable than score-based approaches for analysing longitudinal patient-reported outcomes with missing data.

de Bock É, Hardouin JB, Blanchin M, Le Neel T, Kubis G, Bonnaud-Antignac A, Dantan É, Sébille V. de Bock É, et al. Among authors: blanchin m. Stat Methods Med Res. 2016 Oct;25(5):2067-2087. doi: 10.1177/0962280213515570. Epub 2013 Dec 16. Stat Methods Med Res. 2016. PMID: 24346165

4

Power and sample size determination in the Rasch model: evaluation of the robustness of a numerical method to non-normality of the latent trait.

Guilleux A, Blanchin M, Hardouin JB, Sébille V. Guilleux A, et al. Among authors: blanchin m. PLoS One. 2014 Jan 10;9(1):e83652. doi: 10.1371/journal.pone.0083652. eCollection 2014. PLoS One. 2014. PMID: 24427276 Free PMC article.

5

The minimal clinically important difference determined using item response theory models: an attempt to solve the issue of the association with baseline score.

Rouquette A, Blanchin M, Sébille V, Guillemin F, Côté SM, Falissard B, Hardouin JB. Rouquette A, et al. Among authors: blanchin m. J Clin Epidemiol. 2014 Apr;67(4):433-40. doi: 10.1016/j.jclinepi.2013.10.009. Epub 2014 Jan 18. J Clin Epidemiol. 2014. PMID: 24447591 Free article.

6

Assessment of score- and Rasch-based methods for group comparison of longitudinal patient-reported outcomes with intermittent missing data (informative and non-informative).

de Bock É, Hardouin JB, Blanchin M, Le Neel T, Kubis G, Sébille V. de Bock É, et al. Among authors: blanchin m. Qual Life Res. 2015 Jan;24(1):19-29. doi: 10.1007/s11136-014-0648-1. Epub 2014 Feb 23. Qual Life Res. 2015. PMID: 24563110

7

Power analysis on the time effect for the longitudinal Rasch model.

Feddag ML, Blanchin M, Hardouin JB, Sebille V. Feddag ML, et al. Among authors: blanchin m. J Appl Meas. 2014;15(3):292-301. J Appl Meas. 2014. PMID: 24992252 Free article.

8

A simple ratio-based approach for power and sample size determination for 2-group comparison using Rasch models.

Sébille V, Blanchin M, Guillemin F, Falissard B, Hardouin JB. Sébille V, et al. Among authors: blanchin m. BMC Med Res Methodol. 2014 Jul 5;14:87. doi: 10.1186/1471-2288-14-87. BMC Med Res Methodol. 2014. PMID: 24996957 Free PMC article.

9

RespOnse Shift ALgorithm in Item response theory (ROSALI) for response shift detection with missing data in longitudinal patient-reported outcome studies.

Guilleux A, Blanchin M, Vanier A, Guillemin F, Falissard B, Schwartz CE, Hardouin JB, Sébille V. Guilleux A, et al. Among authors: blanchin m. Qual Life Res. 2015 Mar;24(3):553-64. doi: 10.1007/s11136-014-0876-4. Epub 2014 Dec 5. Qual Life Res. 2015. PMID: 25477228 Free article.

10

Overall performance of Oort's procedure for response shift detection at item level: a pilot simulation study.

Vanier A, Sébille V, Blanchin M, Guilleux A, Hardouin JB. Vanier A, et al. Among authors: blanchin m. Qual Life Res. 2015 Aug;24(8):1799-807. doi: 10.1007/s11136-015-0938-2. Epub 2015 Feb 11. Qual Life Res. 2015. PMID: 25669153

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