An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials

A Bajard; S Chabaud; C Cornu; AC Castellan; S Malik; P Kurbatova; V Volpert; N Eymard; B Kassai; P Nony; the CRESim & Epi-CRESim Study Groups

doi:10.1016/j.jclinepi.2015.06.024

An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials

A Bajard, S Chabaud, C Cornu, AC Castellan, S Malik, P Kurbatova, V Volpert, N Eymard, B Kassai, P Nony, the CRESim & Epi-CRESim Study Groups

Research output: Contribution to journal › Article › Academic › peer-review

21 Citations (Scopus)

Original language	Undefined/Unknown
Pages (from-to)	125-136
Number of pages	12
Journal	Journal of Clinical Epidemiology
Volume	69
DOIs	https://doi.org/10.1016/j.jclinepi.2015.06.024
Publication status	Published - 2016
Externally published	Yes

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EMC OR-01-54-02

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10.1016/j.jclinepi.2015.06.024

Cite this

Bajard, A., Chabaud, S., Cornu, C., Castellan, AC., Malik, S., Kurbatova, P., Volpert, V., Eymard, N., Kassai, B., Nony, P., & CRESim & Epi-CRESim Study Groups, T. (2016). An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials. Journal of Clinical Epidemiology, 69, 125-136. https://doi.org/10.1016/j.jclinepi.2015.06.024

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title = "An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials",

author = "A Bajard and S Chabaud and C Cornu and AC Castellan and S Malik and P Kurbatova and V Volpert and N Eymard and B Kassai and P Nony and {CRESim & Epi-CRESim Study Groups}, the",

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Bajard, A, Chabaud, S, Cornu, C, Castellan, AC, Malik, S, Kurbatova, P, Volpert, V, Eymard, N, Kassai, B, Nony, P & CRESim & Epi-CRESim Study Groups, T 2016, 'An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials', Journal of Clinical Epidemiology, vol. 69, pp. 125-136. https://doi.org/10.1016/j.jclinepi.2015.06.024

TY - JOUR

T1 - An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials

AU - Bajard, A

AU - Chabaud, S

AU - Cornu, C

AU - Castellan, AC

AU - Malik, S

AU - Kurbatova, P

AU - Volpert, V

AU - Eymard, N

AU - Kassai, B

AU - Nony, P

AU - CRESim & Epi-CRESim Study Groups, the

PY - 2016

Y1 - 2016

U2 - 10.1016/j.jclinepi.2015.06.024

DO - 10.1016/j.jclinepi.2015.06.024

M3 - Article

C2 - 26186899

SN - 0895-4356

VL - 69

SP - 125

EP - 136

JO - Journal of Clinical Epidemiology

JF - Journal of Clinical Epidemiology

ER -