My research interests include the analysis of repeated measures and longitudinal data, statistical methods for patient-reported outcome measures (PROMs), and measurement invariance (differential item functioning and response shift). As a research engineer in biostatistics, my research aims to develop and validate through simulation studies statistical methods to address the challenges of analyzing longitudinal PRO data. My works are applied in different chronic conditions such as some cancers, difficult-to-treat depression, end stage renal disease and inflammatory bowel disease. The modules for PRO analysis developed with my colleagues are available on ssc for Stata module and on PRO-online website.
How to investigate the effects of groups on changes in longitudinal Patient-Reported Outcomes and response shift using Rasch Models.
Hammas K, Sébille V, Brisson P, Hardouin J-B, Blanchin M.
Comparison of structural equation modelling, item response theory and Rasch measurement theory-based methods for response shift detection at item level: A simulation study.
Blanchin M, Guilleux A, Hardouin J-B, Sébille V.
Comparison of longitudinal quality of life outcomes in preemptive and dialyzed patients on waiting list for kidney transplantation.
Auneau-Enjalbert L, Hardouin J-B, Blanchin M, Giral M, Morelon E, Cassuto E, et al.
Changes in quality of life after a diagnosis of cancer: a 2-year study comparing breast cancer and melanoma patients.
Bourdon M, Blanchin M, Tessier P, Campone M, Quéreux G, Dravet F, et al.
Identifying patterns of adaptation in breast cancer patients with cancer‐related fatigue using response shift analyses at subgroup level.
Salmon M, Blanchin M, Rotonda C, Guillemin F, Sébille V.