Daisy Shepherd
@_DaisyShepherd
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Postdoctoral biostatistician based with @unimelb and @MCRI_for_kids | Interested in all things data-related
Melbourne, Australia
Joined August 2020
Very excited to see what the next couple of years will involve đ.
Congrats to MCRI's Dr @_DaisyShepherd who has been recognised as one of Science & Technology Australiaâs Superstars of Science, which highlights the diversity of women & non-binary Australians in #STEM. Read more: @ScienceAU @GenV_for_kids @CEBU_Melbourne
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PREPRINT: Confounding-adjustment methods for the difference in medians. .An updated version is now available with the inclusion of some lesser-known g-computation implementations. @_MargaritaMB @baersighting @CEBU_Melbourne.
arxiv.org
With continuous outcomes, the average causal effect is typically defined using a contrast of expected potential outcomes. However, in the presence of skewed outcome data, the expectation may no...
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RT @_MargaritaMB: JOB: Biostats postdoc role in my causal team @vicbiostat . Apply now / pass it around! See: NB: FâŚ.
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Congratulations @_DaisyShepherd on TWO Best Poster awards - at both #SER2021 and #ISCB2021 for "Causal inference with skewed outcome data: moving beyond the âignore or transformâ approach". Poster on our website: @_MargaritaMB
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Thank you! And a big shoutout to my wonderful supervisor and causal team colleagues at MCRI for all their help/discussion of the project @_MargaritaMB @ghazalehdashti @SusieEllul @JiaxinZhang96.
Super proud of @_DaisyShepherd having won a poster award at #SER2021 for her work on causal inference with skewed outcome data! @vicbiostat.
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An absolute honour to have my research (and first causal methods project!) recognised at the SER conference last week.
Congrats to the #SER2021 Poster Winners! Go check them out in the poster hall - filter by ranking to see all winners!
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