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Missing data: Mechanisms and Mitigations

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CIFW02 - Causal identification and discovery

I will summarise recent work on using DAGs to explore MAR , and subsamples where MAR might hold, and parametric assumptions underlying bias when estimating a “causal” association using linear or logistic regression. Then I will discuss ongoing work about the implications of these for (a) exploring the potential missingness mechanisms (i.e. causal discovery mainly of missingness) and (b) using a causal discovery algorithm (pcalg) to explore DAGs for the substantive data, with/without the missing data mechanisms.

This talk is part of the Isaac Newton Institute Seminar Series series.

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In person in the Max Perutz Lecture Theatre (CB2 0QH) and via Zoom, link: https://mrc-lmb-cam-ac-uk.zoom.us/j/91756905972?pwd=RlI2cU0wdmkrblZ0VkpLWmtiRThUdz09 Alison Richard Building 2nd Floor, Centre of Development Studies Meeting Room Addenbrooke's Seminar Room 7 (Clinical School)

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