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. 2021 Jul 12;7(2):e001654. doi: 10.1136/rmdopen-2021-001654

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© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Directed acyclic graphs (DAGs) representing (A) a longitudinal study with time-varying confounding and (B) a longitudinal study with time-varying mediation. For the purpose of illustration, the DAGs are simplified (absent arrows) by making the following (unlikely to hold) assumptions: Y_t+1 does not influence T_t+1; Y_t+1 does not influence Y_t+2; C_t does not influence C_t+1. Black arrows, associations of interest (‘front doors’); red arrows, biasing paths (‘back doors’); T_t, treatment status (yes/no) at the start of the first interval; T_t+1, treatment status at the start of the second interval; C_t, a set of pretreatment confounders at the start of the first interval; C_t+1, a set of pretreatment confounders at the start of the second interval; Y_t+1, outcome at end of the first interval; Y_t+2, outcome at the end of the second interval; M_t*, mediator measured after treatment assignment and before outcome assessment on the first interval; M_t+1*, mediator measured after treatment assignment and before outcome assessment on the second interval.