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In settings such as this, many commonly used statistical approaches for estimating treatment effects, such as g-methods, often adopt the \u2018no unmeasured confounding\u2019 assumption. Instrumental variable (IV) methods aim to reduce biases due to unmeasured confounding, but have received limited attention in settings with time-varying treatments. This paper extends and critically evaluates a commonly used IV estimating approach, Two Stage Least Squares (2SLS), for evaluating time-varying treatments. Using a simulation study, we found that, unlike standard 2SLS, the extended 2SLS performs relatively well across a wide range of circumstances, including certain model misspecifications. We illustrate the methods in an evaluation of treatment intensification for Type-2 Diabetes Mellitus, exploring the exogeneity in prescribing preferences to operationalise a time-varying instrument.<\/jats:p>","DOI":"10.1177\/09622802251404064","type":"journal-article","created":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T16:35:57Z","timestamp":1765816557000},"page":"346-369","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Two stage least squares with time-varying instruments: An application to an evaluation of treatment intensification for type-2 diabetes"],"prefix":"10.1177","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6761-6270","authenticated-orcid":false,"given":"Daniel","family":"Tompsett","sequence":"first","affiliation":[{"name":"University College London"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stijn","family":"Vansteelandt","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics, Computer Science, and Statistics, University of Ghent, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard","family":"Grieve","sequence":"additional","affiliation":[{"name":"London School of Hygiene and Tropical Medicine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Robson","sequence":"additional","affiliation":[{"name":"Wolfson Institute of Population Health"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manuel","family":"Gomes","sequence":"additional","affiliation":[{"name":"University College London"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,12,15]]},"reference":[{"key":"e_1_3_3_2_2","volume-title":"Causal Inference:What If","author":"Hern\u00e1n M","year":"2020","unstructured":"Hern\u00e1n M, Robins J. 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