These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
214 related articles for article (PubMed ID: 35661462)
1. Causal inference with observational data in addiction research. Chan GCK; Lim C; Sun T; Stjepanovic D; Connor J; Hall W; Leung J Addiction; 2022 Oct; 117(10):2736-2744. PubMed ID: 35661462 [TBL] [Abstract][Full Text] [Related]
2. Evaluating the Practicality of Causal Inference From Non-randomized Observational Data in Small-Scale Clinical Settings: A Study on the Effects of Ninjin'yoeito. Okui N Cureus; 2024 Mar; 16(3):e55825. PubMed ID: 38463406 [TBL] [Abstract][Full Text] [Related]
3. Designing observational studies for credible causal inference in addiction research-Directed acyclic graphs, modified disjunctive cause criterion and target trial emulation. Chan GCK; Sun T; Stjepanović D; Vu G; Hall WD; Connor JP; Leung J Addiction; 2024 Jun; 119(6):1125-1134. PubMed ID: 38343103 [TBL] [Abstract][Full Text] [Related]
4. Can synthetic controls improve causal inference in interrupted time series evaluations of public health interventions? Degli Esposti M; Spreckelsen T; Gasparrini A; Wiebe DJ; Bonander C; Yakubovich AR; Humphreys DK Int J Epidemiol; 2021 Jan; 49(6):2010-2020. PubMed ID: 33005920 [TBL] [Abstract][Full Text] [Related]
5. Unifying instrumental variable and inverse probability weighting approaches for inference of causal treatment effect and unmeasured confounding in observational studies. Liu T; Hogan JW Stat Methods Med Res; 2021 Mar; 30(3):671-686. PubMed ID: 33213292 [TBL] [Abstract][Full Text] [Related]
6. Instrumental variables and inverse probability weighting for causal inference from longitudinal observational studies. Hogan JW; Lancaster T Stat Methods Med Res; 2004 Feb; 13(1):17-48. PubMed ID: 14746439 [TBL] [Abstract][Full Text] [Related]
7. Using Propensity Scores for Causal Inference: Pitfalls and Tips. Shiba K; Kawahara T J Epidemiol; 2021 Aug; 31(8):457-463. PubMed ID: 34121051 [TBL] [Abstract][Full Text] [Related]
9. Squeezing observational data for better causal inference: Methods and examples for prevention research. Garcia-Huidobro D; Michael Oakes J Int J Psychol; 2017 Apr; 52(2):96-105. PubMed ID: 27094382 [TBL] [Abstract][Full Text] [Related]
10. Use and reporting of inverse-probability-of-treatment weighting for multicategory treatments in medical research: a systematic review. Bettega F; Mendelson M; Leyrat C; Bailly S J Clin Epidemiol; 2024 Jun; 170():111338. PubMed ID: 38556101 [TBL] [Abstract][Full Text] [Related]
11. Unicompartmental compared with total knee replacement for patients with multimorbidities: a cohort study using propensity score stratification and inverse probability weighting. Prats-Uribe A; Kolovos S; Berencsi K; Carr A; Judge A; Silman A; Arden N; Petersen I; Douglas IJ; Wilkinson JM; Murray D; Valderas JM; Beard DJ; Lamb SE; Ali MS; Pinedo-Villanueva R; Strauss VY; Prieto-Alhambra D Health Technol Assess; 2021 Nov; 25(66):1-126. PubMed ID: 34812138 [TBL] [Abstract][Full Text] [Related]
12. Causal Inference Methods for Estimating Long-Term Health Effects of Air Quality Regulations. Zigler CM; Kim C; Choirat C; Hansen JB; Wang Y; Hund L; Samet J; King G; Dominici F; Res Rep Health Eff Inst; 2016 May; (187):5-49. PubMed ID: 27526497 [TBL] [Abstract][Full Text] [Related]
13. Using public clinical trial reports to probe non-experimental causal inference methods. Steinberg E; Ignatiadis N; Yadlowsky S; Xu Y; Shah N BMC Med Res Methodol; 2023 Sep; 23(1):204. PubMed ID: 37689623 [TBL] [Abstract][Full Text] [Related]
14. Two basic statistical strategies of conducting causal inference in real-world studies. Fang Y Contemp Clin Trials; 2020 Dec; 99():106193. PubMed ID: 33153972 [TBL] [Abstract][Full Text] [Related]
15. Comparing approaches to causal inference for longitudinal data: inverse probability weighting versus propensity scores. Ertefaie A; Stephens DA Int J Biostat; 2010; 6(2):Article 14. PubMed ID: 21969998 [TBL] [Abstract][Full Text] [Related]
16. Minimizing bias in massive multi-arm observational studies with BCAUS: balancing covariates automatically using supervision. Belthangady C; Stedden W; Norgeot B BMC Med Res Methodol; 2021 Sep; 21(1):190. PubMed ID: 34544367 [TBL] [Abstract][Full Text] [Related]
17. Causal inference, probability theory, and graphical insights. Baker SG Stat Med; 2013 Nov; 32(25):4319-30. PubMed ID: 23661231 [TBL] [Abstract][Full Text] [Related]
18. Inferring causality from observational studies: the role of instrumental variable analysis. Fu R; Kim SJ Kidney Int; 2021 Jun; 99(6):1303-1308. PubMed ID: 33811980 [TBL] [Abstract][Full Text] [Related]
19. Formulating causal questions and principled statistical answers. Goetghebeur E; le Cessie S; De Stavola B; Moodie EE; Waernbaum I; Stat Med; 2020 Dec; 39(30):4922-4948. PubMed ID: 32964526 [TBL] [Abstract][Full Text] [Related]
20. A matching framework to improve causal inference in interrupted time-series analysis. Linden A J Eval Clin Pract; 2018 Apr; 24(2):408-415. PubMed ID: 29266646 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]