LifeCycleMethods

This database provides access to statistical methods materials on the topic of causal inference and longitudinal modelling of particular relevance to life-course epidemiology. It is fed by members of the LifeCycle project as they come along with materials of interest, with a focus on applied methods and educational papers. Many references are accessible to non-specialists.

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									Lifecycle Tutorial	false
A calibration approach to transportability with observational data	Causal Inference	Josey KP, Yang F, Ghosh D, Raghavan S	2020	arXiv:2008.06615v1 [stat.ME]	https://arxiv.org/abs/2008.06615	Original research	Transportability; observational studies; generalizability; external validity; confounding; sampling weights; calibration; data-fusion	Not peer-reviewed	No	Show
A critical evaluation of statistical approaches to examining the role of growth trajectories in the developmental origins of health and disease	Longitudinal modelling	Tu YK, Tilling K, Sterne JA, Gilthorpe MS	2013	Tu YK, Tilling K, Sterne JA, Gilthorpe MS. A critical evaluation of statistical approaches to examining the role of growth trajectories in the developmental origins of health and disease. Int J Epidemiol. 2013 Oct;42(5):1327-39. doi: 10.1093/ije/dyt157.	https://academic.oup.com/ije/article/42/5/1327/622212	educational, applied methods	Developmental origins of health and disease; birthweight; body weight; cohort studies; growth.		No	Show
Analysis of Longitudinal Studies With Repeated Outcome Measures: Adjusting for Time-Dependent Confounding Using Conventional Methods	Causal Inference and longitudinal modelling	Keogh RH, Daniel RM, VanderWeele TJ, Vansteelandt S	2018	Am J Epidemiol. 2018 May 1;187(5):1085-1092.	https://doi.org/10.1093/aje/kwx311	Educational	direct effect, indirect effect, inverse probability weight, longitudinal study, marginal structural model, sequential conditional mean model, time-varying confounder, total effect		No	Show
An Introduction to G Methods	Causal Inference	Naimi AI, Cole SR, Kennedy EH	2017	Int J Epidemiol. 2017 Apr 1;46(2):756-762.	https://academic.oup.com/ije/article/46/2/756/2760169	Educational	G Methods; Marginal Structural Model; Structural Nested Model; G Formula; Inverse Probability Weighting; G Estimation; Monte Carlo Estimation		No	Show
An introduction to instrumental variables for epidemiologists	Causal Inference	Greenland S	2000	Int J Epidemiol. 2000 Aug;29(4):722-9. doi: 10.1093/ije/29.4.722	https://academic.oup.com/ije/article/29/4/722/765560	Educational	Biometry, causal models, compliance, confounding, econometrics, epidemiological methods, instrumental variables, measurement error, misclassification, regression, regression calibration	Two errata were published: https://academic.oup.com/ije/article/29/6/1102/659250; https://academic.oup.com/ije/article/47/1/358/4774623	No	Show
Applied causal inference methods for sequential mediators	Causal Inference	Zugna D, Popovic M, Fasanelli F, Heude B, Scelo G, Richiardi L	2021	Zugna D, Popovic M, Fasanelli F, Heude B, Scelo G, Richiardi L. Applied causal inference methods for sequential mediators. BMC Med Res Methodol. 2022 Nov 24;22(1):301. doi: 10.1186/s12874-022-01764-w. PMID: 36424556.	https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-022-01764-w	tutorial	mediation analysis, sequential mediators, dierct and indirect effects, weighting, imputation		Yes	Show
Applied mediation analyses: a review and tutorial	Causal Inference	Lange T, Hansen KW, Sørensen R, Galatius S	2017	Epidemiol Health. 2017 Aug 6;39:e2017035.	https://www.e-epih.org/upload/pdf/epih-39-e2017035.pdf	Tutorial	Mediation analysis, Causal inference, Pathway analysis, Acute coronary syndrome, Randomized clinical trials		No	Show
Applying the exposome concept in birth cohort research: a review of statistical approaches	Exposome and omics	Santos S, Maitre L, Warembourg C, Agier L, Richiardi L, Basagaña X, Vrijheid M.	2020	Eur J Epidemiol. 2020 Mar;35(3):193-204.	https://link.springer.com/article/10.1007/s10654-020-00625-4	Educational	birth cohort studies, exposure approaches, correlation, dimensionality, variability		Yes	Show
Approaches for incorporating environmental mixtures as mediators in mediation analysis	Causal Inference	Bellavia A, James-Todd T, Williams PL	2019	Environ Int. 2019 Feb;123:368-374. doi: 10.1016/j.envint.2018.12.024	https://www.sciencedirect.com/science/article/pii/S016041201832021X?via%3Dihub	Review	Environmental mixtures; Environmental epidemiology; Mediation analysis		No	Show
A Practical Guide to Regression Discontinuity	Causal Inference	Jacob R, Zhu P	2012	Web site: www.mdrc.org	https://www.mdrc.org/sites/default/files/RDD%20Guide_Full%20rev%202016_0.pdf	Educational	Regression discontinuity approach, internal validity, generalizability		No	Show
A Practical Introduction to Regression Discontinuity Designs: Foundations	Causal Inference	Cattaneo MD, Idrobo N, Titiunik R	2019	arXiv:1911.09511v1. doi: 10.1017/9781108684606	https://arxiv.org/abs/1911.09511	Tutorial	Regression discontinuity; Econometrics; Computation		No	Show
A proposal for capturing interaction and effect modification using DAGs	Causal Inference	Attia J, Holliday E, Oldmeadow C.	2022	Attia J, Holliday E, Oldmeadow C. A proposal for capturing interaction and effect modification using DAGs. Int J Epidemiol. 2022 Aug 10;51(4):1047-1053.	https://academic.oup.com/ije/article/51/4/1047/6607680	Opinion	interaction, effect modification, confounding, DAGs	Erratum in Correction to: A proposal for capturing interaction and effect modification using DAGs. Attia J, Holliday E, Oldmeadow C. Int J Epidemiol. 2022 Jul 20:dyac153.	No	Show
A review of generalizability and transportability	Causal Inference	Degtiar I, Rose S	2021	arXiv:2102.11904v1 [stat.ME] for this version	https://arxiv.org/abs/2102.11904#:~:text=Abstract%3A%20When%20assessing%20causal%20effects,generalize%20is%20a%20critical%20decision.&text=Estimates%20from%20randomized%20data%20may,representative%20of%20the%20target%20population.	Educational paper	external validity; transportability; generalizability	Not peer-reviewed	No	Show
A selective review of negative control methods in epidemiology	Causal Inference	Shi X, Miao W, Tchetgen ET	2020	Curr Epidemiol Rep. 2020 Dec;7(4):190-202. doi: 10.1007/s40471-020-00243-4	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118596/	Review	Bias correction; Bias detection; Bias reduction; Negative control; Unmeasured confounding		No	Show
Assessing environmental epidemiology questions in practice with a causal inference pipeline: An investigation of the air pollution‐multiple sclerosis relapses relationship	Causal Inference	Sommer AJ, Leray E, Lee Y, Bind MC	2021	Stat Med 2021 Mar 15;40(6):1321-1335. doi: 10.1002/sim.8843	https://onlinelibrary.wiley.com/doi/full/10.1002/sim.8843	Applied methods	Causal inference; environmental epidemiology; matching; multiple sclerosis; observational data		No	Show
Assessing Natural Direct and Indirect Effects Through Multiple Pathways	Causal Inference	Lange T, Rasmussen M, Thygesen LC	2014	Am J Epidemiol. 2014 Feb 15;179(4):513-518.	https://doi.org/10.1093/aje/kwt270	Educational	causal inference, mediation, multiple mediators		No	Show
Association of maternal diabetes mellitus in pregnancy with offspring adiposity into early adulthood: sibling study in a prospective cohort of 280,866 men from 248,293 families	Causal Inference	Lawlor DA, Lichtenstein P, Långström N.	2011	Circulation. 2011 Jan 25;123(3):258-265. doi: 10.1161/CIRCULATIONAHA.110.980169	https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.110.980169?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub++0pubmed&	Applied methods	within sibship, developmental origins, causal inference		No	Show
Association of pre-pregnancy body mass index with offspring metabolic profile: findings from 3 European prospective birth cohorts	Causal Inference	Santos Ferreira DL, Williams DM, Kangas AJ, Soininen P, Ala-Korpela M, Davey Smith G, Jarvelin M-R, Lawlor DA	2017	PLoS Med. 2017 Aug 22;14(8):e1002376. doi: 10.1371/journal.pmed.1002376	https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002376	Applied methods	Negative control, metabolomics, developmental origins, parental comparisons		No	Show
A structured approach to hypotheses involving continuous exposures over the life course	Longitudinal modelling	Smith ADAC, Hardy R, Heron J, Lawlor DA, Joinson CJ, Macdonald-Wallis C, Tilling K	2016	Int J Epidemiol. 2016 Aug;45(4):1271-1279. doi:10.1093/ije/dyw164	https://academic.oup.com/ije/article/45/4/1271/2951966	Applied methods	Lifecourse models, repeat measures, continuous data		No	Show
Baseline selection on a collider: a ubiquitous mechanism occurring in both representative and selected cohort studies	Causal Inference	Richiardi L, Pearce N, Pagano E, Di Cuonzo D, Zugna D, Pizzi C	2019	J Epidemiol Community Health. 2019 May;73(5):475-480.	https://jech.bmj.com/content/73/5/475.long	Research article	bias; cohort studies; collider bias; representativeness; selection		No	Show
Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies	Causal Inference	Haycock PC, Burgess S, Wade KH, Bowden J, Relton C, Davey Smith G	2016	Am J Clin Nutr. 2016 Apr;103(4):965-978.	https://academic.oup.com/ajcn/article/103/4/965/4564602	Educational	Mendelian randomization, practice of MR, writing MR papers, assumptions of MR		No	Show
Carryover Effects in Sibling Comparison Designs	Causal Inference	Sjölander A, Frisell T, Kuja-Halkola R, Öberg S, Zetterqvist J	2016	Epidemiology. 2016 Nov;27(6):852-858. doi: 10.1097/EDE.0000000000000541	https://journals.lww.com/epidem/Abstract/2016/11000/Carryover_Effects_in_Sibling_Comparison_Designs.12.aspx	Educational	Siblings design; bias; carryover effect; causal diagrams; confounding		No	Show
Causal inference and the data-fusion problem	Causal Inference	Bareinboim E, Pearl J	2016	Proc Natl Acad Sci U S A. 2016 Jul 5;113(27):7345-7352.	https://www.pnas.org/content/113/27/7345	Research article	generalizability, transportability, selection bias, confounding	The paper provides a theoretical background; no codes are available for implementation	No	Show
Causal Inference in Statistics: A Primer	Causal Inference	Pearl J, Glymour M, Jewell NP	2016	Wiley 2016. 156 pages. ISBN: 978-1-119-18684-7	https://www.wiley.com/en-gb/Causal+Inference+in+Statistics%3A+A+Primer-p-9781119186847	Textbook	DAGs, Causal Inference, Counterfactuals		No	Show
Causal inference - so much more than statistics: an essay review of Causal Inference in Statistics: A Primer by Judea Pearl, Madelyn Glymour, and Nicholas P. Jewell	Causal Inference	Pearce N, Lawlor DA.	2017	Int J Epidemiol. 2016 Dec 1;45(6):1895-1903. doi: 10.1093/ije/dyw328	https://academic.oup.com/ije/article/45/6/1895/2999350	Educational	DAGs, Causal inference, Collider Bias		No	Show