References

Alsan, Marcella, and Marianne Wanamaker. 2017. “Tuskegee and the Health of Black Men*.” The Quarterly Journal of Economics 133 (1): 407–55. https://doi.org/10.1093/qje/qjx029.

Arama, Charles, Jeff Skinner, Didier Doumtabe, Silvia Portugal, Tuan M. Tran, Aarti Jain, Boubacar Traore, et al. 2015. “Genetic Resistance to Malaria Is Associated With Greater Enhancement of Immunoglobulin (Ig)M Than IgG Responses to a Broad Array of Plasmodium falciparum Antigens.” Open Forum Infectious Diseases 2 (3): ofv118. https://doi.org/10.1093/ofid/ofv118.

Banack, Hailey R, Elizabeth Rose Mayeda, Ashley I Naimi, Matthew P Fox, and Brian W Whitcomb. 2023. “Collider Stratification Bias I: Principles and Structure.” American Journal of Epidemiology, October. https://doi.org/10.1093/aje/kwad203.

Brookhart, M. Alan, Sebastian Schneeweiss, Kenneth J. Rothman, Robert J. Glynn, Jerry Avorn, and Til Stürmer. 2006. “Variable Selection for Propensity Score Models.” American Journal of Epidemiology 163 (12): 1149–56. https://doi.org/10.1093/aje/kwj149.

Cohen, Jessica, and Pascaline Dupas. 2010. “Free Distribution or Cost-Sharing? Evidence from a Randomized Malaria Prevention Experiment*.” The Quarterly Journal of Economics 125 (1): 1–45. https://doi.org/10.1162/qjec.2010.125.1.1.

Cowger, Tori L., Eleanor J. Murray, Jaylen Clarke, Mary T. Bassett, Bisola O. Ojikutu, Sarimer M. Sánchez, Natalia Linos, and Kathryn T. Hall. 2022. “Lifting Universal Masking in Schools Covid-19 Incidence Among Students and Staff.” New England Journal of Medicine 387 (21): 1935–46. https://doi.org/10.1056/nejmoa2211029.

D’Agostino McGowan, Lucy. 2018. “Improving Modern Techniques of Causal Inference: Finite Sample Performance of ATM and ATO Doubly Robust Estimators, Variance Estimation for ATO Estimators, and Contextualized Tipping Point Sensitivity Analyses for Unmeasured Confounding.” PhD thesis.

D’Agostino McGowan, Lucy, Travis Gerke, and Malcolm Barrett. 2023. “Causal Inference Is Not Just a Statistics Problem.” Journal of Statistics and Data Science Education, December, 1–6. https://doi.org/10.1080/26939169.2023.2276446.

Ding, Peng, and Luke W. Miratrix. 2015. “To Adjust or Not to Adjust? Sensitivity Analysis of m-Bias and Butterfly-Bias.” Journal of Causal Inference 3 (1): 41–57. https://doi.org/doi:10.1515/jci-2013-0021.

Fox, Matthew P, Eleanor J Murray, Catherine R Lesko, and Shawnita Sealy-Jefferson. 2022. “On the Need to Revitalize Descriptive Epidemiology.” American Journal of Epidemiology 191 (7): 1174–79. https://doi.org/10.1093/aje/kwac056.

Gartner, Danielle R., Paul L. Delamater, Robert A. Hummer, Jennifer L. Lund, Brian W. Pence, and Whitney R. Robinson. 2020. “Integrating Surveillance Data to Estimate Race/Ethnicity-Specific Hysterectomy Inequalities Among Reproductive-Aged Women.” Epidemiology 31 (3): 385–92. https://doi.org/10.1097/ede.0000000000001171.

Gettleman, Jeffrey. 2015. “Meant to Keep Malaria Out, Mosquito Nets Are Used to Haul Fish In.” The New York Times, January. https://www.nytimes.com/2015/01/25/world/africa/mosquito-nets-for-malaria-spawn-new-epidemic-overfishing.html.

Godtfredsen, Nina S, Eva Prescott, and Merete Osler. 2005. “Effect of Smoking Reduction on Lung Cancer Risk.” Jama 294 (12): 1505–10.

Greifer, Noah, and Elizabeth A Stuart. 2021. “Choosing the Estimand When Matching or Weighting in Observational Studies.” arXiv Preprint arXiv:2106.10577.

Gupta, Rishi K, Ewen M Harrison, Antonia Ho, Annemarie B Docherty, Stephen R Knight, Maarten van Smeden, Ibrahim Abubakar, et al. 2021. “Development and Validation of the ISARIC 4C Deterioration Model for Adults Hospitalised with COVID-19: A Prospective Cohort Study.” The Lancet Respiratory Medicine 9 (4): 349–59. https://doi.org/10.1016/s2213-2600(20)30559-2.

Haber, N. A., S. E. Wieten, J. M. Rohrer, O. A. Arah, P. W. G. Tennant, E. A. Stuart, E. J. Murray, et al. 2022. “Causal and Associational Language in Observational Health Research: A Systematic Evaluation.” Am J Epidemiol 191 (12): 2084–97.

Harrell, Frank E. 2001. Multivariable Modeling Strategies. Springer New York. https://doi.org/10.1007/978-1-4757-3462-1_4.

Hawley, William A., Penelope A. Phillips-Howard, Feiko O. ter Kuile, Dianne J. Terlouw, John M. Vulule, Maurice Ombok, Bernard L. Nahlen, et al. 2003. “Community-wide effects of permethrin-treated bed nets on child mortality and malaria morbidity in western Kenya.” The American Journal of Tropical Medicine and Hygiene 68 (4 Suppl): 121–27.

Hernan, M. A., and S. R. Cole. 2009. “Invited Commentary: Causal Diagrams and Measurement Bias.” American Journal of Epidemiology 170 (8): 959–62. https://doi.org/10.1093/aje/kwp293.

Hernán, M. A., and J. M. Robins. 2021. Causal Inference: What If? Boca Raton: Chapman Hall/CRC.

Hernán, Miguel A. 2018. “The C-Word: Scientific Euphemisms Do Not Improve Causal Inference From Observational Data.” American Journal of Public Health 108 (5): 616–19. https://doi.org/10.2105/ajph.2018.304337.

Hernán, Miguel A., John Hsu, and Brian Healy. 2019. “A Second Chance to Get Causal Inference Right: A Classification of Data Science Tasks.” CHANCE 32 (1): 42–49. https://doi.org/10.1080/09332480.2019.1579578.

Hernán, Miguel A, and James M Robins. 2016. “Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available.” American Journal of Epidemiology 183 (8): 758–64.

Herodotus. n.d. “The History of Herodotus.” https://www.gutenberg.org/files/2707/2707-h/2707-h.htm.

Howard, S. C., J. Omumbo, C. Nevill, E. S. Some, C. A. Donnelly, and R. W. Snow. 2000. “Evidence for a mass community effect of insecticide-treated bednets on the incidence of malaria on the Kenyan coast.” Transactions of the Royal Society of Tropical Medicine and Hygiene 94 (4): 357–60. https://doi.org/10.1016/s0035-9203(00)90103-2.

Imbens, Guido W, and Donald B Rubin. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge University Press.

James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2022. An Introduction to Statistical Learning: With Applications in r. Springer.

Keil, A. P., J. K. Edwards, D. B. Richardson, A. I. Naimi, and S. R. Cole. 2014. “The parametric g-formula for time-to-event data: intuition and a worked example.” Epidemiology 25 (6): 889–97.

Kuhn, Max, and Kjell Johnson. 2013. Applied Predictive Modeling. Springer New York. https://doi.org/10.1007/978-1-4614-6849-3.

Kuhn, Max, and Julia Silge. 2022. Tidy Modeling with r: A Framework for Modeling in the Tidyverse. O’Reilly.

Lengeler, C. 2004. “Insecticide-treated bed nets and curtains for preventing malaria.” The Cochrane Database of Systematic Reviews, no. 2: CD000363. https://doi.org/10.1002/14651858.CD000363.pub2.

Lipsitch, Marc, Eric Tchetgen Tchetgen, and Ted Cohen. 2010. “Negative Controls.” Epidemiology 21 (3): 383–88. https://doi.org/10.1097/ede.0b013e3181d61eeb.

Lu, Haidong, Stephen R. Cole, Chanelle J. Howe, and Daniel Westreich. 2022. “Toward a Clearer Definition of Selection Bias When Estimating Causal Effects.” Epidemiology 33 (5): 699–706. https://doi.org/10.1097/ede.0000000000001516.

Mansournia, Mohammad A, Miguel A Hernán, and Sander Greenland. 2013. “Matched Designs and Causal Diagrams.” International Journal of Epidemiology 42 (3): 860–69. https://doi.org/10.1093/ije/dyt083.

Miao, Wang, Zhi Geng, and Eric J Tchetgen Tchetgen. 2018. “Identifying Causal Effects with Proxy Variables of an Unmeasured Confounder.” Biometrika 105 (4): 987–93. https://doi.org/10.1093/biomet/asy038.

Miller, William C. 2004. “Prevalence of Chlamydial and Gonococcal Infections Among Young Adults in the United States.” JAMA 291 (18): 2229. https://doi.org/10.1001/jama.291.18.2229.

“Mosquito Net Use in Early Childhood and Survival to Adulthood in Tanzania | NEJM.” n.d. https://www.nejm.org/doi/full/10.1056/NEJMoa2112524.

Murray, Eleanor J., and Zach Kunicki. 2022. “As the Wheel Turns: Causal Inference for Feedback Loops and Bidirectional Effects.” http://dx.doi.org/10.31219/osf.io/9em5q.

Myers, Jessica A., Jeremy A. Rassen, Joshua J. Gagne, Krista F. Huybrechts, Sebastian Schneeweiss, Kenneth J. Rothman, Marshall M. Joffe, and Robert J. Glynn. 2011. “Effects of Adjusting for Instrumental Variables on Bias and Precision of Effect Estimates.” American Journal of Epidemiology 174 (11): 1213–22. https://doi.org/10.1093/aje/kwr364.

Nevill, C. G., E. S. Some, V. O. Mung’ala, W. Mutemi, L. New, K. Marsh, C. Lengeler, and R. W. Snow. 1996. “Insecticide-treated bednets reduce mortality and severe morbidity from malaria among children on the Kenyan coast.” Tropical medicine & international health: TM & IH 1 (2): 139–46. https://doi.org/10.1111/j.1365-3156.1996.tb00019.x.

Nilsson, Anton, Carl Bonander, Ulf Strömberg, and Jonas Björk. 2020. “A Directed Acyclic Graph for Interactions.” International Journal of Epidemiology 50 (2): 613–19. https://doi.org/10.1093/ije/dyaa211.

Pearl, J., and D. Mackenzie. 2018. The Book of Why: The New Science of Cause and Effect. Penguin Books Limited.

Pearl, Judea, Madelyn Glymour, and Nicholas P. Jewell. 2021. Causal Inference in Statistics: A Primer. Wiley.

Pryce, Joseph, Marty Richardson, and Christian Lengeler. 2018. “Insecticide-Treated Nets for Preventing Malaria.” Cochrane Database of Systematic Reviews, no. 11. https://doi.org/10.1002/14651858.CD000363.pub3.

Riederer, Emily. 2020. “Column Names as Contracts.” Emily Riederer. Emily Riederer. https://emilyriederer.netlify.app/post/column-name-contracts/.

Ritchie, Hannah, and Max Roser. 2021. “Forests and Deforestation.” Our World in Data.

Robins, J. M., and L. Wasserman. 1999. On the Impossibility of Inferring Causation from Association Without Background Knowledge. Edited by P. Glymour and G. Cooper. Menlo Park, CA, Cambridge, MA: AAAI Press, The MIT Press.

Robins, James M., and Larry Wasserman. 1999. “On the Impossibility of Inferring Causation from Association Without Background Knowledge.” In. The MIT Press. https://doi.org/10.7551/mitpress/2006.003.0012.

Rosenbaum, Paul R, and Donald B Rubin. 1983. “The Central Role of the Propensity Score in Observational Studies for Causal Effects.” Biometrika 70 (1): 41–55.

Samuels, Lauren Ruth. 2017. Aspects of Causal Inference Within the Evenly Matchable Population: The Average Treatment Effect on the Evenly Matchable Units, Visually Guided Cohort Selection, and Bagged One-to-One Matching. Vanderbilt University.

Shmueli, Galit. 2010. “To Explain or to Predict?” Statistical Science 25 (3). https://doi.org/10.1214/10-sts330.

“Split Decision.” 2022. Book by Ice-T, Spike, Douglas Century | Official Publisher Page | Simon & Schuster. https://www.simonandschuster.com/books/Split-Decision/Ice-T/9781982148775.

Steck, Harald, Linas Baltrunas, Ehtsham Elahi, Dawen Liang, Yves Raimond, and Justin Basilico. 2021. “Deep Learning for Recommender Systems: A Netflix Case Study.” AI Magazine 42 (3): 7–18. https://doi.org/10.1609/aimag.v42i3.18140.

Sugiyama, Kozo, Shojiro Tagawa, and Mitsuhiko Toda. 1981. “Methods for Visual Understanding of Hierarchical System Structures.” IEEE Transactions on Systems, Man, and Cybernetics 11 (2): 109–25. https://doi.org/10.1109/tsmc.1981.4308636.

Tennant, Peter W G, Eleanor J Murray, Kellyn F Arnold, Laurie Berrie, Matthew P Fox, Sarah C Gadd, Wendy J Harrison, et al. 2020. “Use of Directed Acyclic Graphs (DAGs) to Identify Confounders in Applied Health Research: Review and Recommendations.” International Journal of Epidemiology 50 (2): 620–32. https://doi.org/10.1093/ije/dyaa213.

Textor, Johannes, Benito van der Zander, Mark S. Gilthorpe, Maciej Liśkiewicz, and George T. H. Ellison. 2017. “Robust Causal Inference Using Directed Acyclic Graphs: The R Package ‘Dagitty’.” International Journal of Epidemiology, January, dyw341. https://doi.org/10.1093/ije/dyw341.

Weinberg, Clarice R. 2007. “Can DAGs Clarify Effect Modification?” Epidemiology 18 (5): 569–72. https://doi.org/10.1097/ede.0b013e318126c11d.

Westreich, D., and S. Greenland. 2013. “The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients.” American Journal of Epidemiology 177 (4): 292–98. https://doi.org/10.1093/aje/kws412.

Williamson, Elizabeth J, Andrew Forbes, and Ian R White. 2014. “Variance Reduction in Randomised Trials by Inverse Probability Weighting Using the Propensity Score.” Statistics in Medicine 33 (5): 721–37.

“World Malaria Report 2021.” 2021. https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2021.

Wynants, Laure, Ben Van Calster, Gary S Collins, Richard D Riley, Georg Heinze, Ewoud Schuit, Elena Albu, et al. 2020. “Prediction Models for Diagnosis and Prognosis of Covid-19: Systematic Review and Critical Appraisal.” BMJ, April, m1328. https://doi.org/10.1136/bmj.m1328.

Zander, Benito van der, Maciej Liśkiewicz, and Johannes Textor. 2019. “Separators and Adjustment Sets in Causal Graphs: Complete Criteria and an Algorithmic Framework.” Artificial Intelligence 270 (May): 1–40. https://doi.org/10.1016/j.artint.2018.12.006.