APA (7th ed.) Citation

Brooks, J. M., Chapman, C. G., Floyd, S. B., Chen, B. K., Thigpen, C. A., & Kissenberth, M. (2022). Assessing the ability of an instrumental variable causal forest algorithm to personalize treatment evidence using observational data: The case of early surgery for shoulder fracture. BMC Medical Research Methodology, 22(1), 1. https://doi.org/10.1186/s12874-022-01663-0

Chicago Style (17th ed.) Citation

Brooks, John M., Cole G. Chapman, Sarah B. Floyd, Brian K. Chen, Charles A. Thigpen, and Michael Kissenberth. "Assessing the Ability of An instrumental Variable Causal Forest Algorithm to Personalize Treatment Evidence Using Observational Data: The Case of Early Surgery for Shoulder Fracture." BMC Medical Research Methodology 22, no. 1 (2022): 1. https://doi.org/10.1186/s12874-022-01663-0.

MLA (9th ed.) Citation

Brooks, John M., et al. "Assessing the Ability of An instrumental Variable Causal Forest Algorithm to Personalize Treatment Evidence Using Observational Data: The Case of Early Surgery for Shoulder Fracture." BMC Medical Research Methodology, vol. 22, no. 1, 2022, p. 1, https://doi.org/10.1186/s12874-022-01663-0.