Conover MM, Rothman KJ, Sturmer T, Ellis AR, Poole C, Jonsson Funk M. Propensity score trimming mitigates bias due to covariate measurement error in inverse probability of treatment weighted analyses: a plasmode simulation. Stat Med. 2021 Apr;40(9):2101-12. doi: 10.1002/sim.8887
Webster-Clark M, Sturmer T, Wang T, Man K, Marinac‐Dabic D, Rothman KJ, Ellis AR, Gokhale M, Lunt M, Girman C, Glynn RJ. Using propensity scores to estimate effects of treatment initiation decisions: state of the science. Stat Med. 2021 Mar 30;40(7):1718-35. doi: 10.1002/sim.8866
Ritter A, Mellor R, Chalmers J, Sunderland M, Lancaster K. Key considerations in planning for substance use treatment: estimating treatment need and demand. J Stud Alcohol Suppl. 2019 Jan;Supp1 18:22-30. doi: 10.15288/jsads.2019.s18.22
Manga N, Duffy JC, Rowe PH, Cronin MTD. Structure-based methods for the prediction of the dominant P450 enzyme in human drug biotransformation: consideration of CYP3A4, CYP2C9, CYP2D6. SAR QSAR Environ Res. 2005 Feb;16(1-2):43-61.
Garcia R, Benet M, Arnau C, Cobo E. Efficiency of the cross-over design: an empirical estimation. Stat Med. 2004 Dec 30;23(24):3773-80. doi: 10.1002/sim.2072.
Cronin MT, Dearden JC, Duffy JC, Edwards R, Manga N, Worth AP, Worgan AD. The importance of hydrophobicity and electrophilicity descriptors in mechanistically-based QSARs for toxicological endpoints. SAR QSAR Environ Res. 2002 Mar;13(1):167-76.