Hagino H, Yoshinaga Y, Hamaya E, Lin TC, Ajmera M, Meyers J. A real-world study of treatment patterns among patients with osteoporotic fracture: analysis of a Japanese hospital database. Arch Osteoporosis. 2023 Jan 23;18(1):23. doi: 10.1007/s11657-022-01201-x
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
Quinlan SC, Hawes JCL, Mines D, Ahmed S, Lanes S, Mehta V, Holick CN, Santanello N, Mast TC. Performance of an administrative claims algorithm to estimate the incidence of pure red cell aplasia in chronic hepatitis C patients. Epidemiology reports. 2015;3(1). doi: 10.7243/2054-9911-3-1
Wade SW, Strader C, Fitzpatrick LA, Anthony MS, O'Malley CD. Estimating prevalence of osteoporosis: examples from industrialized countries. Arch Osteoporosis. 2014;9(1):182. doi: 10.1007/s11657-014-0182-3
Wade SW, Strader C, Fitzpatrick LA, Anthony MS. Sex- and age-specific incidence of non-traumatic fractures in selected industrialized countries. Arch Osteoporosis. 2012;7(1-2):219-27.
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.