Research participant compensation: A matter of statistical inference as well as ethics.
The ethics of compensation of research subjects for participation in clinical trials has been debated for years. One ethical issue of concern is variation among subjects in the level of compensation for identical treatments. Surprisingly, the impact of variation on the statistical inferences made from trial results has not been examined. We seek to identify how variation in compensation may influence any existing dependent censoring in clinical trials, thereby also influencing inference about the survival curve, hazard ratio, or other measures of treatment efficacy. In simulation studies, we consider a model for how compensation structure may influence the censoring model. Under existing dependent censoring, we estimate survival curves under different compensation structures and observe how these structures induce variability in the estimates. We show through this model that if the compensation structure affects the censoring model and dependent censoring is present, then variation in that structure induces variation in the estimates and affects the accuracy of estimation and inference on treatment efficacy. From the perspectives of both ethics and statistical inference, standardization and transparency in the compensation of participants in clinical trials are warranted.
Department of Biostatistics, Harvard School of Public Health, 655 Huntington Ave., Boston, MA 02115, USA. Electronic address: dms866@mail.harvard.edu.
David M
DM
Swanson
Department of Biostatistics, Harvard School of Public Health, 655 Huntington Ave., Boston, MA 02115, USA. Electronic address: betensky@hsph.harvard.edu.
Rebecca A
RA
Betensky
D015982:Bias; D002986:Clinical Trials as Topic / Q000379:methods*; D006801:Humans; D053208:Kaplan-Meier Estimate; D016016:Proportional Hazards Models; D012044:Regression Analysis; D035842:Research Subjects; D012456:Salaries and Fringe Benefits / Q000706:statistics & numerical data*
Bias; Dependent censoring; Ethics; Participant compensation; Sensitivity analysis; Survival analysis