The ability of randomized, clinical trials (RCTs) to produce unbiased estimates of an intervention's specific (i.e., innate pharmacologic or physiologic) effect rests on at least two assumptions. First, other prognostic effects (such as disease severity or the psychologic effects of treatment) are assumed to be evenly distributed across treatment groups, and second, it is assumed that these other effects do not interact with the intervention's specific effect. This essay shows how the effect of patients' preferences for treatments may interact with an intervention's specific effect to bias the trial's results. Earlier mathematical descriptions of how preference effects may produce bias in nonblinded trials are extended to the case of (presumably) blinded RCTs. The extent to which preference effects may confer bias in partially unblinded placebo-controlled vs. active-controlled drug trials are considered. Finally, methods for estimating preference effects in partially unblinded RCTs are provided. It is concluded that investigators could use these methods to quantify potential preference effects in partially unblinded RCTs, and thereby more accurately estimate the specific effects of treatments.