if the well-established disease test was determined to have the same effect as found by previous experimenters, this indicates that the experiment is being performed in the same way that the previous experimenters did. When possible, multiple positive controls may be used—if there is more than one disease test that is known to be effective, more than one might be tested. Multiple positive controls also allow finer comparisons of the results (calibration, or standardization) if the expected results from the positive controls have different sizes. For example, in the enzyme assay discussed above, a standard curve may be produced by making many different samples with different quantities of the enzyme. Randomization In randomization, the groups that receive different experimental treatments are determined randomly. While this does not ensure that there are no differences between the groups, it ensures that the differences are distributed equally, thus correcting for systematic errors. For example, in experiments where crop yield is affected (e.g. soil fertility), the experiment can be controlled by assigning the treatments to randomly selected plots of land. This mitigates the effect of variations in soil composition on the yield. Blind experiments Blinding is the practice of withholding information that may bias an experiment. For example, participants may not know who received an active treatment and who received a placebo. If this information were to become available to trial participants, patients could receive a larger placebo effect, researchers could influence the experiment to meet their expectations (the observer effect), and evaluators could be subject to confirmation bias. A blind can be imposed on any participant of an experiment, including subjects, researchers, technicians, data analysts, and evaluators. In some cases, sham surgery may be necessary to achieve blinding. During the course of an experiment, a participant becomes unblinded if they deduce or otherwise obtain information that has been masked to them. Unblinding that occurs before the conclusion of a study is a source of experimental error, as the bias that was eliminated by blinding is re-introduced. Unblinding is common in blind experiments and must be measured and reported. Meta-research has revealed high levels of unblinding in pharmacological trials. In particular, antidepressant trials are poorly blinded. Reporting guidelines recommend that all studies assess and report unblinding. In practice, very few studies assess unblinding. Blinding is an important tool of the scientific method, and is used in many fields of research. In some fields, such