The process of science doesn't require that every experiment and every study be repeated, but many are, especially those that produce surprising or particularly important results.
In some fields, it is standard procedure for a scientist to replicate his or her own results before publication in order to ensure that the findings were not due to some fluke or factors outside the experimental design. The desire for replicability is part of the reason that scientific papers almost always include a methods section, which describes exactly how the researchers performed the study.
That information allows other scientists to replicate the study and to evaluate its quality, helping ensure that occasional cases of fraud or sloppy scientific work are weeded out and corrected. Estimating the reproducibility of psychological science. Kahneman D. A new etiquette for replication.
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I Accept Show Purposes. The replicated results were a false negative. Both studies were correct but differed due to unknown differences in experimental conditions or methodologies. Was this page helpful? Thanks for your feedback! Sign Up. What are your concerns? Positive findings about ESP are often reported, but so far they always disappear when somebody skeptical about ESP tries to replicate them.
The same thing can happen in education and health research. That is why double- blind research is the gold standard of science. It prevents expectations from altering the outcome of research, as we will discuss presently. When proper controls such as double-blind design are used, researchers may be unable to repeat a finding first reported by enthusiasts. If so, the finding is open to doubt.
There are also occasions when a dishonest researcher commits fraud. The field of social psychology was traumatized in when several Dutch researchers were found to have published fraudulent data. This type of misbehavior is also detected by failures of replication.
An example of a fraud detected by replication failures is the "spotted mice" scandal at the prestigious Sloan-Kettering Institute in the early s. A research scientist was working under pressure to produce successful skin grafts from black-furred mice to white-furred mice.
In all previous experiments, such grafts failed to succeed because the host animal rejected the foreign tissue. This was important research, because organ rejection commonly occurs after transplants. The scientist who faked the skin graft was riding in an elevator early one morning with a batch of his white-furred mice and a permanent ink marking pen. The reports of a successful transplant surprised other scientists.
They tried to replicate the experiment, and they could not. In this case, after failed replications, the scientist confessed what he had done, so the mysterious results were explained. The consequences of fraud are devastating for a scientist, leading to dishonor and usually to the loss of job and career. Scientists know any important result will be subjected to attempts at replication.
This provides a powerful incentive for honesty among researchers. That's because you know that not everyone will respond the same, that there is variation to be expected. Therefore, you would test the new medicine on many, many people replicates. A well-replicated experiment ensures that the effect of one thing the independent variable on the other the dependent variable is real, true, reliable, valid. It accounts for the variation we expect to exist in nature. It also accounts for the error we desperately try to control.
Suppose you were measuring the elevation in heart rate of a mouse due to the appearance of a cat. You might be off in your measurement by a beat or two, but if you have enough replicates then the average of those replicates will give you a reliable estimate. Why is replication important in experimental design?
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