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Addressing any question in empirical sciences implies that there will be some kind of study, which needs to be designed in such fashion that it answers the question in the most unambiguous way. Scientific questions can usually fall into one of these categories: identification of influencing factors (etiology and risk factors), predicting power of those factors (prognosis and prediction), effects of interventions into those factors. To answer these questions, factors that are measured or manipulated must correspond to questions that are asked. Meaning, your outcome measure has to be relevant for your question. Preferably, it should answer your question directly. The design of your study also has to fit the outcome measure. Furthermore, if there are some factors that we are unaware of or others that are known to us but we cannot measure them, then we have to use randomization to reduce their possible influence on things that we want to measure. If you do not address things that are listed above when planning research, you can simply get wrong answers to your questions . <ref>Glasziou P, Heneghan C A spotter’s guide to study designs BMJ Evidence-Based Medicine 2009;14:37-38.</ref>
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