In this paper, we take a different perspective and discuss how to present findings derived from empirical studies that are claimed to be reproducible. This different perspective can help clarify the conflicting views expressed in the debate on reproducible research. Using an example from translational medicine, we demonstrate an approach for presenting research results by generalization of findings.
- Threats to External Validity;
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Specifically, the methodology presented here maps research findings with a conceptual boundary of meaning BOM of alternative representations of the findings. A BOM delineates a demarcation line between alternative representations of research findings that share equivalence of meaning and alternatives, that appear similar, but have difference meanings not supported by the study. We suggest that it is the responsibility of researchers to present the BOM of their study.
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This mapping can be statistically evaluated by tests of hypotheses controlling for sign type S-type errors determined by the study design. Such errors apply to statements about the direction of an effect and are different from the traditional Ho or H1 statements applied to one sided or two sided tests of hypothesis. The example is of colon cancer detection with a composite polymeric system designed to target malignant regions with dual machinery.
The research outcomes, determining affinity to colon cancer cell lines and malignant colon tissues from the rat model, were derived by statistically designed experiments. We suggest that in scientific publications, details on the study design experimental set up for repeatability purposes should be available only as supplementary material. Our main message is that reproducibility is more important than repeatability and that to inform about reproducibility characteristics, findings should be generalized. Keywords: Reproducible research, generalizability of findings, information quality, boundary of meaning.
In everyday language, a generalization is defined as a broad statement or an idea that is applied to a group of people or things. Often, generalizations are not entirely true, because there are usually examples of individuals or situations wherein the generalization does not apply. In this respect, generalizations can be similar to stereotypes in that they are sometimes offensive. These are just a few of the many examples of generalizations that exist. As you can see, a generalization is a statement that is often true, but not completely true in all cases. Next time you find yourself making an overly broad statement about a topic or a group of people, stop and think about whether you are making a generalization yourself and if you are sure that's what you want to do.
Homework is very easy. Homework is very hard. The United States is colder than Europe. Women all want to have large families.
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Men are all afraid of commitment. The best way to make new friends is to just start talking to people. Nobody really believes that the Earth is flat. Most politicians are greedy and manipulative. No American thinks staying in Iraq is the best solution.
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Cats are meaner than dogs. Dogs are smarter than cats. Most people find church boring. Everyone likes a little bit of excitement and variety in their life. Only a fool would believe what that commercial says. Three models of generalization, as proposed in a seminal article by Firestone, are discussed in this paper: classic sample-to-population statistical generalization, analytic generalization, and case-to-case transfer transferability.
Suggestions for enhancing the capacity for generalization in terms of all three models are offered. The suggestions cover such issues as planned replication, sampling strategies, systematic reviews, reflexivity and higher-order conceptualization, thick description, mixed methods research, and the RE-AIM framework within pragmatic trials. National Center for Biotechnology Information , U. Didn't get the message? Find out why Add to Clipboard.
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