Links to online resources for advanced data analysis
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Link to this workbook:
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https://bit.ly/LinksToDataAnalysisResources
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Author contact:
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Will Masters, Friedman School of Nutrition, Tufts University (william.masters@tufts.edu)
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About this workbook:
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This is a repository of links to online advice and resources for advanced research methods and data analysis, created for use by researchers associated with the Friedman School at Tufts University, including IMMANA Fellows, other postdocs and graduate students.
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Our aim is to collect links we've found useful, so as to organize and share the 'hidden curriculum' of tips, tools and tricks as well as informal advice and guidance posted online by experienced researchers.
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The links here all concern quantitative, statistical research using data that may come from randomized trials or from surveys and other sources. Our aim is to manage large and complex datasets to generate useful descriptive statistics, hypothesis tests, and causal inference.
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What this workbook is NOT
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The workbook is not a textbook, or a complete guide to study design and implementation. It is intended only as a repository of links to online materials, organized in categories that are themselves useful for organizing one's thinking about the research process.
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Most of the sources are not specific to agriculture, nutrition and health, or to research in any particular location, but should be relevant and useful for our work.
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Mansplaining alert
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It is striking (to me, and perhaps you) that so many of the researchers who post advice online are relatively privileged people, typically white men. The positive, helpful reason for this is that they have the time, resources and self-confidence to provide "mentorship" (yes, the root of mentorship is what it sounds like...). The potentially harmful aspect of this phenomenon, aka mansplaining and colonialism, is that these voices can crowd out others and sometimes provide useless or even misleading information. We will need to curate this workbook carefully, harnessing the mansplaining impulse to harvest as much genuinely useful information as possible while also expanding the set of links to include a much wider range of material from more diverse contributors.
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