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        • Blind analysis: Making all decisions regarding data analysis before the results of interest are unveiled, such that expectations about the results do not bias the analysis. Usually co-occurs with a commitment to publicize the results however they turn out. 
        • Examples of analysis decisions for which blind analysis could be useful: 
        • Confirmation bias drives the need for blind analysis.  
        • Scientists are constantly looking for bugs in scientific practices in order to fix them. Blind analysis is just the latest example of scientists recognizing a bug in their practice (e.g., a way of being fooled) and adjusting practice to account for/remove the bug.