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> And thus someone could likely draw meaningful conclusions from that data
This fails to acknowledge that data must be collected correctly, or the value is compromised. Bias or skew may be adjusted, post data collection, but this simply adds more uncertainty rather than less, as it depends on assumptions.
> Bias is defined as any tendency which prevents unprejudiced consideration of a question. Bias can occur at any phase of research, including study design or data collection, as well as in the process of data analysis and publication. Bias is not a dichotomous variable. Interpretation of bias cannot be limited to a simple inquisition: is bias present or not?
> Instead, reviewers of the literature must consider the degree to which bias was prevented by proper study design and implementation. As some degree of bias is nearly always present in a published study, readers must also consider how bias might influence a study's conclusions. *
Comment: This is what I am talking about _proper study design_. You cannot get good results from data that were not systematically collected, making every effort to avoid the problems of bias, skew and omission. Compensation by adjusting for error is a bandaid; developing a robust data set is a much better goal.
Peter L Borst
* Pannucci, C. J., & Wilkins, E. G. (2010). Identifying and avoiding bias in research.
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