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Our data methodology can be described as an embedded case study (Yin 2003) that explores issues occurring in a realistic context and is designed to combine an inductive and deductive approach (Eisenhardt 1989).
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Our data, methodologies and workflow will have to cut across different disciplines.
Our data, methodologies and approaches to tackle problems will have to cut across various disciplines.
You can examine our data and methodology here.
In publishing the index, we recognise the limitations of our data and methodology.
Thus, our data and methodology can map where respondents are located along the liberal-conservative continuum.
We are forthright with our data and methodology to encourage serious debate, independent research and further study.
Our data collection methodology provide us with a large source of reliable 'ground truth' labels about promotion, which represent an ideal testbed to evaluate detection algorithms.
According to our data organization methodology, in this case proteins correspond to Insts and are grouped into OUs, which in this case are their respective genomes.
This result suggests that, despite limitations and biases that might exist in our data, our methodology could be a useful tool to support faster and cheaper large-scale studies on gender preferences for venues.
The remainder of the paper will introduce an application of the GRM to our data, the methodology used, and how these results can be considered in order to refine the Affect Scale.
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CEO of Professional Science Editing for Scientists @ prosciediting.com