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Using a fixed-effects panel regression methodology, we analyzed liquidity and order imbalance simultaneously as potential explanatory factors.
Applying our methodology, we analyzed experimental data on the in vitro evolution of a random polypeptide (139 amino acids) toward acquiring infectivity (=" ability to infect) of fd phage.
Because the four sub-cohorts differed according to inclusion criterion, clinical setting, screening-question expression, and assay methodology, we analyzed each separately and then pooled across subcohorts after examining heterogeneity of effect.
Furthermore, in keeping with the methodology, we analyzed data while still conducting interviews [ 21].
Using this methodology we analyzed a total of 10 samples in each group, from patients with active HIV disease and normal non-HIV controls.
As an application of the methodology, we analyzed the iAF1260 version of the K12 MG1655 strain of E. coli [ 32] provided in the BiGG database [ 33, 34].
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As an example of the methodology, we analyze two geographical locations on Earth with distinct spectral conditions.
In our design methodology, we analyze several aspects involved, from high-level application analysis down to fine-grained operations and physical aspects (e.g. geometry and spatial distribution).
In particular, for each methodology, we analyze which software process model it (often implicitly) underlies and which phases of the process are covered by it, thus enabling us to identify some key limitations of currently methodology-centered researches.
Using our methodology, we analyze real surveillance data consisting of 2008 2010 Indiana respiratory syndrome counts from the PHESS data set.
These results agree extremely well with a previous study from our group, although there we employed a different statistical methodology and we analyzed 16 tissues in a smaller number of animals (four) [ 3].
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