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Field added: "The measures we set out in this report are intended to reduce the chance of another scheme going down the BHS route.
To correct for multiple testing (20 total tests = 10 SNPs × 2 language measures), we set statistical thresholds using the false discovery rate with α = 0.05 (Benjamini & Hochberg 1995).
To help raise awareness of the range of relevant and available outcome measures, we set out to develop an online database of outcome measures relevant to CAM/IM interventions which would be widely available.
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Based on results concerning this measure we set up an optimization problem for the capacity allocation.
Since these descriptive phenotypes are determined by a quantitative outcome measure, we set out to find an empirical CE-MRI threshold value that can objectively segregate expanding vs. collapsed PLN.
By all measures we had set up, we were very successful, identifying hot spots, generating revenue, protecting important places.
To compare the performance of actors sets selected by the T measure with other influence measures, we selected sets of top actors based on the T measure and sets identified by measures that are known to be good heuristics for seed set selection, namely degree and betweenness centrality [26].
To compare the performance of actors sets selected by the HT measure with other influence measures, we selected sets of top actors based on the HT, T, PageRank, and Katz centrality measures.
Using multiple structural measures we identified sets of such areas in both cat and macaque cortex and demonstrated marked similarities across brain functional systems and species.
Using this information we subtracted the baseline signal as the lowest fluorescent signal measured, and we set the c(t) line to a standard deviation of 0.1.
To measure f, we set Fe to be a value as small as possible, at which the resonant peak was clear and settled in frequency.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com