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Principal component analysis was used for two purposes: first, to generate a global factor for socioeconomic characteristics, uniting the information on education level, social level, family income, and IQ, because they were highly correlated (minimum correlation between them was R=0.482, P<0.001), in order to generate a new factor that could unite their characteristics.
We compare this expression to one developed by Newell and Pizer (2006) [6] for an intensity target, and show the theoretical minimum correlation between GDP and emissions required for an intensity target to be preferred over a hybrid.
In the first category, a Monte Carlo study is used to answer the question of which of several different parameterizations of an ambiguous equivalent circuit model lead to minimum correlation between fitting parameters, a desirable condition.
The minimum correlation between samples obtained up to 12 months apart was 0.67.
This sample size assuming a power of 85%%, at the 95%% level of confidence and z-score of 1.96, allows to detect a minimum correlation between anthropometric indices and HOMA-IR of 0.20 [ 22], this correlation is lower than others reported by previous studies [ 4, 18].
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(step 3c) EIC m/ z width, ± 5 ppm; minimum correlation coefficients between EIC peaks of M and M′, 0.75 for peak picking and 0.9 for feature grouping (step 3e).
We test for monogeniety in mixture fractions by finding the minimum correlation coefficient between mixture fractions of consecutive tumor sectors (ignoring normal controls) maximized over all permutations of the sectors.
We initially decided on a minimum sample size of 80 because the minimum correlation coefficient was 0.22 between VC on plain radiographs and CAD, based on our previous study.
The number of clusters was determined empirically according to the fewest clusters required to achieve a minimum correlation radius of 0.7 between any individual profile and its cognate cluster members, resulting in 30 clusters.
The threshold was set as the average value between the minimum correlation value of the positive-match distribution and the maximum value of the no-match distribution.
The minimum correlation of -0.62 was observed between LCK, coding for lymphocyte-specific protein tyrosine kinase, and PAK2, p21 protein (Cdc42/Rac -activated kinase 2. LCdc42/Rac -activatedignaling protein in many cellular processes, especially in T cell receptor (TCR) activation and T cell development [ 22].
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