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To extract those orders with positive correlation among them, we used a threshold of 0.5, resulting in two separate networks, Network A and Network B. Likewise, a threshold of −0.5 was used to extract negatively correlated orders.
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We addressed the relationship between ground-state bonding properties and reactivity and found that a change of just 0.02 Å of the bridging P O(R) bond length is quantitatively correlated to orders of magnitude in change to reactivity.
On the other hand, goodness-of-fit indices showed that both correlated first-order factors and higher-order factor models of the construct could explain the data obtained from the scale.
Model 3 was a hierarchical model, with one higher-order 'negative thoughts' factor and a separate yet correlated first-order 'positive thoughts' factor.
In the current study, CFA of the HeRQoLEDv2 revealed two correlated second-order factors that explained the relationships between seven first-order factors.
Specifically, a better fit of our data with the correlated first-order factors model was found.
The above is explained through an example borrowed from the pipelined correlated filter ordering problem [6] (more details are given in Section 6).
The Autonomy over Tobacco Scale (AUTOS), a 12-item self-administered questionnaire, was designed to measure autonomy in three correlated lower-order symptom domains: withdrawal, psychological dependence, and cue-induced craving.
Depending on electron density and type of adsorption sites, the conductivity for correlated and ordered adatoms is found to be enhanced in dozens of times as compared to the cases of their random positions.
Note that although correlated, the order of presentation and of response is not necessarily identical for each trial.
A 25-item questionnaire with three correlated second-order factor structures best fitted data.
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