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The simplest assumption about how several causes jointly determine the probability of the effect is that the impact of each cause should be integrated by simple linear addition.
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SASDAS was calculated by the simple linear addition of ASDAS which includes five components: patient global assessment (NRS 0 10 cm), back pain (BASDAI question no. 2), peripheral pain and swelling (BASDAI question no. 3), duration of morning stiffness (BASDAI question no. 6), and ESR in millimeters per hour, divided by 10.
Discharge of a representative neuron is shown in Figure 7 A – D. Smooth pursuit was tested at 0.7 Hz and trunk-on-head rotation was tested at 0.3 Hz (Fig. 7 A, B ). Modulation during combined stimulation (Fig. 7 C ) was predicted by the simple linear addition of each modulation (Fig. 7 D, actual versus predicted (a + b)).
We illustrate the nonnormative nature of simple linear addition by using a coin-tossing game as an example.
Thus, manipulating both color and angle properties concurrently in WM does not result in a simple linear addition of the neural demands of each single task.
Factors included in multiple linear regression analysis were selected among variables yielding P < 0.1 by simple linear regression analysis.
Relationships between continuous variables were assessed by simple linear regression analysis.
They model expansion probability by simple linear regression.
Relationships between continuous variables were examined by simple linear regression.
Relationships between variables were determined by simple linear regression analysis.
Scatter plots were evaluated by simple linear regression analysis.
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