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Previous models, however, predict the rewarding value to increase linearly as the outcome increases in magnitude.
Likewise, a negative coefficient – "inverse association" - means that as the predictor decreases, the outcome increases after controlling for other predictors.
Likewise, a red upward arrow—"inverse association"—means that as the level of predictor decreases, the outcome increases.
A positive coefficient – "direct association" - indicates that as the level of the predictor increases, the outcome increases after controlling for all other significant features.
Assuming that an animal is in a slightly deprived state, a linear model predicts that as the magnitude of the outcome increases, its rewarding value will increase linearly.
A blue down arrow—"direct association"—indicates that as the degree of the predictor increases, the outcome increases after controlling for other significant predictors.
Similar(52)
Neurologic complications may alter directly the outcome, increasing mortality and morbidity or indirectly by contraindicating early cardiac surgery.
uAnCR was predictive of the outcome increased length of stay (AUC = 0.77).
Adjusting for important covariates that are correlated with the outcome increased the precision and reduced the ICC.
Also, it was possible to show that variables in the proximal level were overall the ones most strongly associated with the outcome, and that, at a collective level, association strength increased as the proximity of variables to the outcome increased.
This approach enables testing of factors that may not be implicated in other work as having a relationship with the outcome, increasing the likelihood that new hypotheses are generated.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com