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This allows us to differentiate the different models reported as well as highlight models that are being repeatedly utilized.
Bivariate associations of the outcomes by explanatory variables were tested using Ordinary Least Squares (OLS) regression, with regression coefficients from multivariable models reported as adjusted effects.
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Such a core could correspond to the list [Gly, Ala, Val, Pro, Glu], in which the only notable discrepancy is for Val following the Jordan et al. [ 9] model (reported as a "weak gainer").
In the paper, the model is described in detail and the results derived from its application to a real test case are discussed; a computational analysis of the model is reported as well.
The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential.
Variables entered into models are listed in Section 3 and graphs of results show predictions derived from significant models; full estimates from these multilevel models are reported as supplementary data (see electronic supplementary material (ESM)).
Coefficients from the logistic regression models were reported as odds ratios.
Intraclass correlation coefficients (ICC3) calculated by two-way mixed models and reported as average values.
Nevertheless, a higher number of Markov models are reported as independently conducted CEAs, whereas decision trees, ISM and DES tended to be adopted more often.
Outcome models are reported as odds ratios (ORs) with 95%% confidence intervals (CIs).
Results from the multivariable regression models are reported as RRs with 95% CIs.
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CEO of Professional Science Editing for Scientists @ prosciediting.com