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The properties of fairness, effectiveness and timeliness are checked in the model checker Mocha, and TTP transparency is analysed in the toolsets μCRL and CADP.
The effects of covariates (age, gender, education, monthly income, cART treatment, and months since HIV-seropositive) were also checked in the model simultaneously.
The effects of covariates (age, gender, education, monthly income, cART treatment, and months since HIV-seropositive) were checked in the model simultaneously.
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Interactions between insight and outcome and significant covariates were checked in the modelling.
These properties are intended to be consistency checks on the model, which allow the presence of possible human errors to be checked in the modelling process and the model can be guaranteed to behave as expected.
The approach uses model checking in the model construction process for testing the composite behaviors of components, including process deadlock and inconsistency in inter-component call sequences.
Therefore we checked in the numerical model the effect of vocabulary size on the multisensory enhancement function (see Figure 5b).
Collinearity was checked in the fixed model.
Potential interactions were also checked in the prediction model.
Multicollinearity effect has been checked in the multivariate model and all the variables were having a standard error <2.0.
Violations of the regression assumptions were checked in the final model using a residual-versus-fitted plot.
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