Table 5 presents results from the linear regression models examining the adherence measures as predictors of changes in CD4 count.
In order to minimize the potential effect of a healthy dietary pattern on inflammatory response we have adjusted the regression models for the adherence to a MedDiet.
In addition, we implemented a freely available open source tool, named BEBoP (understandaBility vErifier for Business Process models), to check the adherence of a model to the guidelines.
We also found that good adherence is strongly related to a lower risk of death in univariate and multivariate models, given that the adherence score was considered as continuous variable or as a binomial variable (8 10 vs 0 7 points).
In these steps, it is necessary to include the model implementation, the use of the model to forecast the system, and the model adherence to reality by matching predictions with available data.
The aim of this paper was to explore provider perspectives of the implementation of the new TB treatment adherence model, the Enhanced Tuberculosis Adherence (ETA) programme, using the normalization process model as an analytic framework [ 14].
Additionally, the adherence models were evaluated by fitting multivariate LR with stepwise functions, decision trees, and random forests models, assessing 10-fold multiple cross validation (MCV).
Also, evaluation of the adherence models was done by fitting multivariate LR with stepwise functions (Akaike information criterion [AIC] and boost), decision trees, and random forests assessing extra-sample error via multiple 10-fold cross validation (MCV), repeated 50 times with random seeds.
The following variables were included in the models: daily adherence to use of P2 or surgical masks, number of adults in the household, number of siblings in the household, and index case <5 years of age.
Multilevel multiple logistic regression was most appropriate for the adherence model (Rasbash et al., 2009).
