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The goal of the tree is to generate a model ϕ(X 1,X 2,…,X q ) in the form of a decision tree for predicting the value of C from the values taken by the predictive variables.
59.9 % of the variation in the PDQ-39 summary index (SI) score was explained by the predictive variables identified in this study.
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We compared two models by Akaike information criterion (AIC) [29]: the first was composed by all the predictive variables with no interaction and a second with all the variables plus age crossed with the physical activity intensity level (Borg scale).
The predictive variables formed the fixed effects of the model.
The predictive variables were the above described objective, socioeconomic, subjective and treatment variables.
For this reason, in the multiple regression vitamin D status analysis, we chose to use age as the predictive variable, adjusted by gender and ethnicity.
Using a model of multiple linear regression, setting the age as the predictive variable and adjusting by ethnicity and gender, the following correlations were still significant: PTH (p = 0.01), ionized calcium (p = 0.048) and month of the year (p = 0.01).
"Best" is defined by how well the variable splits the set into homogeneous subsets that have the same value of the predictive variable [35].
Next, classification and regression trees (CART) [ 19] were composed that divided the sample in subgroups as homogeneous as possible with regard to the outcome by selecting the most predictive variables based on minimum prediction error.
To reduce the number of variables to be entered into one overall regression analysis to produce the final model predicting QoL-AD scores, the following method was adopted, which maximised the potential for a strong prediction by selecting the most predictive variables from each domain, and allowed identification of the domains which appeared most relevant to QoL-AD scores.
Although a total of 19 global bioclimatic variables are available from WorldClim database [47], the precision of the predictions may be biased by the selection of predictive variables [25].
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