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Each variable (age, sex and municipality) was tested for significant dependence in a univariate model and added to the multivariate model according to the strength of dependence.
Table 4 lists mean ranges for GEDVI values calculated with the final multivariate model according to the age groups defined for univariate analysis.
In the second step, each variable related to burnout in at least one MBI subscale were included in the multivariate model according to a forward stepwise approach.
Variables with a p-value <0.10 in the univariate analysis were offered forward to the multivariate model according to the time sequence of the occurrence of these risk factors; models were checked for interaction.
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7 However, each individual study may cover a small number of factors (a median of 7 factors considered per study with multivariate models according to Mantzavinis et al 7) and the authors of this review suggest that forthcoming studies should cover a large number of important factors comprehensively, use a large sample size, and adopt adequate multivariate modelling.
For example, Spiker's and Silverman's examined clustering according to the Autism Diagnostic Interview (ADI-R), whilst Constantino's [ 13] examined clustering on the Social Reciprocity Scale (SRS) and Ronald's [ 8] examined multivariate model fitting according to Childhood Asperger Syndrome Test (CAST).
Factors associated with GBS by univariate analysis (P < 0.10) were considered eligible for inclusion in a multivariate model and retained in the model according to a forward stepwise procedure based on a likelihood-ratio test.
Interestingly, we obtained very consistent results using either a classic multivariate logistic regression model (the best model according to c statistics and the Hosmer-Lemeshow test) or logistic regression models based on propensity score considered as a continuous variable, a variable categorized according to score quintiles or a matching variable.
Parameters included in the multivariate model were selected according to the statistical significance in univariate models.
Variables for the multivariate model were selected according to the recommendations of Hosmer and Lemeshow (28 ).
The best set of variables for the multivariate model was chosen according to simplicity and fitness criteria through a stepwise approach.
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