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As such, the model included variables such as parents' socio-economic group (high; medium (reference category) and low) and school type (Adolfo Portela School (reference category) and Marques Castilho School/technological related school).
This logistic regression model included variables that were statistically significant (p < 0.05) in the univariate analysis, and in the final model, only variables that were statistically significant were included.
The model included variables such as the achieved level of education (vocational education or lower and high school diploma or higher) as an indicator of the socioeconomic status, the gender of the respondents, and age groups (60 69 years old and older than 70 years).
A multivariable logistic regression model included variables whose associations with vaccination decisions were statistically significant, defined as p<0.05.
The final model included variables and interactions that were significant on the Wald Chi-square test as well as all variables included in the interaction terms even if these did not reach statistical significance on their own [32].
aThe model included variables with statistical significance only.
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Our specification of the model includes variables typically employed in the literature (Dang et al. 2014; Cruces et al. 2011), plus statistically significant variables at the regional level.
a The multivariate model includes variables for which p < 0.10 by univariate analysis.
Thus, the Detroit model includes variables to account for proximity to industrial facilities that either presently or historically emit lead.
We used a logistic regression model including variables that were significant in the univariate analysis (p < 0.05) with backward elimination.
For the model including variables from GP EMRs (IPAEOPGP), the level of variation in regression coefficients (size and direction) was somewhat greater for those variables derived from GP data.
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