Examples of using Regression model in English and their translations into Portuguese
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Table 3 shows the result of the multiple logistic regression model adjustment.
The Hosmer-Lemeshow's test was applied to analyze the regression model goodness-of-fit.
Trend analysis was performed using a Poisson regression model.
The regression model met the assumptions of error normality z 1.525 and Prob.
The regression model detected excess mortality in March-April 1992- shortly after the detection of the first cases of cholera in the state in February- and in October-November 1992.
Moreover, in linear regression model is assumed that the same linear model  holds for the whole data set, but this is not always valid.
In this paper, we studied two class of residuals for the zero adjusted gamma regression model(zaga) and the zero adjusted inverse gaussian regression model  zaig.
Poisson multiple regression model in man indicated that overall sedentarism was lower among single
multiple poisson regression model with robust variance.
it distribution could be used in place of the normal distribution and consequently in regression model.
Table 3 shows the multiple linear regression model for the variables HGS and flexibility/mobility,
Variables that showed p< 0.20 in the univariate analysis were inserted into the multiple linear regression model, performed for each WHOQOL-bref domain.
The univariate linear regression model showed that an increase of one score in the HOME Inventory scale resulted in a 0.659 increase of cognitive performance R=10.6.
In the regression model, the inverse association was confirmed,
If we have a simple linear regression model, we have some equation like Y=A1X1+A2X2. Plus.
To construct the multiple logistic regression model, the stepwise forward method was used,
The Hosmer-Lemeshow test was used under the hypothesis that the multiple logistic regression model presents a well fit value p 0.8705.
Thus an intermediate step before the final adjustment of the regression model was to see whether the number of categories for these variables could be reduced.
The multiple logistic regression model showed an independent association of sociodemographic variables,
Table III presents univariate and multivariate least squares regression model results for the post-