Examples of using Predictor variables in English and their translations into Portuguese
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Colloquial
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Official
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Medicine
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Financial
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
Predictor variables.
But now, we could have a whole set of predictor variables.
Predictor Variables of burnout experience.
For the input of the predictor variables into the model a p-value.
Predictor variables that showed to have influence with a significance level.
Finally, we tested the predictor variables of burnout experience.
The relative risk was calculated in order to determine the associations among predictor variables.
All predictor variables with p< 0.05 were mantained in the final model.
In the alternative hypothesis, with 18 predictor variables and statistical power of.
The Chi-square test?was used to analyze potential association between the outcome and the predictor variables.
Univariate analysis between the outcome and predictor variables was performed obtaining odds ratio.
In digital soil mapping the terrain attributes have been used as the main environmental predictor variables.
Table 2 displays the Regression Analysis with the predictor variables in relation to career indecision.
Inclusion of the predictor variables considered national and international literature relevant for the outcome of CMD.
Ideally, a highly accurate but parsimonious model with few predictor variables is desired.
The predictor variables were selected based on literature reviews about return to work and disability benefits.
Figure 1- Theoretical structure used in the selection of the predictor variables presented in the study p< 0.25.
The outcome predictor variables were female sex, peak systolic aortic jet velocity and initial BNP value.
The third was performed using the method of simultaneous input of predictor variables age group, gender and the three diseases.
As two predictor variables were used, the 31-subject sample was enough to avoid compromising the regression quality.
Table 4 presents the results of the crude and adjusted analyses of the predictor variables associated with the outcome of hospital death.
The predictor variables were socio-demographic data, self-reported health conditions, and functional and cognitive capacities.
We showed that only univariate models were employed due to issues of multi-collinearity among the SES indicator predictor variables.
Univariate analysis with the predictor variables and the categorization made by the likelihood ratio test was performed.
The advantage of this approach is that it used all available data andadjusted results based on correlations between outcomes and predictor variables.
To analyze the predictor variables, the logistic regression model was used, adopting the occurrence or not of falls as the outcome p.
Multiple linear regressions were done to identify predictor variables for 25 cognitive tests scores dependent variables. .
Predictor variables with associations with p-value below 0.20 were inserted in the multiple linear regression, using the forward method.
Table 4 presents the unadjusted and adjusted analysis results of predictor variables associated with the outcome"Pap smear adherence.
The effect size of predictor variables were obtained through a general linear model using a negative binomial regression link function.