Exemplos de uso de Multiple logistic regression em Inglês e suas traduções para o Português
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Results from the multiple logistic regression are expressed by odds ratio OR for one specific xp and reference categories.
Predictors of fatal outcome were subjected to multiple logistic regression, and the results are expressed as odds ratios.
Multiple logistic regression was performed to assess the association between variables
Multiple logistic regression was used to test associations between variables related to the grandmothers
The intensity of the pain was the only variable which remained in the final model of multiple logistic regression.
RR for bivariate analyses and odds ratios OR for the multiple logistic regression analysis.
In the data analysis we applied the chi-square test and performed multiple logistic regression p.
2 Gy were determined by multiple logistic regression.
multivariate analysis using multiple logistic regression(mlr) and model diagnosis.
by phone Analysis of variance and multiple logistic regression.
In addition, multiple logistic regression was performed since the variables cannot be considered independent.
The multiple logistic regression analysis explains the independent influence of the sociodemographic variables,
Table 1 lists the results of the bivariate analysis and multiple logistic regression analysis of associations between maternal characteristics consumption of milky meals,
Multiple logistic regression was used to assess the multiple relationships between extubation success
The multiple logistic regression model showed an independent association of sociodemographic variables,
Multiple logistic regression identified the age range of 60 to 70 years as one of the risk factors for pneumonia.
Multiple logistic regression was used to adjust for confounders,
using multiple logistic regression in order to determine the independent impact of each variable on the capacity to determine the presence of ILD.
Multiple logistic regression was performed to determine the association between pa
Multiple logistic regression was then conducted including the variables that were significant at 10% level in the previous analyses of bivariate models.