Examples of using Final regression in English and their translations into Portuguese
{-}
-
Colloquial
-
Official
-
Medicine
-
Financial
-
Ecclesiastic
-
Ecclesiastic
-
Computer
-
Official/political
Practical analysis of final regression model.
In the final regression model the following aspects were included.
The interactions among all covariates in the final regression model were tested.
In the final regression model, factors whose p-value was.
Age and schooling emerged as adjustment variables in all final regression models.
In the end, it was reached a final regression model with only the variables with greater statistical significance.
Although other anthropometric variables were also associated,only BMI remained in the final regression model.
Workplace violence remained in the final regression model of professional efficacy.
The final regression, after the backward and forward procedures, was termed stepwise Poisson regression. .
Significance for all the terms of the final regression model and all the possible interactions was evidenced.
Final regression model shows the association of each variable with HIV infection adjusted by the other variables.
These data support the findings of this study in which leukocyte subpopulations remained in all final regression models.
In the final regression model, significantly associated factors were found for which the p value was less than 0.05.
Table 2 presents the prevalence rates of suicidal ideation according to the characteristics that remained in the final regression model.
The final regression model is capable of explaining, approximately, 23% of the variability in physical activity behavior in this group of subjects.
The greater frequency of EBF in 1998 remained significantly higher in the final regression model even after confounder control adjusted OR=3.77;
The final regression model was able to evidence the effect of maternal schooling and job on the cognitive performance score measured in the Bayley scale.
We also checked for the potential occurrence of significant interactions between each anthropometric indicator andthe variables included in the final regression models.
Table 2 shows the final regression model for the absolute latency of waves III and V variables with no significant associations were not included in the table.
Specifically in the present study, although age exhibited a statistically significant difference in bivariate analysis,significance was not maintained in the final regression model.
The final regression models demonstrated that both volume categories replaced in the emergency care phase were related to lower mortality risks in all intervals.
R value was calculated to show how much of the variation of the dependent variable could be explained by the independent variables of the final regression model.
In the final regression model, were considered factors significantly associated with physical inactivity in commuting only those for which the p value was lower than 0.05.
All the variables with statistically significant performance in the partial models were tested in the final regression model and their results are presented in the Table 2.
Again, age andschooling were kept in the final regression models as confounding variables, and again there was no significant interaction between anthropometric indicators and these variables.
Variables independently associated with the outcome andconfounding factors were kept in the final regression model, considering plausibility and maximum likelihood estimates during the modeling process.
Alternatively, the final regression formula was used to create a logistic calculator, provided as an Excel spreadsheet electronic file or application for smartphones to be available in the near future.
This result is confirmed in part by the results of a studywhere the Zarit scale was included in the final regression model as an explanatory variable, along with the presence of partner and caregiver disease variables.
In the final regression model, prior diagnosis of CVD and moderate to severe diastolic dysfunction showed to be independent risk factors for fatal and nonfatal cardiovascular events Table 4.
In the third stage,the stepwise method was used to identify the final regression model, i.e. to identify the risk factors that presented collective and individual associations with the outcome.