Exemplos de uso de Binary logistic regression model em Inglês e suas traduções para o Português
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The variables with p<0.10 were subjected to binary logistic regression model.
Binary logistic regression models Enter method were run with all these variables.
We attempted to define critical values using a ROC curve, andwe tested various binary logistic regression models.
Binary logistic regression models were built where independent variables with p.
These variables were included in the multivariate binary logistic regression model, adjusted for gender and age.
The binary logistic regression model was adjusted to assess possible risk factors for UI.
Y- new binary variable that will be used as a response in adjusting the binary logistic regression model;
Dynamic update of binary logistic regression model for fraud detection in electronic….
In order toidentify the factors significantly related to the presence of MPD, the binary logistic regression model was used.
A binary logistic regression model enter method was used to identify characteristics predictive of incorrect inhaler technique.
This model has different intercepts and coefficients for each comparison andcan be adjusted for k binary logistic regression models.
Binary logistic regression models, which predict the presence or absence of sleep apnea, could provide immediately useful information.
To assess the statistical significance of the frequency variation observed from 2006 to 2009, binary logistic regression models were developed.
Table 4 Multivariate analysis(binary logistic regression model) assessing factors associated with the occurrence of WMSD, according to data from the PNS, Brazil, 2013.
Variables with significance at 0.1 or less, adjusted for gender and age,were included in the multivariate binary logistic regression model enter method for predictors of a favorable response.
Descriptive analyses and binary logistic regression models were estimated for the dependent variables"be enrolled in school" and"be in situation of age-grade di.
And to establish the risk profile for manifestation of violence and verify, which of these, has the greatest chance of recurrence,was used the binary logistic regression model.
The multiple binary logistic regression model was then determined from variables that presented significance probability p-value of less than 0.25 in the univariate analysis.
Although many methods have been developed for evaluating the adjustment of binary logistic regression models, few of these methods have been extended to ordinal response data.
We used the binary logistic regression model, which studies the probability of an event that presents a dichotomous qualitative way, based on the behavior of explanatory variables.
To assess the possible factors associated with the occurrence of WMSD, Pearson's Chi-square test was used,as well as the binary logistic regression model, both univariate and multivariate.
Indeed, since these results were analyzed by using a binary logistic regression model, adjusted for all the other variables, PAI-1 seems to be independently associated with CAD> 70% p< 0.001.
The non-collinear variables that reached significance p< 0.01 in the univariate analysis, adjusted for gender andage, were included in a binary logistic regression model using the forward conditional method.
The binary logistic regression model, from the OR risk estimator, confirmed that female adolescents, in the EP, with overweight or obesity had a significant association with body dissatisfaction Table 4.
The non-collinear variables that reached significance p<0.01 in the univariate analysis were included in a stepwise forward conditional binary logistic regression model adjusted for gender and age for each outcome.
In the binary logistic regression model, the 1-point increase in the ISS represented 9% increase in the likelihood of kidney injury development, as it increases the risk of death by 7.5 fold.
Considering the biopsy results as malignant orbenign, to analyze the association we used binary logistic regression models and assessed the odds ratios of malignancy for each TI-RADS category.
We used univariate exact binary logistic regression models to investigate whether there was any relationship between unsatisfactory results and longer duration of preoperative pain or between unsatisfactory results and performing tenotomy procedures, with or without tenodesis of the LHB tendon.
Raw odds ratios were calculated for each risk factor andfor those with statistical significance adjusted odds ratios were calculated by means of a binary logistic regression model, with 95% confidence intervals.
In the context of ordinal regression, it is necessary to calculate binary logistic regression models for all the cut-off points of the response variable Y, with the partial residual for each case i and the covariable p being defined in the following way.