Exemplos de uso de Binary logistic regression was used em Inglês e suas traduções para o Português
{-}
-
Colloquial
-
Official
-
Medicine
-
Financial
-
Ecclesiastic
-
Ecclesiastic
-
Computer
-
Official/political
Binary logistic regression was used p< 0.05.
In the multivariable analysis, binary logistic regression was used.
Binary logistic regression was used in the other situations.
To identify factors associated with the dependent variable, binary logistic regression was used to estimate Odds Ratio and 95% confidence intervals.
A binary logistic regression was used to express the degree of association between variables.
Univariate binary logistic regression analysis was performed to calculate odds ratios,while multivariate binary logistic regression was used to calculate adjusted odds ratios.
Binary logistic regression was used to obtain the estimates of the odd's ratio OR and confidence intervals.
For multivariate analysis, binary logistic regression was used, and the entry criteria for all variables was p.
Binary logistic regression was used for bivariate analysis aiming at identifying predictors for postpartum depression.
Multivariate analysis through multiple binary logistic regression was used to identify covariates associated with the occurrence of QoR-40.
Binary Logistic Regression was used to identify the sociodemographic, health and behavioral factors associated with non-engagement of non-users to the program.
The multivariate binary logistic regression was used to analyze the influence of sociodemographic variables with p.
Binary logistic regression was used to determine possible risk factors associated with physical activity level and selected by the backward elimination process.
Afterwards, the binary logistic regression was used again, adjusted for BMI, considering body image as a dependent variable.
Binary logistic regression was used to obtain an adjustment of the estimated odds ratio and find which risk factors were independently associated with AKI.
Binary logistic regression was used in the multivariate analysis stage, considering as outcomes: 1 feelings of loneliness most of the time or always; 2 having few friends 0-1 friends.
Binary logistic regression was used to express the level of association between independent and dependent variables, through odds ratio calculation OR and confidence interval of 95.
Binary logistic regression was used to estimate the predicted probabilities of adequate control of hypertension by age, according to education level and socioeconomic status of the household.
Binary logistic regression was used in the adjusted analysis, with effects expressed as odds ratios OR and respecting the hierarchy among the possible factors associated with the outcome Figure.
Binary logistic regression was used for analyzing the association between weight status and health perception, controlling for age, economic status, marital status, years spent in formal education, occupational status and time spent on physical activity per week.
Binary logistic regression was used to assess associations between the outcome and sociodemographic indicators gender, age, socioeconomic status, lifestyle eating habits, physical activity, alcohol consumption, aerobic fitness, and presence or absence of excess weight, estimating the odds ratio OR and the 95% confidence interval.
In the multivariate analysis, binary logistic regression was used, by estimating the odds ratio OR and 95% confidence intervals to express the degree of association between the independent variables general and abdominal obesity and the dependent variable HBP, using adjustment for age, as performed in other studies.
Descriptive analysis and binary logistic regression were used, with significance level of 5.
In the association analyses, both unadjusted andadjusted, Wald test and binary logistic regression were used to estimate odds ratios OR and 95% confidence intervals 95%CI.
Multinomial logistic regression and binary logistic regression were used to estimate, respectively, the predicted probability of occurrence of three or more doctor visits and one or more hospitalizations in the past 12 months, according to functional limitation and source of health care.
Procedures of binary logistic regression were used for the multivariable analysis.
Multivariate analysis via binary multiple logistic regression was used to identify covariables associated with the occurrence of the binary outcome.
Binary logistic regression analysis was used to determine the strength of the associations between the dependent and independent variabl.
To verify association between practice of walking outcome andenvironmental characteristics independent variables, binary logistic regression analysis was used.
In order to identify the factors significantly related to the presence of MPD, the binary logistic regression model was used.