Exemplos de uso de Bivariate and multivariate em Inglês e suas traduções para o Português
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Bivariate and multivariate analyses were conducted by Poisson regression.
In the inferential statistics, bivariate and multivariate hypotheses tests were applied.
Bivariate and multivariate analyses of data were carried out through Poisson regression.
Data were analyzed with univariate, bivariate and multivariate statistical techniques.
In the bivariate and multivariate analysis, none of the variables was associated with the outcome.
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The prevalence ratios(pr)were obtained by bivariate and multivariate analysis according to a hierarchical model.
The bivariate and multivariate analyzes were performed by unconditional logistic regression.
Tables 2 and 3 show the results of bivariate and multivariate analyses for risk of MV, respectively.
Bivariate and multivariate analyses were performed to search for associated factors with embolism in ie.
The linear relationship between the research variables was investigated using two approaches: bivariate and multivariate.
Carried out simple analysis, bivariate and multivariate using the logistic regression hierarquized multiple.
The significance level of 5% and confidence interval of 95% were adopted for the bivariate and multivariate analyses.
Bivariate and multivariate analyses were performed to determine factors associated with 25(oh)d levels below the lowest tertile.
Potential factors associated with depression were investigated by bivariate and multivariate analyses, stratified by gender.
Frequency measures and bivariate and multivariate analyses were used to assess the use of comorbidity measures.
Data analysis was performed using descriptive and inferential statistics, bivariate and multivariate analysis.
Bivariate and multivariate analyses were performed to measure the effect of concomitant prolapse surgery on sling outcomes.
This provided the odds ratio OR for the bivariate and multivariate analysis, together with their respective confidence intervals CI95.
Bivariate and multivariate analyses were conducted using Poisson regressionand results were described as prevalence ratios.
As a stand-alone package,import your data and make univariate, bivariate and multivariate time series analysis interactively.
Table 4 shows the bivariate and multivariate associations of the variables analyzed with high blood pressure in adolescents.
After the discriminating analysis and use of geriatric criteria to construct the FCI, bivariate and multivariate analyses were performed.
Our bivariate and multivariate analyses demonstrated that the age variable was a significant predictor of selecting plastic surgeon as expert.
Reports were categorized and submitted to descriptive analysis and the spss software,in order to conduct bivariate and multivariate statistics.
Univariate, bivariate and multivariate analyses through logistic regression were carried out to evaluate risk factors for the outcome of interest.
However, we showed that prior plastic surgery exposure was not independent variable determinants of plastic surgeons response in bivariate and multivariate analyses.
The statistical analysis of the data included bivariate and multivariate analyses, having as reference group those with short working hours first tertile.
Bivariate and multivariate logistic regression models were constructed with variables that exhibited significant associations in the previous tests.
We conducted multiple analysis by Cox model,obtaining the ratio of hazards in the bivariate and multivariate analysis for the variables with proportionality of hazards over time.
Tables 3 and 4 show the bivariate and multivariate analyses between victimsand perpetrators of bullying, respectively, with the independent variables.