Sentence examples for by multivariate analysis using from inspiring English sources

Factors attaining a P-value of less than 0.1 in univariate analysis were evaluated by multivariate analysis using Cox proportional hazard regression analyses.

The relationship between specific growth rate and initial body weight in fish was analysed by multivariate analysis using data sets from growth studies on rainbow trout (initial weight between 10 and 30 g, n=546) and Atlantic salmon (initial weight between 10 and 20 g, n=355).

Various prognostic factors were analyzed by multivariate analysis using logistic regression.

Variables associated with outcome were identified by multivariate analysis using logistic regression.

In further support, associations with outcome for CSR in ER-positive (Figure 5D), LN-positive and TAM tumors were supported by multivariate analysis using ER-status, LN-status and stratified histological grade as covariates when applicable.

The associations between potential risk factors and TB infection estimated by IGRA positivity were also evaluated by multivariate analysis using a logistic regression model, with IGRA result as outcome and factors possibly related to tuberculosis infection as independent variables.

This was followed by a multivariate analysis using logistic regression.

We continued the analysis of SNPs selected in the first step by individual multivariate analysis, using age and PS=2 as covariates.

Furthermore, by a multivariate analysis using the Cox proportional hazards model with inclusion of age and other clinical parameters, age was not selected in the final model as an independent predictor for survival.

The association between knowledge of symptoms and each sociodemographic variable was firstly examined using the Wilcoxon rank-sum test (for comparison of two groups) and Kruskal Wallis test (for comparison of more than two groups), followed by a multivariate analysis using ordinal logistic regression.

Finally, how the questionnaire scores were influenced by socio-demographic and morbidity indicators was studied by univariate and multivariate analysis, using the nonparametric quantile (Least Absolute Value) regression.