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Bivariate analyzes first, all variables then entered in the same model.
Bivariate analyzes first, then all variables entered in the same model.
However, more women with severe FOC experienced an induction of labour.> Table 2 shows the result of the bivariate analyzes of all outcome measures.
Relevant variables that reach significance in bivariate analyzes, will be entered into a multiple logistic regression analyses to determine their influence on sleep outcome variables.
In a first step, bivariate analyzes were performed to set up the description of the characteristics of the study population and production of crude prevalence ratios (with corresponding 95% confidence intervals) for associations between covariates and dental caries.
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Motivated by the above reasons, we here performed the first bivariate GWAS analyzing simultaneously two correlated diseases of public health significance, obesity and osteoporosis.
Data were analyzed using descriptive statistics, and bivariate correlations were analyzed using Pearson Chi-square, Mann-Whitney, or Kruskall-Wallis tests as appropriate.
Maintaining this category in bivariate and multivariate analyzes, resulted in very imprecise estimates.
The bivariate K-function analyzes only the relationship between Leishmania spp. positive households for persons and domestic animals in Dharan.
In order to identify potential trade-offs and synergies, we then analyzed bivariate relationships between different ecosystem services, and between individual ecosystem services and plant biodiversity.
In bivariate analysis, we analyzed risk factors for an unsuccessful outcome by age, sex, occupation, education, marital status, HIV risk group, residence in a rural district, adverse event during TB treatment, CTX use, prior history of TB, TB types, and registration status.
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